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## Data Processing Techniques and Transformations ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/data_processing_techniques_and_transformations))
<!-- [PLACEHOLDER_START:data_processing_techniques_and_transformations] -->
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:-------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------|
| <sub>[Advanced ML II](https://github.com/hudson-and-thames/research)</sub> | <sub>More implementations of Financial Machine Learning (De Prado).</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises too Financial Machine Learning (De Prado).</sub> | <sub>4/25/18 17:22</sub> | <sub>1/16/20 17:25</sub> | <sub>973.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data_processing_techniques_and_transformations] -->
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:----------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Advanced ML II](https://github.com/hudson-and-thames/research)</sub> | <sub>More implementations of Financial Machine Learning (De Prado).</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises too Financial Machine Learning (De Prado).</sub> | <sub>4/25/18 17:22</sub> | <sub>1/16/20 17:25</sub> | <sub>973.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint)</sub> | <sub>NEW</sub> | <sub>2016-09-26 19:42:54</sub> | <sub>2021-01-20 23:07:40</sub> | <sub>72.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis)</sub> | <sub>NEW</sub> | <sub>2017-07-23 02:59:59</sub> | <sub>2017-07-23 03:10:35</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Twitter-Trends](https://github.com/Medha11/Twitter-Trends)</sub> | <sub>NEW</sub> | <sub>2017-05-22 17:07:45</sub> | <sub>2017-05-23 08:06:27</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>NEW</sub> | <sub>2014-06-01 01:14:12</sub> | <sub>2020-10-22 00:24:50</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>NEW</sub> | <sub>2019-06-02 05:48:39</sub> | <sub>2019-09-12 13:03:05</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data_processing_techniques_and_transformations] -->
# Portfolio Management
@@ -102,8 +107,8 @@ ___
| <sub>[VaR GaN](https://github.com/hamaadshah/market_risk_gan_keras)</sub> | <sub>Estimate Value-at-Risk for market risk management using Keras and TensorFlow.</sub> | <sub>8/6/18 16:09</sub> | <sub>11/22/20 19:02</sub> | <sub>41.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Various Risk Measures](https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb)</sub> | <sub>Risk measures and factors for alternative and responsible investments.</sub> | <sub>8/7/17 14:44</sub> | <sub>8/8/17 22:52</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Pyfolio](https://github.com/quantopian/pyfolio)</sub> | <sub>Portfolio and risk analytics in Python.</sub> | <sub>6/1/15 15:31</sub> | <sub>2/28/20 17:30</sub> | <sub>3673.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Quant Finance](https://github.com/mrefermat/quant_finance)</sub> | <sub>General quant repository.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[CAPM](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb)</sub> | <sub>Expected returns using CAPM.</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Quant Finance](https://github.com/mrefermat/quant_finance)</sub> | <sub>General quant repository.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Risk Basic](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb)</sub> | <sub>Active portfolio risk management .</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Factor Analysis](https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb)</sub> | <sub>Factor analysis for mutual funds.</sub> | <sub>3/13/18 7:39</sub> | <sub>3/13/18 7:42</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Statistical Finance](https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments)</sub> | <sub>Various financial experiments.</sub> | <sub>10/4/15 9:10</sub> | <sub>3/28/20 18:33</sub> | <sub>21.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
@@ -122,9 +127,9 @@ ___
|:-------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[PCA Pairs Trading](https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading)</sub> | <sub>PCA, Factor Returns, and trading strategies.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Pairs Trading](https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb)</sub> | <sub>Finding pairs with cluster analysis.</sub> | <sub>9/5/17 19:19</sub> | <sub>9/27/17 20:42</sub> | <sub>79.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Project to cluster industries according to financial attributes.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Clustering of industries.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Fund Clusters](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb)</sub> | <sub>Data exploration of fund clusters.</sub> | <sub>4/16/18 22:18</sub> | <sub>6/7/18 22:01</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Project to cluster industries according to financial attributes.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[VRA Stock Embedding](https://github.com/ml-hongkong/stock2vec)</sub> | <sub>Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.</sub> | <sub>6/21/17 4:47</sub> | <sub>6/21/17 4:51</sub> | <sub>32.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:unsupervised] -->
@@ -157,8 +162,8 @@ ___
| <sub>[Option Strategies](https://github.com/rstreppa/valuation-OptionStrategies)</sub> | <sub>Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.</sub> | <sub>5/22/18 18:27</sub> | <sub>5/22/18 18:30</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Computational Derivatives](https://github.com/chenbowen184/Computational_Finance)</sub> | <sub>Projects focusing on investigating simulations and computational techniques applied in finance.</sub> | <sub>1/29/18 5:01</sub> | <sub>8/2/18 5:56</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Reinforcement Learning](https://github.com/FinTechies/HedgingRL)</sub> | <sub>Hedging portfolios with reinforcement learning.</sub> | <sub>4/21/17 10:58</sub> | <sub>8/2/17 21:41</sub> | <sub>16.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Options Risk Measures](https://github.com/wanglouis49/risk_estimation)</sub> | <sub>Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).</sub> | <sub>4/29/16 3:51</sub> | <sub>1/16/18 1:24</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Black Scholes](https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb)</sub> | <sub>Options pricing.</sub> | <sub>12/9/17 18:50</sub> | <sub>7/9/18 9:48</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Options Risk Measures](https://github.com/wanglouis49/risk_estimation)</sub> | <sub>Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).</sub> | <sub>4/29/16 3:51</sub> | <sub>1/16/18 1:24</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Derman](https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb)</sub> | <sub>Binomial tree for American call.</sub> | <sub>5/18/18 18:08</sub> | <sub>9/21/18 19:59</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:derivatives_and_hedging] -->
## Fixed Income ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/fixed_income))
@@ -186,20 +191,20 @@ ___
<!-- [PLACEHOLDER_START:extended_research] -->
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Commodity](https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb)</sub> | <sub>Commodity influence over Brazilian stocks.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Real Estate Property Fraud](https://github.com/aviroop1/Real_Estate_Property_Fraud)</sub> | <sub>Unsupervised fraud detection model that can identify likely candidates of fraud.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Commodity](https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb)</sub> | <sub>Commodity influence over Brazilian stocks.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Behavioural Economics](https://github.com/pcmichaud/notebooks)</sub> | <sub>Behavioural Economics and Finance Python Notebooks.</sub> | <sub>12/20/18 0:21</sub> | <sub>3/26/19 11:51</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Corporate Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance)</sub> | <sub>Basic corporate finance.</sub> | <sub>9/9/17 3:35</sub> | <sub>9/9/17 23:04</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Applied Corporate Finance](https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance)</sub> | <sub>Studies the empirical behaviours in stock market.</sub> | <sub>1/29/18 5:14</sub> | <sub>7/19/18 6:25</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[NLP Finance Papers](https://github.com/chenbowen184/Research_Documents_Curation_with_NLP)</sub> | <sub>Curating quantitative finance papers using machine learning.</sub> | <sub>10/11/18 20:32</sub> | <sub>12/24/18 23:27</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Applied Corporate Finance](https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance)</sub> | <sub>Studies the empirical behaviours in stock market.</sub> | <sub>1/29/18 5:14</sub> | <sub>7/19/18 6:25</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[HFT](https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy)</sub> | <sub>High frequency trading.</sub> | <sub>7/21/16 5:14</sub> | <sub>2/14/17 16:47</sub> | <sub>748.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Financial Economics](https://github.com/rsvp/fecon235/tree/master/nb)</sub> | <sub>Financial Economics Models.</sub> | <sub>11/9/14 4:49</sub> | <sub>12/3/18 16:30</sub> | <sub>713.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Mathematical Finance](https://github.com/Auquan/Tutorials)</sub> | <sub>Notebooks for math and financial tutorials.</sub> | <sub>1/21/17 11:24</sub> | <sub>8/1/20 17:03</sub> | <sub>664.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Backtests](https://github.com/AlgoTraders/stock-analysis-engine)</sub> | <sub>Trading data and algorithms.</sub> | <sub>9/16/18 20:00</sub> | <sub>9/5/20 13:01</sub> | <sub>620.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Liquidity and Momentum](https://github.com/mrefermat/quant_finance)</sub> | <sub>Various factors and portfolio constructions.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Currency PCA](https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb)</sub> | <sub>Forex spots PCA.</sub> | <sub>3/12/19 21:11</sub> | <sub>3/12/19 22:09</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Life-cycle](https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb)</sub> | <sub>Company life cycle.</sub> | <sub>1/19/19 18:16</sub> | <sub>2/18/19 16:57</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[M&A](https://github.com/atulram/Finance-and-Stocks)</sub> | <sub>Mergers and Acquisitions.</sub> | <sub>1/19/19 18:16</sub> | <sub>2/18/19 16:57</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Currency PCA](https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb)</sub> | <sub>Forex spots PCA.</sub> | <sub>3/12/19 21:11</sub> | <sub>3/12/19 22:09</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Deep Portfolio](https://github.com/DLColumbia/DL_forFinance)</sub> | <sub>Deep learning for finance Predict volume of bonds.</sub> | <sub>5/8/18 19:34</sub> | <sub>5/9/18 15:39</sub> | <sub>27.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:extended_research] -->
# Courses ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/courses))
@@ -221,14 +226,14 @@ ___
<!-- [PLACEHOLDER_START:data] -->
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Capital Markets Data](https://www.capitalmarketsdata.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[IRS](http://social-metrics.org/sox/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Financial Corporate](http://raw.rutgers.edu/Corporate%20Financial%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[http://finance.yahoo.com/](http://finance.yahoo.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Rating Industries](http://www.ratingshistory.info/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://fred.stlouisfed.org/](https://fred.stlouisfed.org/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Non-financial Corporate](http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://stooq.com](https://stooq.com)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Financial Corporate](http://raw.rutgers.edu/Corporate%20Financial%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://fred.stlouisfed.org/](https://fred.stlouisfed.org/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Rating Industries](http://www.ratingshistory.info/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[http://finance.yahoo.com/](http://finance.yahoo.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[IRS](http://social-metrics.org/sox/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Capital Markets Data](https://www.capitalmarketsdata.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[SEC Parsing](https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb)</sub> | <sub>nan</sub> | <sub>6/16/18 14:30</sub> | <sub>6/16/18 17:23</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[https://github.com/timestocome/StockMarketData](https://github.com/timestocome/StockMarketData)</sub> | <sub>nan</sub> | <sub>5/10/17 21:49</sub> | <sub>8/6/17 19:23</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Web Scraping (FirmAI)](https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data)</sub> | <sub>nan</sub> | <sub>2/19/19 19:02</sub> | <sub>7/22/20 16:48</sub> | <sub>577.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
@@ -240,9 +245,9 @@ ___
<!-- [PLACEHOLDER_START:colleges_centers_and_departments] -->
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------|:------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------|
| <sub>[NYU Courant](https://cims.nyu.edu/)</sub> | <sub>Courant Institute of Mathematical Sciences, New York University</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Oxford Man](https://www.oxford-man.ox.ac.uk/)</sub> | <sub>Oxford-Man Institute of Quantitative Finance</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering)</sub> | <sub>Finance and Risk Engineering (NYU Tandon)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Cornell University](https://www.cornell.edu/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Stanford Advanced Financial Technologies](https://fintech.stanford.edu/)</sub> | <sub>Stanford Advanced Financial Technologies Laboratory</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Cornell University](https://www.cornell.edu/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:colleges_centers_and_departments] -->
| <sub>[NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering)</sub> | <sub>Finance and Risk Engineering (NYU Tandon)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Oxford Man](https://www.oxford-man.ox.ac.uk/)</sub> | <sub>Oxford-Man Institute of Quantitative Finance</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NYU Courant](https://cims.nyu.edu/)</sub> | <sub>Courant Institute of Mathematical Sciences, New York University</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:colleges_centers_and_departments] -->
generated_wiki/colleges_centers_and_departments.md
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@@ -1,8 +1,8 @@
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------|:------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------|
| <sub>[NYU Courant](https://cims.nyu.edu/)</sub> | <sub>Courant Institute of Mathematical Sciences, New York University</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Oxford Man](https://www.oxford-man.ox.ac.uk/)</sub> | <sub>Oxford-Man Institute of Quantitative Finance</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering)</sub> | <sub>Finance and Risk Engineering (NYU Tandon)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Cornell University](https://www.cornell.edu/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Stanford Advanced Financial Technologies](https://fintech.stanford.edu/)</sub> | <sub>Stanford Advanced Financial Technologies Laboratory</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Cornell University](https://www.cornell.edu/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering)</sub> | <sub>Finance and Risk Engineering (NYU Tandon)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Oxford Man](https://www.oxford-man.ox.ac.uk/)</sub> | <sub>Oxford-Man Institute of Quantitative Finance</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NYU Courant](https://cims.nyu.edu/)</sub> | <sub>Courant Institute of Mathematical Sciences, New York University</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
generated_wiki/data.md
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| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Capital Markets Data](https://www.capitalmarketsdata.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[IRS](http://social-metrics.org/sox/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Financial Corporate](http://raw.rutgers.edu/Corporate%20Financial%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[http://finance.yahoo.com/](http://finance.yahoo.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Rating Industries](http://www.ratingshistory.info/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://fred.stlouisfed.org/](https://fred.stlouisfed.org/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Non-financial Corporate](http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://stooq.com](https://stooq.com)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Financial Corporate](http://raw.rutgers.edu/Corporate%20Financial%20Data.html)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[https://fred.stlouisfed.org/](https://fred.stlouisfed.org/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Rating Industries](http://www.ratingshistory.info/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[http://finance.yahoo.com/](http://finance.yahoo.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[IRS](http://social-metrics.org/sox/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Capital Markets Data](https://www.capitalmarketsdata.com/)</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[SEC Parsing](https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb)</sub> | <sub>nan</sub> | <sub>6/16/18 14:30</sub> | <sub>6/16/18 17:23</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[https://github.com/timestocome/StockMarketData](https://github.com/timestocome/StockMarketData)</sub> | <sub>nan</sub> | <sub>5/10/17 21:49</sub> | <sub>8/6/17 19:23</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Web Scraping (FirmAI)](https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data)</sub> | <sub>nan</sub> | <sub>2/19/19 19:02</sub> | <sub>7/22/20 16:48</sub> | <sub>577.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
generated_wiki/data_processing_techniques_and_transformations.md
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@@ -1,4 +1,9 @@
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:-------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------|
| <sub>[Advanced ML II](https://github.com/hudson-and-thames/research)</sub> | <sub>More implementations of Financial Machine Learning (De Prado).</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises too Financial Machine Learning (De Prado).</sub> | <sub>4/25/18 17:22</sub> | <sub>1/16/20 17:25</sub> | <sub>973.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:----------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Advanced ML II](https://github.com/hudson-and-thames/research)</sub> | <sub>More implementations of Financial Machine Learning (De Prado).</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises too Financial Machine Learning (De Prado).</sub> | <sub>4/25/18 17:22</sub> | <sub>1/16/20 17:25</sub> | <sub>973.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint)</sub> | <sub>NEW</sub> | <sub>2016-09-26 19:42:54</sub> | <sub>2021-01-20 23:07:40</sub> | <sub>72.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis)</sub> | <sub>NEW</sub> | <sub>2017-07-23 02:59:59</sub> | <sub>2017-07-23 03:10:35</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Twitter-Trends](https://github.com/Medha11/Twitter-Trends)</sub> | <sub>NEW</sub> | <sub>2017-05-22 17:07:45</sub> | <sub>2017-05-23 08:06:27</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>NEW</sub> | <sub>2014-06-01 01:14:12</sub> | <sub>2020-10-22 00:24:50</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>NEW</sub> | <sub>2019-06-02 05:48:39</sub> | <sub>2019-09-12 13:03:05</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
generated_wiki/deep_learning_and_reinforcement_learning.md
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| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Stock-Prediction-Models](https://github.com/huseinzol05/Stock-Prediction-Models)</sub> | <sub>very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert))</sub> | <sub>12/18/17 10:49</sub> | <sub>1/5/21 10:31</sub> | <sub>3655.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[AI Trading](https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md)</sub> | <sub>AI to predict stock market movements.</sub> | <sub>1/9/19 8:02</sub> | <sub>2/11/19 16:32</sub> | <sub>2876.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[FinRL-Library](https://github.com/AI4Finance-LLC/FinRL-Library)</sub> | <sub>started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading</sub> | <sub>7/26/20 13:18</sub> | <sub>4/11/21 22:02</sub> | <sub>1857.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[Deep Learning IV](https://github.com/achillesrasquinha/bulbea)</sub> | <sub>Bulbea: Deep Learning based Python Library.</sub> | <sub>3/9/17 6:11</sub> | <sub>3/19/17 7:42</sub> | <sub>1467.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[RLTrader](https://github.com/notadamking/RLTrader)</sub> | <sub>predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc.</sub> | <sub>4/27/19 18:35</sub> | <sub>10/17/19 16:25</sub> | <sub>1312.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[Deep Learning III](https://github.com/Rachnog/Deep-Trading)</sub> | <sub>Algorithmic trading with deep learning experiments.</sub> | <sub>6/18/16 18:23</sub> | <sub>8/7/18 15:24</sub> | <sub>1266.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[Personae](https://github.com/Ceruleanacg/Personae)</sub> | <sub>implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing</sub> | <sub>3/10/18 11:22</sub> | <sub>9/2/18 17:21</sub> | <sub>1144.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[RL Trading](https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW)</sub> | <sub>A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020](https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020)</sub> | <sub>Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble.</sub> | <sub>7/26/20 13:12</sub> | <sub>1/21/21 18:11</sub> | <sub>560.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>551.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[Neural Network](https://github.com/VivekPa/IntroNeuralNetworks)</sub> | <sub>Neural networks to predict stock prices.</sub> | <sub>9/10/18 6:34</sub> | <sub>11/21/18 7:39</sub> | <sub>489.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
| <sub>[Deep Learning](https://github.com/keon/deepstock)</sub> | <sub>Technical experimentations to beat the stock market using deep learning.</sub> | <sub>12/12/16 2:15</sub> | <sub>3/4/17 8:37</sub> | <sub>427.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
| <sub>[LTSM Recurrent](https://github.com/VivekPa/AIAlpha)</sub> | <sub>OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.</sub> | <sub>10/7/18 3:58</sub> | <sub>8/3/19 9:00</sub> | <sub>1207.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[RL III](https://github.com/samre12/deep-trading-agent)</sub> | <sub>Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.</sub> | <sub>9/21/17 17:05</sub> | <sub>4/13/18 16:33</sub> | <sub>576.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[crypto-rl](https://github.com/sadighian/crypto-rl)</sub> | <sub>Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process)</sub> | <sub>6/21/18 1:06</sub> | <sub>11/5/20 11:08</sub> | <sub>347.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Advanced-Deep-Trading](https://github.com/Rachnog/Advanced-Deep-Trading)</sub> | <sub>notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. </sub> | <sub>2/16/19 21:18</sub> | <sub>11/29/20 20:12</sub> | <sub>319.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[trading-bot](https://github.com/pskrunner14/trading-bot)</sub> | <sub>Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python </sub> | <sub>8/13/18 10:44</sub> | <sub>1/23/20 4:41</sub> | <sub>292.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[BitcoinForecast](https://github.com/PiSimo/BitcoinForecast)</sub> | <sub>RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model </sub> | <sub>3/10/17 10:52</sub> | <sub>6/11/18 8:07</sub> | <sub>289.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Learning-Machine-Learning-Stock](https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock)</sub> | <sub>curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade</sub> | <sub>9/29/18 23:38</sub> | <sub>3/18/21 3:16</sub> | <sub>275.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[DeepLearningInFinance](https://github.com/sonaam1234/DeepLearningInFinance)</sub> | <sub>Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. </sub> | <sub>8/21/17 16:00</sub> | <sub>8/21/17 17:23</sub> | <sub>266.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Pair Trading RL](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading)</sub> | <sub>Using deep actor-critic model to learn best strategies in pair trading.</sub> | <sub>5/18/17 16:47</sub> | <sub>5/18/17 16:56</sub> | <sub>241.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[deep-RL-trading](https://github.com/golsun/deep-RL-trading)</sub> | <sub>trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916)</sub> | <sub>2/25/18 17:41</sub> | <sub>12/1/20 22:06</sub> | <sub>235.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[ARIMA-LTSM Hybrid](https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid)</sub> | <sub>Hybrid model to predict future price correlation coefficients of two assets.</sub> | <sub>8/5/18 2:13</sub> | <sub>10/1/18 11:25</sub> | <sub>222.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[trading-rl](https://github.com/Kostis-S-Z/trading-rl)</sub> | <sub>Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained</sub> | <sub>4/22/19 10:03</sub> | <sub>9/28/20 9:07</sub> | <sub>180.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep Learning II](https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks)</sub> | <sub>Tensorflow Regression.</sub> | <sub>7/12/16 12:56</sub> | <sub>2/16/18 2:43</sub> | <sub>175.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Reinforcement-Stock-Trading](https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading)</sub> | <sub>inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats</sub> | <sub>5/19/19 22:20</sub> | <sub>9/27/20 19:22</sub> | <sub>141.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Reinforcement-Learning-in-Trading](https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading)</sub> | <sub>Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman)</sub> | <sub>5/11/18 0:52</sub> | <sub>10/26/19 14:22</sub> | <sub>138.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[DQN-DDPG_Stock_Trading](https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading)</sub> | <sub>merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN</sub> | <sub>9/19/18 3:17</sub> | <sub>11/26/20 16:58</sub> | <sub>136.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[RL II](https://github.com/deependersingla/deep_trader)</sub> | <sub>reinforcement learning on stock market and agent tries to learn trading.</sub> | <sub>6/11/16 7:27</sub> | <sub>1/22/18 14:35</sub> | <sub>1340.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[AutomatedStockTrading-DeepQ-Learning](https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning)</sub> | <sub>cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report</sub> | <sub>2/23/19 12:01</sub> | <sub>2/25/20 18:16</sub> | <sub>134.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[LTSM GRU](https://github.com/RajatHanda/Finance-Forecasting)</sub> | <sub>Stock Market Forecasting using LSTM\GRU.</sub> | <sub>5/13/18 2:39</sub> | <sub>2/25/19 0:26</sub> | <sub>11.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[RL](https://github.com/kh-kim/stock_market_reinforcement_learning)</sub> | <sub>OpenGym with Deep Q-learning and Policy Gradient.</sub> | <sub>10/4/16 14:42</sub> | <sub>12/23/16 7:34</sub> | <sub>715.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
| <sub>[RL V](https://github.com/gstenger98/rl-finance)</sub> | <sub>Building an Agent to Trade with Reinforcement Learning.</sub> | <sub>1/16/19 0:43</sub> | <sub>3/19/20 20:28</sub> | <sub>33.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |
| <sub>[TradingGym](https://github.com/Yvictor/TradingGym)</sub> | <sub>NEW</sub> | <sub>5/1/17 13:53</sub> | <sub>2/14/18 13:58</sub> | <sub>841.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[gym-trading](https://github.com/hackthemarket/gym-trading)</sub> | <sub>NEW</sub> | <sub>12/9/16 20:46</sub> | <sub>12/24/17 15:34</sub> | <sub>581.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Trading-Gym](https://github.com/thedimlebowski/Trading-Gym)</sub> | <sub>NEW</sub> | <sub>6/13/17 13:14</sub> | <sub>7/10/17 8:09</sub> | <sub>507.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[QLearning_Trading](https://github.com/ucaiado/QLearning_Trading)</sub> | <sub>NEW</sub> | <sub>8/10/16 6:02</sub> | <sub>10/15/16 2:36</sub> | <sub>433.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[maro](https://github.com/microsoft/maro)</sub> | <sub>NEW</sub> | <sub>12/27/19 6:48</sub> | <sub>4/7/21 15:49</sub> | <sub>386.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[a3c_trading](https://github.com/evgps/a3c_trading)</sub> | <sub>NEW</sub> | <sub>6/4/18 15:30</sub> | <sub>5/23/20 14:47</sub> | <sub>311.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[tensortrade](https://github.com/tensortrade-org/tensortrade)</sub> | <sub>NEW</sub> | <sub>7/30/19 21:28</sub> | <sub>3/24/21 16:25</sub> | <sub>3101.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[RLQuant](https://github.com/yuriak/RLQuant)</sub> | <sub>NEW</sub> | <sub>4/5/18 5:42</sub> | <sub>8/13/18 4:18</sub> | <sub>277.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[rl_trading](https://github.com/ucaiado/rl_trading)</sub> | <sub>NEW</sub> | <sub>5/29/17 22:19</sub> | <sub>8/29/17 14:54</sub> | <sub>207.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Machine-Learning-and-Reinforcement-Learning-in-Finance](https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance)</sub> | <sub>NEW</sub> | <sub>6/26/18 4:30</sub> | <sub>9/23/18 16:50</sub> | <sub>175.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[RL IV](https://github.com/jjakimoto/DQN)</sub> | <sub>Reinforcement Learning for finance.</sub> | <sub>10/21/16 2:47</sub> | <sub>4/7/17 8:11</sub> | <sub>142.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Pair-Trading-Reinforcement-Learning](https://github.com/wai-i/Pair-Trading-Reinforcement-Learning)</sub> | <sub>NEW</sub> | <sub>6/9/19 22:50</sub> | <sub>1/3/20 15:36</sub> | <sub>136.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[TradingGym](https://github.com/cove9988/TradingGym)</sub> | <sub>NEW</sub> | <sub>11/6/17 0:50</sub> | <sub>11/15/17 23:55</sub> | <sub>112.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[pairstrade-fyp-2019](https://github.com/wywongbd/pairstrade-fyp-2019)</sub> | <sub>NEW</sub> | <sub>9/7/18 7:51</sub> | <sub>5/13/20 5:06</sub> | <sub>110.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Stock-Prediction-Models](https://github.com/huseinzol05/Stock-Prediction-Models)</sub> | <sub>very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert))</sub> | <sub>12/18/17 10:49</sub> | <sub>1/5/21 10:31</sub> | <sub>3655.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[AI Trading](https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md)</sub> | <sub>AI to predict stock market movements.</sub> | <sub>1/9/19 8:02</sub> | <sub>2/11/19 16:32</sub> | <sub>2876.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[FinRL-Library](https://github.com/AI4Finance-LLC/FinRL-Library)</sub> | <sub>started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading</sub> | <sub>7/26/20 13:18</sub> | <sub>4/11/21 22:02</sub> | <sub>1857.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[Deep Learning IV](https://github.com/achillesrasquinha/bulbea)</sub> | <sub>Bulbea: Deep Learning based Python Library.</sub> | <sub>3/9/17 6:11</sub> | <sub>3/19/17 7:42</sub> | <sub>1467.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[RLTrader](https://github.com/notadamking/RLTrader)</sub> | <sub>predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc.</sub> | <sub>4/27/19 18:35</sub> | <sub>10/17/19 16:25</sub> | <sub>1312.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
| <sub>[Deep Learning III](https://github.com/Rachnog/Deep-Trading)</sub> | <sub>Algorithmic trading with deep learning experiments.</sub> | <sub>6/18/16 18:23</sub> | <sub>8/7/18 15:24</sub> | <sub>1266.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[Personae](https://github.com/Ceruleanacg/Personae)</sub> | <sub>implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing</sub> | <sub>3/10/18 11:22</sub> | <sub>9/2/18 17:21</sub> | <sub>1144.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
| <sub>[RL Trading](https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW)</sub> | <sub>A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020](https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020)</sub> | <sub>Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble.</sub> | <sub>7/26/20 13:12</sub> | <sub>1/21/21 18:11</sub> | <sub>560.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>551.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[Neural Network](https://github.com/VivekPa/IntroNeuralNetworks)</sub> | <sub>Neural networks to predict stock prices.</sub> | <sub>9/10/18 6:34</sub> | <sub>11/21/18 7:39</sub> | <sub>489.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
| <sub>[Deep Learning](https://github.com/keon/deepstock)</sub> | <sub>Technical experimentations to beat the stock market using deep learning.</sub> | <sub>12/12/16 2:15</sub> | <sub>3/4/17 8:37</sub> | <sub>427.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
| <sub>[LTSM Recurrent](https://github.com/VivekPa/AIAlpha)</sub> | <sub>OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.</sub> | <sub>10/7/18 3:58</sub> | <sub>8/3/19 9:00</sub> | <sub>1207.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
| <sub>[RL III](https://github.com/samre12/deep-trading-agent)</sub> | <sub>Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.</sub> | <sub>9/21/17 17:05</sub> | <sub>4/13/18 16:33</sub> | <sub>576.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[crypto-rl](https://github.com/sadighian/crypto-rl)</sub> | <sub>Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process)</sub> | <sub>6/21/18 1:06</sub> | <sub>11/5/20 11:08</sub> | <sub>347.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Advanced-Deep-Trading](https://github.com/Rachnog/Advanced-Deep-Trading)</sub> | <sub>notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. </sub> | <sub>2/16/19 21:18</sub> | <sub>11/29/20 20:12</sub> | <sub>319.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[trading-bot](https://github.com/pskrunner14/trading-bot)</sub> | <sub>Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python </sub> | <sub>8/13/18 10:44</sub> | <sub>1/23/20 4:41</sub> | <sub>292.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[BitcoinForecast](https://github.com/PiSimo/BitcoinForecast)</sub> | <sub>RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model </sub> | <sub>3/10/17 10:52</sub> | <sub>6/11/18 8:07</sub> | <sub>289.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Learning-Machine-Learning-Stock](https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock)</sub> | <sub>curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade</sub> | <sub>9/29/18 23:38</sub> | <sub>3/18/21 3:16</sub> | <sub>275.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[DeepLearningInFinance](https://github.com/sonaam1234/DeepLearningInFinance)</sub> | <sub>Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. </sub> | <sub>8/21/17 16:00</sub> | <sub>8/21/17 17:23</sub> | <sub>266.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Pair Trading RL](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading)</sub> | <sub>Using deep actor-critic model to learn best strategies in pair trading.</sub> | <sub>5/18/17 16:47</sub> | <sub>5/18/17 16:56</sub> | <sub>241.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[deep-RL-trading](https://github.com/golsun/deep-RL-trading)</sub> | <sub>trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916)</sub> | <sub>2/25/18 17:41</sub> | <sub>12/1/20 22:06</sub> | <sub>235.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[ARIMA-LTSM Hybrid](https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid)</sub> | <sub>Hybrid model to predict future price correlation coefficients of two assets.</sub> | <sub>8/5/18 2:13</sub> | <sub>10/1/18 11:25</sub> | <sub>222.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[trading-rl](https://github.com/Kostis-S-Z/trading-rl)</sub> | <sub>Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained</sub> | <sub>4/22/19 10:03</sub> | <sub>9/28/20 9:07</sub> | <sub>180.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep Learning II](https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks)</sub> | <sub>Tensorflow Regression.</sub> | <sub>7/12/16 12:56</sub> | <sub>2/16/18 2:43</sub> | <sub>175.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Reinforcement-Stock-Trading](https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading)</sub> | <sub>inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats</sub> | <sub>5/19/19 22:20</sub> | <sub>9/27/20 19:22</sub> | <sub>141.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[Deep-Reinforcement-Learning-in-Trading](https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading)</sub> | <sub>Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman)</sub> | <sub>5/11/18 0:52</sub> | <sub>10/26/19 14:22</sub> | <sub>138.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[DQN-DDPG_Stock_Trading](https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading)</sub> | <sub>merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN</sub> | <sub>9/19/18 3:17</sub> | <sub>11/26/20 16:58</sub> | <sub>136.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[RL II](https://github.com/deependersingla/deep_trader)</sub> | <sub>reinforcement learning on stock market and agent tries to learn trading.</sub> | <sub>6/11/16 7:27</sub> | <sub>1/22/18 14:35</sub> | <sub>1340.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[AutomatedStockTrading-DeepQ-Learning](https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning)</sub> | <sub>cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report</sub> | <sub>2/23/19 12:01</sub> | <sub>2/25/20 18:16</sub> | <sub>134.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |
| <sub>[LTSM GRU](https://github.com/RajatHanda/Finance-Forecasting)</sub> | <sub>Stock Market Forecasting using LSTM\GRU.</sub> | <sub>5/13/18 2:39</sub> | <sub>2/25/19 0:26</sub> | <sub>11.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
| <sub>[RL](https://github.com/kh-kim/stock_market_reinforcement_learning)</sub> | <sub>OpenGym with Deep Q-learning and Policy Gradient.</sub> | <sub>10/4/16 14:42</sub> | <sub>12/23/16 7:34</sub> | <sub>715.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
| <sub>[RL V](https://github.com/gstenger98/rl-finance)</sub> | <sub>Building an Agent to Trade with Reinforcement Learning.</sub> | <sub>1/16/19 0:43</sub> | <sub>3/19/20 20:28</sub> | <sub>33.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |
| <sub>[TradingGym](https://github.com/Yvictor/TradingGym)</sub> | <sub>NEW</sub> | <sub>5/1/17 13:53</sub> | <sub>2/14/18 13:58</sub> | <sub>841.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[gym-trading](https://github.com/hackthemarket/gym-trading)</sub> | <sub>NEW</sub> | <sub>12/9/16 20:46</sub> | <sub>12/24/17 15:34</sub> | <sub>581.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Trading-Gym](https://github.com/thedimlebowski/Trading-Gym)</sub> | <sub>NEW</sub> | <sub>6/13/17 13:14</sub> | <sub>7/10/17 8:09</sub> | <sub>507.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[QLearning_Trading](https://github.com/ucaiado/QLearning_Trading)</sub> | <sub>NEW</sub> | <sub>8/10/16 6:02</sub> | <sub>10/15/16 2:36</sub> | <sub>433.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[maro](https://github.com/microsoft/maro)</sub> | <sub>NEW</sub> | <sub>12/27/19 6:48</sub> | <sub>4/7/21 15:49</sub> | <sub>386.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[a3c_trading](https://github.com/evgps/a3c_trading)</sub> | <sub>NEW</sub> | <sub>6/4/18 15:30</sub> | <sub>5/23/20 14:47</sub> | <sub>311.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[tensortrade](https://github.com/tensortrade-org/tensortrade)</sub> | <sub>NEW</sub> | <sub>7/30/19 21:28</sub> | <sub>3/24/21 16:25</sub> | <sub>3101.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[RLQuant](https://github.com/yuriak/RLQuant)</sub> | <sub>NEW</sub> | <sub>4/5/18 5:42</sub> | <sub>8/13/18 4:18</sub> | <sub>277.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[rl_trading](https://github.com/ucaiado/rl_trading)</sub> | <sub>NEW</sub> | <sub>5/29/17 22:19</sub> | <sub>8/29/17 14:54</sub> | <sub>207.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[FinRL](https://github.com/AI4Finance-LLC/FinRL)</sub> | <sub>NEW</sub> | <sub>2020-07-26 13:18:16</sub> | <sub>2021-04-11 22:02:16</sub> | <sub>1865.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Machine-Learning-and-Reinforcement-Learning-in-Finance](https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance)</sub> | <sub>NEW</sub> | <sub>6/26/18 4:30</sub> | <sub>9/23/18 16:50</sub> | <sub>175.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[RL IV](https://github.com/jjakimoto/DQN)</sub> | <sub>Reinforcement Learning for finance.</sub> | <sub>10/21/16 2:47</sub> | <sub>4/7/17 8:11</sub> | <sub>142.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Pair-Trading-Reinforcement-Learning](https://github.com/wai-i/Pair-Trading-Reinforcement-Learning)</sub> | <sub>NEW</sub> | <sub>6/9/19 22:50</sub> | <sub>1/3/20 15:36</sub> | <sub>136.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[TradingGym](https://github.com/cove9988/TradingGym)</sub> | <sub>NEW</sub> | <sub>11/6/17 0:50</sub> | <sub>11/15/17 23:55</sub> | <sub>112.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[pairstrade-fyp-2019](https://github.com/wywongbd/pairstrade-fyp-2019)</sub> | <sub>NEW</sub> | <sub>9/7/18 7:51</sub> | <sub>5/13/20 5:06</sub> | <sub>110.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
generated_wiki/derivatives_and_hedging.md
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| <sub>[Option Strategies](https://github.com/rstreppa/valuation-OptionStrategies)</sub> | <sub>Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.</sub> | <sub>5/22/18 18:27</sub> | <sub>5/22/18 18:30</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Computational Derivatives](https://github.com/chenbowen184/Computational_Finance)</sub> | <sub>Projects focusing on investigating simulations and computational techniques applied in finance.</sub> | <sub>1/29/18 5:01</sub> | <sub>8/2/18 5:56</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Reinforcement Learning](https://github.com/FinTechies/HedgingRL)</sub> | <sub>Hedging portfolios with reinforcement learning.</sub> | <sub>4/21/17 10:58</sub> | <sub>8/2/17 21:41</sub> | <sub>16.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Options Risk Measures](https://github.com/wanglouis49/risk_estimation)</sub> | <sub>Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).</sub> | <sub>4/29/16 3:51</sub> | <sub>1/16/18 1:24</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Black Scholes](https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb)</sub> | <sub>Options pricing.</sub> | <sub>12/9/17 18:50</sub> | <sub>7/9/18 9:48</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Options Risk Measures](https://github.com/wanglouis49/risk_estimation)</sub> | <sub>Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).</sub> | <sub>4/29/16 3:51</sub> | <sub>1/16/18 1:24</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Derman](https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb)</sub> | <sub>Binomial tree for American call.</sub> | <sub>5/18/18 18:08</sub> | <sub>9/21/18 19:59</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
generated_wiki/extended_research.md
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| <sub>repo</sub> | <sub>comment</sub> | <sub>created_at</sub> | <sub>last_commit</sub> | <sub>star_count</sub> | <sub>repo_status</sub> | <sub>rating</sub> |
|:-----------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[Commodity](https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb)</sub> | <sub>Commodity influence over Brazilian stocks.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Real Estate Property Fraud](https://github.com/aviroop1/Real_Estate_Property_Fraud)</sub> | <sub>Unsupervised fraud detection model that can identify likely candidates of fraud.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Commodity](https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb)</sub> | <sub>Commodity influence over Brazilian stocks.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Behavioural Economics](https://github.com/pcmichaud/notebooks)</sub> | <sub>Behavioural Economics and Finance Python Notebooks.</sub> | <sub>12/20/18 0:21</sub> | <sub>3/26/19 11:51</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Corporate Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance)</sub> | <sub>Basic corporate finance.</sub> | <sub>9/9/17 3:35</sub> | <sub>9/9/17 23:04</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Applied Corporate Finance](https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance)</sub> | <sub>Studies the empirical behaviours in stock market.</sub> | <sub>1/29/18 5:14</sub> | <sub>7/19/18 6:25</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[NLP Finance Papers](https://github.com/chenbowen184/Research_Documents_Curation_with_NLP)</sub> | <sub>Curating quantitative finance papers using machine learning.</sub> | <sub>10/11/18 20:32</sub> | <sub>12/24/18 23:27</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Applied Corporate Finance](https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance)</sub> | <sub>Studies the empirical behaviours in stock market.</sub> | <sub>1/29/18 5:14</sub> | <sub>7/19/18 6:25</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[HFT](https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy)</sub> | <sub>High frequency trading.</sub> | <sub>7/21/16 5:14</sub> | <sub>2/14/17 16:47</sub> | <sub>748.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Financial Economics](https://github.com/rsvp/fecon235/tree/master/nb)</sub> | <sub>Financial Economics Models.</sub> | <sub>11/9/14 4:49</sub> | <sub>12/3/18 16:30</sub> | <sub>713.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Mathematical Finance](https://github.com/Auquan/Tutorials)</sub> | <sub>Notebooks for math and financial tutorials.</sub> | <sub>1/21/17 11:24</sub> | <sub>8/1/20 17:03</sub> | <sub>664.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Backtests](https://github.com/AlgoTraders/stock-analysis-engine)</sub> | <sub>Trading data and algorithms.</sub> | <sub>9/16/18 20:00</sub> | <sub>9/5/20 13:01</sub> | <sub>620.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Liquidity and Momentum](https://github.com/mrefermat/quant_finance)</sub> | <sub>Various factors and portfolio constructions.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Currency PCA](https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb)</sub> | <sub>Forex spots PCA.</sub> | <sub>3/12/19 21:11</sub> | <sub>3/12/19 22:09</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Life-cycle](https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb)</sub> | <sub>Company life cycle.</sub> | <sub>1/19/19 18:16</sub> | <sub>2/18/19 16:57</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[M&A](https://github.com/atulram/Finance-and-Stocks)</sub> | <sub>Mergers and Acquisitions.</sub> | <sub>1/19/19 18:16</sub> | <sub>2/18/19 16:57</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Currency PCA](https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb)</sub> | <sub>Forex spots PCA.</sub> | <sub>3/12/19 21:11</sub> | <sub>3/12/19 22:09</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Deep Portfolio](https://github.com/DLColumbia/DL_forFinance)</sub> | <sub>Deep learning for finance Predict volume of bonds.</sub> | <sub>5/8/18 19:34</sub> | <sub>5/9/18 15:39</sub> | <sub>27.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Bayesian Finance I](https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb)</sub> | <sub>Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs.</sub> | <sub>1/4/19 12:30</sub> | <sub>2/18/19 9:55</sub> | <sub>25.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[High Frequency](https://github.com/cswaney/prickle)</sub> | <sub>A Python toolkit for high-frequency trade research.</sub> | <sub>7/6/16 20:32</sub> | <sub>6/9/18 10:53</sub> | <sub>24.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Bayesian Finance](https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb)</sub> | <sub>Notebook PyMC3 implementation.</sub> | <sub>8/28/18 14:45</sub> | <sub>8/6/20 22:03</sub> | <sub>233.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Economic Foundations](https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations)</sub> | <sub>Basic economic models.</sub> | <sub>5/25/17 2:27</sub> | <sub>6/30/17 3:53</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Finance Graph Theory](https://github.com/AvijitGhosh82/Finance_Graph_Theory)</sub> | <sub>Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.</sub> | <sub>8/2/18 2:48</sub> | <sub>3/16/19 18:39</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Simulation](https://github.com/chenbowen184/Computational_Finance)</sub> | <sub>Investigating simulations as part of computational finance.</sub> | <sub>1/29/18 5:01</sub> | <sub>8/2/18 5:56</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Finance Graph Theory](https://github.com/AvijitGhosh82/Finance_Graph_Theory)</sub> | <sub>Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.</sub> | <sub>8/2/18 2:48</sub> | <sub>3/16/19 18:39</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Computational Finance](https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance)</sub> | <sub>Applied Computational Economics and Finance.</sub> | <sub>8/27/17 3:46</sub> | <sub>8/26/17 4:26</sub> | <sub>12.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Critical Transitions](https://github.com/ryanholbrook/critical-transitions)</sub> | <sub>Detecting critical transitions in financial networks with topological data analysis.</sub> | <sub>1/22/19 10:59</sub> | <sub>3/12/19 18:35</sub> | <sub>10.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Market Crash Prediction](https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb)</sub> | <sub>Predicting market crashes using an LPPL model.</sub> | <sub>1/24/19 13:37</sub> | <sub>2/13/19 16:48</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
generated_wiki/factor_and_risk_analysis.md
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| <sub>[VaR GaN](https://github.com/hamaadshah/market_risk_gan_keras)</sub> | <sub>Estimate Value-at-Risk for market risk management using Keras and TensorFlow.</sub> | <sub>8/6/18 16:09</sub> | <sub>11/22/20 19:02</sub> | <sub>41.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Various Risk Measures](https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb)</sub> | <sub>Risk measures and factors for alternative and responsible investments.</sub> | <sub>8/7/17 14:44</sub> | <sub>8/8/17 22:52</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Pyfolio](https://github.com/quantopian/pyfolio)</sub> | <sub>Portfolio and risk analytics in Python.</sub> | <sub>6/1/15 15:31</sub> | <sub>2/28/20 17:30</sub> | <sub>3673.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Quant Finance](https://github.com/mrefermat/quant_finance)</sub> | <sub>General quant repository.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[CAPM](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb)</sub> | <sub>Expected returns using CAPM.</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Quant Finance](https://github.com/mrefermat/quant_finance)</sub> | <sub>General quant repository.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Risk Basic](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb)</sub> | <sub>Active portfolio risk management .</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Factor Analysis](https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb)</sub> | <sub>Factor analysis for mutual funds.</sub> | <sub>3/13/18 7:39</sub> | <sub>3/13/18 7:42</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Statistical Finance](https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments)</sub> | <sub>Various financial experiments.</sub> | <sub>10/4/15 9:10</sub> | <sub>3/28/20 18:33</sub> | <sub>21.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
generated_wiki/unsupervised.md
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|:-------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
| <sub>[PCA Pairs Trading](https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading)</sub> | <sub>PCA, Factor Returns, and trading strategies.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Pairs Trading](https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb)</sub> | <sub>Finding pairs with cluster analysis.</sub> | <sub>9/5/17 19:19</sub> | <sub>9/27/17 20:42</sub> | <sub>79.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Project to cluster industries according to financial attributes.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Clustering of industries.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Fund Clusters](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb)</sub> | <sub>Data exploration of fund clusters.</sub> | <sub>4/16/18 22:18</sub> | <sub>6/7/18 22:01</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries)</sub> | <sub>Project to cluster industries according to financial attributes.</sub> | <sub>7/21/17 2:12</sub> | <sub>7/23/17 2:53</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[VRA Stock Embedding](https://github.com/ml-hongkong/stock2vec)</sub> | <sub>Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.</sub> | <sub>6/21/17 4:47</sub> | <sub>6/21/17 4:51</sub> | <sub>32.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
raw_data/url_list.csv
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@@ -1,206 +1,212 @@
name,url,comment,category,last_update,star_count,fork_count,contributors_count,created_at,last_commit,repo_path,repo_status,rating,finml_added_date
Venture Capital NN,https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring,Cox-PH neural network predictions for VC/innovations finance research.,Alternative Finance,,,,,,,tr7200/National-Culture-and-Venture-Capital-Monitoring,,,
Private Equity,https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb,Valuation models.,Alternative Finance,11/26/20 3:34,8,6,2,1/27/16 21:13,3/14/16 20:03,TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity,inactive,,
VC OLS,https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb,VC regression.,Alternative Finance,10/6/20 20:56,2,1,1,3/29/18 23:31,3/29/18 23:33,fionawhitefield/venture-capital-ols,inactive,,
Watch Valuation,https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb,Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued.,Alternative Finance,1/14/21 22:41,4,2,1,2/8/17 18:39,4/27/17 22:55,alporter08/Luxury-Watch-Valuation,inactive,,
Art Valuation,https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb,Art evaluation analytics.,Alternative Finance,2/26/21 12:10,9,5,1,12/11/14 0:25,12/12/14 21:25,ahmedhosny/theGreenCanvas,inactive,,
Blockchain,https://github.com/nud3l/dInvest,Repository for distributed autonomous investment banking.,Alternative Finance,2/6/21 7:38,12,7,2,9/5/16 19:12,4/24/17 10:48,nud3l/dInvest,inactive,,
Venture Capital,https://github.com/julian-chan/etothex,Insight into a new founder to make data-driven investment decisions.,Alternative Finance,10/6/20 20:56,3,2,1,12/4/17 8:59,12/13/17 5:35,julian-chan/etothex,inactive,,
Kiva Crowdfunding,https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb,Exploratory data analysis.,Alternative Finance,2/19/21 13:40,5,1,1,2/27/18 16:46,2/13/19 0:15,CJL89/Kiva-Crowdfunding,inactive,,
NYU Courant,https://cims.nyu.edu/,"Courant Institute of Mathematical Sciences, New York University",Colleges Centers and Departments,,,,,,,,,,
Oxford Man,https://www.oxford-man.ox.ac.uk/,Oxford-Man Institute of Quantitative Finance,Colleges Centers and Departments,,,,,,,,,,
Berkeley Lab CIFT,https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/,,Colleges Centers and Departments,,,,,,,,,,
NYU FRE,https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering,Finance and Risk Engineering (NYU Tandon),Colleges Centers and Departments,,,,,,,,,,
Stanford Advanced Financial Technologies,https://fintech.stanford.edu/,Stanford Advanced Financial Technologies Laboratory,Colleges Centers and Departments,,,,,,,,,,
Cornell University,https://www.cornell.edu/,,Colleges Centers and Departments,,,,,,,,,,
Basic Investments,https://github.com/SeanMcOwen/FinanceAndPython.com-Investments,Basic investment tools in python.,Courses,3/23/21 6:32,9,5,1,8/2/17 21:52,8/17/17 3:24,SeanMcOwen/FinanceAndPython.com-Investments,inactive,,
Risk Management,https://github.com/andrey-lukyanov/Risk-Management,Finance risk engagement course resources.,Courses,11/12/20 0:49,6,5,3,10/3/18 16:26,12/13/18 8:04,andrey-lukyanov/Risk-Management,inactive,,
Basic Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance,Source code notebooks basic finance applications.,Courses,3/31/21 2:09,10,8,1,5/6/17 2:39,6/21/17 4:04,SeanMcOwen/FinanceAndPython.com-BasicFinance,inactive,,
ML Specialisation,https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization,Machine Learning in Finance.,Courses,4/5/21 13:37,34,32,1,1/24/19 2:55,1/3/20 21:54,Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization,active,,
Handson Python for Finance,https://github.com/PacktPublishing/Hands-on-Python-for-Finance,Hands-on Python for Finance published by Packt.,Courses,4/12/21 0:49,121,110,3,8/20/18 14:10,1/15/21 8:57,PacktPublishing/Hands-on-Python-for-Finance,active,,
Mathematical Finance,https://github.com/yadongli/nyumath2048,NYU Math-GA 2048: Scientific Computing in Finance.,Courses,1/14/21 18:01,69,63,6,1/25/15 21:10,3/25/20 4:24,yadongli/nyumath2048,active,,
Machine Learning for Trading,https://github.com/stefan-jansen/machine-learning-for-trading,"Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading.",Courses,4/12/21 16:18,3842,1225,8,5/9/18 12:33,4/10/21 22:21,stefan-jansen/machine-learning-for-trading,active,,
Algo Trading,https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading,Intro to algo trading.,Courses,3/12/21 11:02,64,25,1,10/29/17 20:34,1/22/19 6:56,JCreeks/Machine-Learning-in-Finance,inactive,,
Python for Finance,https://github.com/siaen/python_finance_course,CEU python for finance course material.,Courses,3/31/21 2:08,16,15,4,12/12/17 11:54,2/25/20 20:31,siaen/python_finance_course,active,,
Basic Derivatives,https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives,Basic forward contracts and hedging.,Courses,3/31/21 2:08,4,4,1,8/24/17 0:11,10/13/17 1:32,SeanMcOwen/FinanceAndPython.com-Derivatives,inactive,,
Open Edgar,https://github.com/LexPredict/openedgar,,Data,4/9/21 12:15,169,61,6,5/7/18 15:32,5/15/19 8:32,LexPredict/openedgar,active,,
Capital Markets Data,https://www.capitalmarketsdata.com/,,Data,,,,,,,,,,
IRS,http://social-metrics.org/sox/,,Data,,,,,,,,,,
Employee Count SEC Filings,https://github.com/healthgradient/sec_employee_information_extraction,,Data,2/27/21 3:33,10,2,1,6/26/18 23:33,8/14/18 1:31,healthgradient/sec_employee_information_extraction,inactive,,
EDGAR,https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb,,Data,1/23/21 19:22,11,10,1,6/11/18 22:51,7/10/18 18:03,TiesdeKok/UW_Python_Camp,inactive,,
SEC Parsing,https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb,,Data,2/27/21 6:34,9,6,1,6/16/18 14:30,6/16/18 17:23,healthgradient/sec-doc-info-extraction,inactive,,
Web Scraping (FirmAI),https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data,,Data,4/10/21 17:19,577,184,2,2/19/19 19:02,7/22/20 16:48,firmai/business-machine-learning,active,,
Non-financial Corporate,http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html,,Data,,,,,,,,,,
https://stooq.com,https://stooq.com,,Data,,,,,,,,,,
Financial Corporate,http://raw.rutgers.edu/Corporate%20Financial%20Data.html,,Data,,,,,,,,,,
https://fred.stlouisfed.org/,https://fred.stlouisfed.org/,,Data,,,,,,,,,,
Rating Industries,http://www.ratingshistory.info/,,Data,,,,,,,,,,
http://finance.yahoo.com/,http://finance.yahoo.com/,,Data,,,,,,,,,,
https://github.com/timestocome/StockMarketData,https://github.com/timestocome/StockMarketData,,Data,3/26/21 22:35,7,5,1,5/10/17 21:49,8/6/17 19:23,timestocome/StockMarketData,inactive,,
Advanced ML II,https://github.com/hudson-and-thames/research,More implementations of Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,,,,,,,hudson-and-thames/research,,,
Advanced ML,https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises,Exercises too Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,4/12/21 2:20,973,435,4,4/25/18 17:22,1/16/20 17:25,BlackArbsCEO/Adv_Fin_ML_Exercises,active,,
awesome-deep-trading,https://github.com/cbailes/awesome-deep-trading,curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes,Deep Learning And Reinforcement Learning,4/11/21 9:02,551,140,1,11/26/18 3:23,1/1/21 9:41,cbailes/awesome-deep-trading,active,4,3/31/21 8:00
Deep Learning IV,https://github.com/achillesrasquinha/bulbea,Bulbea: Deep Learning based Python Library.,Deep Learning And Reinforcement Learning,4/9/21 20:38,1467,416,1,3/9/17 6:11,3/19/17 7:42,achillesrasquinha/bulbea,inactive,5,
AI Trading,https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md,AI to predict stock market movements.,Deep Learning And Reinforcement Learning,4/12/21 15:42,2876,1384,1,1/9/19 8:02,2/11/19 16:32,borisbanushev/stockpredictionai,inactive,5,
ARIMA-LTSM Hybrid,https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid,Hybrid model to predict future price correlation coefficients of two assets.,Deep Learning And Reinforcement Learning,4/11/21 4:12,222,86,1,8/5/18 2:13,10/1/18 11:25,imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict,inactive,3,
trading-rl,https://github.com/Kostis-S-Z/trading-rl,Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained,Deep Learning And Reinforcement Learning,4/10/21 4:59,180,38,2,4/22/19 10:03,9/28/20 9:07,Kostis-S-Z/trading-rl,active,3,3/31/21 8:00
Deep Learning III,https://github.com/Rachnog/Deep-Trading,Algorithmic trading with deep learning experiments.,Deep Learning And Reinforcement Learning,4/9/21 10:39,1266,675,1,6/18/16 18:23,8/7/18 15:24,Rachnog/Deep-Trading,inactive,5,
Stock-Prediction-Models,https://github.com/huseinzol05/Stock-Prediction-Models,very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert)),Deep Learning And Reinforcement Learning,4/12/21 13:54,3655,1542,2,12/18/17 10:49,1/5/21 10:31,huseinzol05/Stock-Prediction-Models,active,5,3/31/21 8:00
RLTrader,https://github.com/notadamking/RLTrader,predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc.,Deep Learning And Reinforcement Learning,4/12/21 2:50,1312,451,15,4/27/19 18:35,10/17/19 16:25,notadamking/RLTrader,active,5,3/31/21 8:00
Neural Network,https://github.com/VivekPa/IntroNeuralNetworks,Neural networks to predict stock prices.,Deep Learning And Reinforcement Learning,4/3/21 11:59,489,176,2,9/10/18 6:34,11/21/18 7:39,VivekPa/IntroNeuralNetworks,inactive,4,
LTSM Recurrent,https://github.com/VivekPa/AIAlpha,OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.,Deep Learning And Reinforcement Learning,4/12/21 2:39,1207,370,2,10/7/18 3:58,8/3/19 9:00,VivekPa/AIAlpha,active,4,
Deep Learning II,https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks,Tensorflow Regression.,Deep Learning And Reinforcement Learning,4/10/21 6:06,175,67,1,7/12/16 12:56,2/16/18 2:43,LiamConnell/deep-algotrading,inactive,3,
trading-bot,https://github.com/pskrunner14/trading-bot,Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python ,Deep Learning And Reinforcement Learning,4/11/21 5:10,292,143,1,8/13/18 10:44,1/23/20 4:41,pskrunner14/trading-bot,active,3,3/31/21 8:00
LTSM GRU,https://github.com/RajatHanda/Finance-Forecasting,Stock Market Forecasting using LSTM\GRU.,Deep Learning And Reinforcement Learning,3/29/21 23:59,11,6,1,5/13/18 2:39,2/25/19 0:26,RajatHanda/Finance-Forecasting,inactive,3,
DeepLearningInFinance,https://github.com/sonaam1234/DeepLearningInFinance,Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. ,Deep Learning And Reinforcement Learning,3/8/21 13:09,266,145,1,8/21/17 16:00,8/21/17 17:23,sonaam1234/DeepLearningInFinance,inactive,3,3/31/21 8:00
crypto-rl,https://github.com/sadighian/crypto-rl,Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process),Deep Learning And Reinforcement Learning,4/12/21 10:24,347,111,1,6/21/18 1:06,11/5/20 11:08,sadighian/crypto-rl,active,3,3/31/21 8:00
Deep-Reinforcement-Stock-Trading,https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading,inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats,Deep Learning And Reinforcement Learning,4/3/21 22:50,141,42,2,5/19/19 22:20,9/27/20 19:22,Albert-Z-Guo/Deep-Reinforcement-Stock-Trading,active,3,3/31/21 8:00
Advanced-Deep-Trading,https://github.com/Rachnog/Advanced-Deep-Trading,"notebooks containing experiments based on Lopez de Prado book ""Advances in financial machine learning"". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. ",Deep Learning And Reinforcement Learning,3/30/21 7:29,319,158,2,2/16/19 21:18,11/29/20 20:12,Rachnog/Advanced-Deep-Trading,active,3,3/31/21 8:00
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble.,Deep Learning And Reinforcement Learning,4/12/21 16:24,560,249,6,7/26/20 13:12,1/21/21 18:11,AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,active,4,3/31/21 8:00
AutomatedStockTrading-DeepQ-Learning,https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning,cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report,Deep Learning And Reinforcement Learning,3/24/21 1:11,134,51,2,2/23/19 12:01,2/25/20 18:16,sachink2010/AutomatedStockTrading-DeepQ-Learning,active,3,3/31/21 8:00
deep-RL-trading,https://github.com/golsun/deep-RL-trading,trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916),Deep Learning And Reinforcement Learning,4/10/21 7:09,235,108,1,2/25/18 17:41,12/1/20 22:06,golsun/deep-RL-trading,active,3,3/31/21 8:00
FinRL-Library,https://github.com/AI4Finance-LLC/FinRL-Library,started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading,Deep Learning And Reinforcement Learning,4/12/21 12:45,1857,447,22,7/26/20 13:18,4/11/21 22:02,AI4Finance-LLC/FinRL-Library,active,5,3/31/21 8:00
Deep Learning,https://github.com/keon/deepstock,Technical experimentations to beat the stock market using deep learning.,Deep Learning And Reinforcement Learning,3/24/21 14:45,427,154,2,12/12/16 2:15,3/4/17 8:37,keon/deepstock,inactive,4,
Personae,https://github.com/Ceruleanacg/Personae,implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing,Deep Learning And Reinforcement Learning,4/11/21 20:20,1144,330,2,3/10/18 11:22,9/2/18 17:21,Ceruleanacg/Personae,inactive,5,3/31/21 8:00
Pair Trading RL,https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading,Using deep actor-critic model to learn best strategies in pair trading.,Deep Learning And Reinforcement Learning,3/27/21 2:19,241,113,1,5/18/17 16:47,5/18/17 16:56,shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading,inactive,3,
Deep-Learning-Machine-Learning-Stock,https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock,curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade,Deep Learning And Reinforcement Learning,4/12/21 2:58,275,99,1,9/29/18 23:38,3/18/21 3:16,LastAncientOne/Deep-Learning-Machine-Learning-Stock,active,3,3/31/21 8:00
Deep-Reinforcement-Learning-in-Trading,https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading,Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman),Deep Learning And Reinforcement Learning,4/10/21 13:17,138,66,1,5/11/18 0:52,10/26/19 14:22,saeed349/Deep-Reinforcement-Learning-in-Trading,active,3,3/31/21 8:00
BitcoinForecast,https://github.com/PiSimo/BitcoinForecast,RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model ,Deep Learning And Reinforcement Learning,4/6/21 2:06,289,128,3,3/10/17 10:52,6/11/18 8:07,PiSimo/BitcoinForecast,inactive,3,3/31/21 8:00
Pair-Trading-Reinforcement-Learning,https://github.com/wai-i/Pair-Trading-Reinforcement-Learning,NEW,Deep Learning And Reinforcement Learning,4/10/21 4:53,136,56,1,6/9/19 22:50,1/3/20 15:36,wai-i/Pair-Trading-Reinforcement-Learning,active,,39:11.1
rl_trading,https://github.com/ucaiado/rl_trading,NEW,Deep Learning And Reinforcement Learning,4/8/21 15:34,207,89,1,5/29/17 22:19,8/29/17 14:54,ucaiado/rl_trading,inactive,,39:11.1
Trading-Gym,https://github.com/thedimlebowski/Trading-Gym,NEW,Deep Learning And Reinforcement Learning,4/10/21 8:00,507,147,3,6/13/17 13:14,7/10/17 8:09,thedimlebowski/Trading-Gym,inactive,,39:11.1
DQN-DDPG_Stock_Trading,https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading,merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN,Deep Learning And Reinforcement Learning,4/7/21 12:42,136,49,4,9/19/18 3:17,11/26/20 16:58,AI4Finance-LLC/DQN-DDPG_Stock_Trading,active,3,3/31/21 8:00
pairstrade-fyp-2019,https://github.com/wywongbd/pairstrade-fyp-2019,NEW,Deep Learning And Reinforcement Learning,4/4/21 23:47,110,41,2,9/7/18 7:51,5/13/20 5:06,wywongbd/pairstrade-fyp-2019,active,,39:11.1
Machine-Learning-and-Reinforcement-Learning-in-Finance,https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance,NEW,Deep Learning And Reinforcement Learning,3/30/21 9:11,175,98,1,6/26/18 4:30,9/23/18 16:50,joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance,inactive,,39:11.1
maro,https://github.com/microsoft/maro,NEW,Deep Learning And Reinforcement Learning,4/12/21 2:22,386,66,17,12/27/19 6:48,4/7/21 15:49,microsoft/maro,active,,39:11.1
TradingGym,https://github.com/cove9988/TradingGym,NEW,Deep Learning And Reinforcement Learning,3/28/21 5:37,112,39,3,11/6/17 0:50,11/15/17 23:55,cove9988/TradingGym,inactive,,39:11.1
a3c_trading,https://github.com/evgps/a3c_trading,NEW,Deep Learning And Reinforcement Learning,4/10/21 12:49,311,98,1,6/4/18 15:30,5/23/20 14:47,evgps/a3c_trading,active,,39:11.1
RLQuant,https://github.com/yuriak/RLQuant,NEW,Deep Learning And Reinforcement Learning,4/9/21 5:01,277,92,1,4/5/18 5:42,8/13/18 4:18,yuriak/RLQuant,inactive,,39:11.1
TradingGym,https://github.com/Yvictor/TradingGym,NEW,Deep Learning And Reinforcement Learning,4/11/21 20:20,841,237,2,5/1/17 13:53,2/14/18 13:58,Yvictor/TradingGym,inactive,,39:11.1
QLearning_Trading,https://github.com/ucaiado/QLearning_Trading,NEW,Deep Learning And Reinforcement Learning,4/6/21 22:09,433,168,1,8/10/16 6:02,10/15/16 2:36,ucaiado/QLearning_Trading,inactive,,39:11.1
gym-trading,https://github.com/hackthemarket/gym-trading,NEW,Deep Learning And Reinforcement Learning,4/12/21 9:06,581,195,2,12/9/16 20:46,12/24/17 15:34,hackthemarket/gym-trading,inactive,,39:11.1
RL II,https://github.com/deependersingla/deep_trader,reinforcement learning on stock market and agent tries to learn trading.,Deep Learning And Reinforcement Learning,4/11/21 20:21,1340,489,3,6/11/16 7:27,1/22/18 14:35,deependersingla/deep_trader,inactive,3,
RL,https://github.com/kh-kim/stock_market_reinforcement_learning,OpenGym with Deep Q-learning and Policy Gradient.,Deep Learning And Reinforcement Learning,4/11/21 12:27,715,298,1,10/4/16 14:42,12/23/16 7:34,kh-kim/stock_market_reinforcement_learning,inactive,2,
RL V,https://github.com/gstenger98/rl-finance,Building an Agent to Trade with Reinforcement Learning.,Deep Learning And Reinforcement Learning,4/8/21 18:57,33,8,5,1/16/19 0:43,3/19/20 20:28,gstenger98/rl-finance,active,2,
RL Trading,https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW,A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.,Deep Learning And Reinforcement Learning,,,,,,,,,4,
RL IV,https://github.com/jjakimoto/DQN,Reinforcement Learning for finance.,Deep Learning And Reinforcement Learning,4/5/21 11:42,142,55,1,10/21/16 2:47,4/7/17 8:11,jjakimoto/DQN,inactive,,
tensortrade,https://github.com/tensortrade-org/tensortrade,NEW,Deep Learning And Reinforcement Learning,4/12/21 16:05,3101,715,39,7/30/19 21:28,3/24/21 16:25,tensortrade-org/tensortrade,active,,39:11.1
RL III,https://github.com/samre12/deep-trading-agent,Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.,Deep Learning And Reinforcement Learning,4/3/21 20:48,576,203,1,9/21/17 17:05,4/13/18 16:33,samre12/deep-trading-agent,inactive,3,
Options Risk Measures,https://github.com/wanglouis49/risk_estimation,Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).,Derivatives and Hedging,10/6/20 20:37,1,2,1,4/29/16 3:51,1/16/18 1:24,wanglouis49/risk_estimation,inactive,,
Option Strategies,https://github.com/rstreppa/valuation-OptionStrategies,"Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.",Derivatives and Hedging,2/27/21 8:50,2,3,1,5/22/18 18:27,5/22/18 18:30,rstreppa/valuation-OptionStrategies,inactive,,
Black Scholes,https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb,Options pricing.,Derivatives and Hedging,10/6/20 20:36,1,2,0,12/9/17 18:50,7/9/18 9:48,irajwani/numerical_methods_python,inactive,,
Computational Derivatives,https://github.com/chenbowen184/Computational_Finance,Projects focusing on investigating simulations and computational techniques applied in finance.,Derivatives and Hedging,1/12/21 12:22,17,12,1,1/29/18 5:01,8/2/18 5:56,chen-bowen/Computational_Finance,inactive,,
Delta Hedging,https://github.com/RobinsonGarcia/delta-hedging,Advanced derivatives.,Derivatives and Hedging,2/27/21 8:48,3,2,1,3/2/18 23:53,7/17/18 23:32,RobinsonGarcia/delta-hedging,inactive,,
Derivatives Python,https://github.com/yhilpisch/dawp/tree/master/python36,Derivative analytics with Python.,Derivatives and Hedging,4/12/21 14:39,388,299,1,7/9/15 12:27,2/22/21 13:29,yhilpisch/dawp,active,,
Derman,https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb,Binomial tree for American call.,Derivatives and Hedging,10/6/20 20:37,1,3,1,5/18/18 18:08,9/21/18 19:59,rstreppa/valuation-convertibles-Goldman1994,inactive,,
Reinforcement Learning,https://github.com/FinTechies/HedgingRL,Hedging portfolios with reinforcement learning.,Derivatives and Hedging,1/20/21 8:12,16,9,1,4/21/17 10:58,8/2/17 21:41,FinTechies/HedgingRL,inactive,,
Volatility and Variance Derivatives,https://github.com/yhilpisch/lvvd/tree/master/lvvd,Volatility derivatives analytics.,Derivatives and Hedging,4/7/21 19:21,79,78,1,10/21/16 4:12,2/22/21 13:32,yhilpisch/lvvd,active,,
Options,https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D,Introduction to options.,Derivatives and Hedging,4/9/21 21:17,335,163,36,7/28/17 15:48,3/17/21 17:17,QuantConnect/Tutorials,active,,
Derivative Markets,https://github.com/broughtj/Fin6470/tree/master/Notebooks,"The economics of futures, futures, options, and swaps.",Derivatives and Hedging,4/6/21 20:49,8,8,1,2/9/16 5:30,4/6/21 20:49,broughtj/Fin6470,active,,
Hull White,https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb,"Callable Bond, Hull White.",Derivatives and Hedging,10/6/20 20:37,4,6,1,6/6/18 22:06,6/6/18 22:27,rstreppa/valuation-callables-HullWhite,inactive,,
Options,https://github.com/PHBS/2018.M1.ASP/tree/master/py,Black Scholes and Copula.,Derivatives and Hedging,,,,,,,PHBS/2018.M1.ASP,,,
Mathematical Finance,https://github.com/Auquan/Tutorials,Notebooks for math and financial tutorials.,Extended Research,4/8/21 19:37,664,425,9,1/21/17 11:24,8/1/20 17:03,Auquan/Tutorials,active,,
Economic Foundations,https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations,Basic economic models.,Extended Research,10/6/20 21:01,2,3,1,5/25/17 2:27,6/30/17 3:53,SeanMcOwen/FinanceAndPython.com-EconomicFoundations,inactive,,
Financial Economics,https://github.com/rsvp/fecon235/tree/master/nb,Financial Economics Models.,Extended Research,4/10/21 17:02,713,275,2,11/9/14 4:49,12/3/18 16:30,rsvp/fecon235,inactive,,
Finance Graph Theory,https://github.com/AvijitGhosh82/Finance_Graph_Theory,Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.,Extended Research,3/28/21 2:22,17,7,3,8/2/18 2:48,3/16/19 18:39,evijit/Finance_Graph_Theory,inactive,,
Market Crash Prediction,https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb,Predicting market crashes using an LPPL model.,Extended Research,10/6/20 21:01,1,3,1,1/24/19 13:37,2/13/19 16:48,sarachmax/MarketCrashes_Prediction,inactive,,
Life-cycle,https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb,Company life cycle.,Extended Research,12/21/20 14:42,3,3,1,1/19/19 18:16,2/18/19 16:57,atulram/Finance-and-Stocks,inactive,,
Behavioural Economics,https://github.com/pcmichaud/notebooks,Behavioural Economics and Finance Python Notebooks.,Extended Research,2/3/21 7:22,9,4,1,12/20/18 0:21,3/26/19 11:51,pcmichaud/notebooks,inactive,,
Applied Corporate Finance,https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance,Studies the empirical behaviours in stock market.,Extended Research,2/19/21 13:40,8,9,1,1/29/18 5:14,7/19/18 6:25,chen-bowen/Data_Science_in_Applied_Corporate_Finance,inactive,,
HFT,https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy,High frequency trading.,Extended Research,4/11/21 23:36,748,333,1,7/21/16 5:14,2/14/17 16:47,rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy,inactive,,
Corporate Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance,Basic corporate finance.,Extended Research,1/16/21 19:01,9,4,1,9/9/17 3:35,9/9/17 23:04,SeanMcOwen/FinanceAndPython.com-CorporateFinance,inactive,,
M&A,https://github.com/atulram/Finance-and-Stocks,Mergers and Acquisitions.,Extended Research,12/21/20 14:42,3,3,1,1/19/19 18:16,2/18/19 16:57,atulram/Finance-and-Stocks,inactive,,
Backtests,https://github.com/AlgoTraders/stock-analysis-engine,Trading data and algorithms.,Extended Research,4/12/21 2:28,620,165,3,9/16/18 20:00,9/5/20 13:01,AlgoTraders/stock-analysis-engine,active,,
Bayesian Finance I,https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb,Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs.,Extended Research,11/28/20 3:02,25,6,0,1/4/19 12:30,2/18/19 9:55,AlexIoannides/pymc-stochastic-process,inactive,,
Computational Finance,https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance,Applied Computational Economics and Finance.,Extended Research,3/7/21 17:47,12,13,1,8/27/17 3:46,8/26/17 4:26,lnsongxf/Applied_Computational_Economics_and_Finance,inactive,,
Commodity,https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb,Commodity influence over Brazilian stocks.,Extended Research,,,,,,,felipessalvatore/fin2vec,,,
High Frequency,https://github.com/cswaney/prickle,A Python toolkit for high-frequency trade research.,Extended Research,3/22/21 2:19,24,17,2,7/6/16 20:32,6/9/18 10:53,cswaney/prickle,inactive,,
Currency PCA,https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb,Forex spots PCA.,Extended Research,10/26/20 0:55,3,1,1,3/12/19 21:11,3/12/19 22:09,shanemulqueen/python-finance-pca,inactive,,
Liquidity and Momentum,https://github.com/mrefermat/quant_finance,Various factors and portfolio constructions.,Extended Research,3/30/21 0:09,31,15,1,8/11/18 22:59,11/12/19 4:49,mrefermat/quant_finance,active,,
Bayesian Finance,https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb,Notebook PyMC3 implementation.,Extended Research,4/10/21 19:50,233,55,1,8/28/18 14:45,8/6/20 22:03,marketneutral/alphatools,active,,
NLP Finance Papers,https://github.com/chenbowen184/Research_Documents_Curation_with_NLP,Curating quantitative finance papers using machine learning.,Extended Research,2/27/21 6:33,8,9,1,10/11/18 20:32,12/24/18 23:27,chen-bowen/Research_Documents_Curation_with_NLP,inactive,,
Deep Portfolio,https://github.com/DLColumbia/DL_forFinance,Deep learning for finance Predict volume of bonds.,Extended Research,1/12/21 11:48,27,19,2,5/8/18 19:34,5/9/18 15:39,DLColumbia/DL_forFinance,inactive,,
Real Estate Property Fraud,https://github.com/aviroop1/Real_Estate_Property_Fraud,Unsupervised fraud detection model that can identify likely candidates of fraud.,Extended Research,,,,,,,aviroop1/Real_Estate_Property_Fraud,,,
Critical Transitions,https://github.com/ryanholbrook/critical-transitions,Detecting critical transitions in financial networks with topological data analysis.,Extended Research,1/30/21 11:50,10,3,1,1/22/19 10:59,3/12/19 18:35,ryanholbrook/critical-transitions,inactive,,
Simulation,https://github.com/chenbowen184/Computational_Finance,Investigating simulations as part of computational finance.,Extended Research,1/12/21 12:22,17,12,1,1/29/18 5:01,8/2/18 5:56,chen-bowen/Computational_Finance,inactive,,
Risk and Return,https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials,Riskiness of portfolios and assets.,Factor and Risk Analysis,4/6/21 17:03,140,62,2,9/12/17 13:35,8/6/20 12:35,PyDataBlog/Python-for-Data-Science,active,,
Stock-Prediction,https://github.com/Ronak-59/Stock-Prediction,NEW,Factor and Risk Analysis,3/26/21 8:37,129,64,2,3/18/18 4:54,2/28/20 11:43,Ronak-59/Stock-Prediction,active,,37:06.3
Quant Finance,https://github.com/mrefermat/quant_finance,General quant repository.,Factor and Risk Analysis,3/30/21 0:09,31,15,1,8/11/18 22:59,11/12/19 4:49,mrefermat/quant_finance,active,,
CAPM,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb,Expected returns using CAPM.,Factor and Risk Analysis,3/1/21 13:53,31,18,1,5/10/16 11:03,5/17/16 3:44,RJT1990/Active-Portfolio-Management-Notes,inactive,,
Various Risk Measures,https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb,Risk measures and factors for alternative and responsible investments.,Factor and Risk Analysis,11/4/20 7:04,4,5,1,8/7/17 14:44,8/8/17 22:52,Jorgencr/Alternative-and-Responsible-Investments,inactive,,
Risk Basic,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb,Active portfolio risk management .,Factor and Risk Analysis,3/1/21 13:53,31,18,1,5/10/16 11:03,5/17/16 3:44,RJT1990/Active-Portfolio-Management-Notes,inactive,,
VaR,https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb,Value-at-risk calculations.,Factor and Risk Analysis,3/31/21 2:06,10,9,1,11/15/16 19:24,1/14/17 21:19,willb/var-notebook,inactive,,
Factor Analysis,https://github.com/alpha-miner/alpha-mind/tree/master/notebooks,Factor strategy notebooks.,Factor and Risk Analysis,4/8/21 19:02,172,60,3,5/1/17 7:36,4/7/21 15:25,alpha-miner/alpha-mind,active,,
Convex Optimisation,https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb,Convex Optimization for Finance.,Factor and Risk Analysis,4/8/21 19:02,18,10,1,6/26/18 20:36,10/22/19 21:56,ssanderson/convex-optimization-for-finance,active,,
Python for Finance,https://github.com/yhilpisch/py4fi/tree/master/jupyter36,Various financial notebooks.,Factor and Risk Analysis,4/9/21 8:12,1298,794,1,12/15/14 11:23,7/10/18 6:38,yhilpisch/py4fi,inactive,,
AlphaTrading,https://github.com/jerryxyx/AlphaTrading,NEW,Factor and Risk Analysis,4/10/21 6:34,149,74,1,5/18/18 22:09,8/7/18 18:05,jerryxyx/AlphaTrading,inactive,,37:06.3
Performance Analysis,https://github.com/quantopian/alphalens,Performance analysis of predictive (alpha) stock factors.,Factor and Risk Analysis,4/10/21 12:58,1847,700,17,6/3/16 21:49,4/27/20 18:40,quantopian/alphalens,active,,
Pyfolio,https://github.com/quantopian/pyfolio,Portfolio and risk analytics in Python.,Factor and Risk Analysis,4/12/21 11:55,3673,1157,42,6/1/15 15:31,2/28/20 17:30,quantopian/pyfolio,active,,
VaR GaN,https://github.com/hamaadshah/market_risk_gan_keras,Estimate Value-at-Risk for market risk management using Keras and TensorFlow.,Factor and Risk Analysis,3/20/21 21:53,41,28,1,8/6/18 16:09,11/22/20 19:02,hamaadshah/market_risk_gan_tensorflow,active,,
Factor Analysis,https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb,Factor analysis for mutual funds.,Factor and Risk Analysis,12/21/20 14:26,3,4,1,3/13/18 7:39,3/13/18 7:42,garvit-kudesia91/factor_analysis,inactive,,
Statistical Finance,https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments,Various financial experiments.,Factor and Risk Analysis,3/30/21 0:09,21,16,1,10/4/15 9:10,3/28/20 18:33,mrefermat/FinancePhD,active,,
Vasicek,https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb,Bootstrapping and interpolation.,Fixed Income,12/10/20 21:20,3,3,1,7/18/18 19:26,7/18/18 19:34,RobinsonGarcia/fixed-income,inactive,,
Corporate Bonds,https://github.com/ishank011/gs-quantify-bond-prediction,Predicting the buying and selling volume of the corporate bonds.,Fixed Income,1/3/21 21:46,7,5,1,9/27/17 19:57,9/27/17 20:00,ishank011/gs-quantify-bond-prediction,inactive,,
Binomial Tree,https://github.com/hy-lei/math-finance-exercise,Utility functions in fixed income securities.,Fixed Income,10/6/20 20:55,1,2,1,2/2/19 8:44,5/3/19 17:16,hy-lei/math-finance-toolbox,active,,
Hands-On-Machine-Learning-for-Algorithmic-Trading,https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading,repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have,Other Models,4/12/21 15:41,600,386,2,5/7/19 11:04,1/19/21 7:51,PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading,active,5,39:24.6
CryptoBot,https://github.com/AdeelMufti/CryptoBot,Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained,Other Models,3/25/21 9:17,234,94,1,1/17/17 12:44,1/17/17 12:48,AdeelMufti/CryptoBot,inactive,2,39:24.6
MathAndScienceNotes,https://github.com/melling/MathAndScienceNotes,Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/),Other Models,4/12/21 0:49,460,54,1,3/11/16 19:13,12/21/20 3:54,melling/MathAndScienceNotes,active,,39:24.6
fin-ml,https://github.com/tatsath/fin-ml,NEW,Other Models,4/11/21 3:29,116,66,2,5/10/20 0:25,1/23/21 17:15,tatsath/fin-ml,active,,39:24.6
Trend Following,http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html,A futures trend following portfolio investment strategy.,Other Models,,,,,,,,,,
Short-Term Movement Cues,https://github.com/anfederico/Clairvoyant,Identify social/historical cues for short term stock movement.,Other Models,4/12/21 13:11,2166,678,1,9/12/16 18:38,8/29/18 20:27,anfederico/clairvoyant,inactive,,
Mixture Models II,https://github.com/BlackArbsCEO/mixture_model_trading_public,Mixture models and stock trading.,Other Models,3/12/21 13:21,166,73,1,12/11/17 17:05,5/13/20 23:50,BlackArbsCEO/mixture_model_trading_public,active,,
Fundamental LT Forecasts,https://github.com/Hvass-Labs/FinanceOps,Research in investment finance for long term forecasts.,Other Models,4/5/21 23:36,383,127,1,7/22/18 8:14,2/17/21 14:39,Hvass-Labs/FinanceOps,active,,
Scikit-learn Stock Prediction,https://github.com/robertmartin8/MachineLearningStocks,Using python and scikit-learn to make stock predictions.,Other Models,4/11/21 10:00,931,347,2,2/12/17 4:50,2/4/21 3:48,robertmartin8/MachineLearningStocks,active,,
Speculator,https://github.com/amicks/Speculator,NEW,Other Models,3/15/21 16:27,101,31,2,9/3/17 17:43,9/12/18 18:58,amicks/Speculator,inactive,,39:24.6
Machine-Learning-and-AI-in-Trading,https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading,NEW,Other Models,4/8/21 11:31,261,101,1,8/30/17 6:14,10/29/19 8:14,PyPatel/Machine-Learning-and-AI-in-Trading,active,,39:24.6
Mixture Models I,https://github.com/BlackArbsCEO/Mixture_Models,Mixture models to predict market bottoms.,Other Models,3/2/21 19:44,31,31,1,3/20/17 18:54,4/25/17 23:35,BlackArbsCEO/Mixture_Models,inactive,,
stock-trading-ml,https://github.com/yacoubb/stock-trading-ml,NEW,Other Models,4/11/21 14:46,340,186,1,10/10/19 9:44,10/12/19 11:38,yacoubb/stock-trading-ml,active,,39:24.6
Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,NEW,Other Models,4/8/21 20:01,279,126,4,11/15/19 8:51,1/21/21 7:56,PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,active,,39:24.6
mosquito,https://github.com/miro-ka/mosquito,NEW,Other Models,4/12/21 9:44,220,44,2,6/18/17 19:57,3/14/21 22:22,miro-ka/mosquito,active,,39:24.6
Machine-Learning-for-Finance,https://github.com/PacktPublishing/Machine-Learning-for-Finance,NEW,Other Models,4/8/21 16:54,180,122,4,3/15/18 6:28,1/14/21 15:58,PacktPublishing/Machine-Learning-for-Finance,active,,39:24.6
ML_Finance_Codes,https://github.com/mfrdixon/ML_Finance_Codes,NEW,Other Models,4/11/21 8:30,250,104,3,9/27/19 16:13,6/13/20 21:20,mfrdixon/ML_Finance_Codes,active,,39:24.6
Machine-Learning-For-Finance,https://github.com/anthonyng2/Machine-Learning-For-Finance,NEW,Other Models,4/1/21 20:11,205,119,1,7/11/17 9:09,2/21/18 5:36,anthonyng2/Machine-Learning-For-Finance,inactive,,39:24.6
Stock.Indicators,https://github.com/DaveSkender/Stock.Indicators,NEW,Other Models,4/12/21 10:47,175,64,9,12/29/19 5:18,4/11/21 19:17,DaveSkender/Stock.Indicators,active,,39:24.6
AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,NEW,Other Models,4/4/21 20:02,576,130,3,2/14/16 0:47,2/8/21 21:35,ScottfreeLLC/AlphaPy,active,,39:24.6
mlfinlab,https://github.com/hudson-and-thames/mlfinlab,NEW,Other Models,4/12/21 10:51,2295,709,3,2/13/19 16:57,4/12/21 10:50,hudson-and-thames/mlfinlab,active,,39:24.6
Awesome-Quant-Machine-Learning-Trading,https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading,NEW,Other Models,4/10/21 13:38,1005,319,3,11/5/18 21:09,10/8/20 16:48,grananqvist/Awesome-Quant-Machine-Learning-Trading,active,,39:24.6
botflow,https://github.com/kkyon/botflow,NEW,Other Models,3/31/21 10:56,1165,102,8,8/20/18 3:13,5/23/19 14:40,kkyon/botflow,active,,39:24.6
surpriver,https://github.com/tradytics/surpriver,NEW,Other Models,4/12/21 12:27,1189,221,6,8/30/20 7:56,9/21/20 4:32,tradytics/surpriver,active,,39:24.6
finance_ml,https://github.com/jjakimoto/finance_ml,NEW,Other Models,4/8/21 15:28,282,117,1,6/29/18 21:21,2/18/19 12:34,jjakimoto/finance_ml,inactive,,39:24.6
awesome-ai-in-finance,https://github.com/georgezouq/awesome-ai-in-finance,NEW,Other Models,4/11/21 7:43,941,162,8,8/29/18 2:07,11/27/20 9:43,georgezouq/awesome-ai-in-finance,active,,39:24.6
Pattern-Recognition-for-Forex-Trading,https://github.com/PythonProgramming/Pattern-Recognition-for-Forex-Trading,NEW,Other Models,4/5/21 3:23,173,91,1,3/26/15 2:22,3/26/15 2:33,PythonProgramming/Pattern-Recognition-for-Forex-Trading,inactive,,39:24.6
Microservices-Based-Algorithmic-Trading-System,https://github.com/saeed349/Microservices-Based-Algorithmic-Trading-System,NEW,Other Models,4/10/21 12:59,104,56,0,1/6/20 0:21,3/31/20 13:02,saeed349/Microservices-Based-Algorithmic-Trading-System,active,,39:24.6
Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,NEW,Other Models,4/11/21 6:02,172,94,5,12/6/18 11:35,1/18/21 6:40,PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,active,,39:24.6
Machine Learning in Asset Management,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952,,Personal Papers,,,,,,,,,,
Financial Event Prediction using Machine Learning,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555,,Personal Papers,,,,,,,,,,
Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization,https://jfds.pm-research.com/content/2/2/17,,Personal Papers,,,,,,,,,,
Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies,https://jfds.pm-research.com/content/2/1/10,,Personal Papers,,,,,,,,,,
Online Portfolio Selection,https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb,****Comparing OLPS algorithms on a diversified set of ETFs.,Portfolio Selection and Optimisation,,,,,,,,,,
node-finance,https://github.com/albertosantini/node-finance,NEW,Portfolio Selection and Optimisation,4/5/21 8:01,101,26,3,9/17/11 17:49,4/5/21 8:01,albertosantini/node-finance,active,,37:19.5
Riskfolio-Lib,https://github.com/dcajasn/Riskfolio-Lib,NEW,Portfolio Selection and Optimisation,4/12/21 12:25,371,62,1,3/2/20 19:49,4/1/21 3:50,dcajasn/Riskfolio-Lib,active,,37:19.5
OLMAR Algorithm,https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb,Relative importance of each component of the OLMAR algorithm.,Portfolio Selection and Optimisation,4/8/21 19:07,7,4,1,7/26/16 16:20,12/30/16 11:40,charlessutton/OLMAR,inactive,,
Reinforcement Learning,https://github.com/filangel/qtrader,Reinforcement Learning for Portfolio Management.,Portfolio Selection and Optimisation,3/29/21 3:47,364,150,1,10/7/17 9:14,6/26/18 9:22,filangelos/qtrader,inactive,,
DeepDow,https://github.com/jankrepl/deepdow,Portfolio optimization with deep learning.,Portfolio Selection and Optimisation,4/7/21 6:57,311,58,2,2/2/20 8:46,2/16/21 18:50,jankrepl/deepdow,active,,
Distribution Characteristic Optimisation,https://github.com/VivekPa/OptimalPortfolio,Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.,Portfolio Selection and Optimisation,4/12/21 13:10,232,82,3,11/16/18 12:20,7/4/19 1:41,VivekPa/OptimalPortfolio,active,,
401K Portfolio Optimisation,https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb,Portfolio analyses and optimisation for 401K.,Portfolio Selection and Optimisation,12/25/20 9:39,14,5,1,8/1/18 19:48,9/5/19 11:18,otosman/Python-for-Finance,active,,
Modern Portfolio Theory,https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb,Universal portfolios; modern portfolio theory.,Portfolio Selection and Optimisation,,,,,,,,,,
Deep Portfolio Theory,https://github.com/tcloaa/Deep-Portfolio-Theory,Autoencoder framework for portfolio selection.,Portfolio Selection and Optimisation,4/6/21 11:47,105,57,1,2/10/17 9:03,3/8/18 16:47,tcloaa/Deep-Portfolio-Theory,inactive,,
PyPortfolioOpt,https://github.com/robertmartin8/PyPortfolioOpt,"Financial portfolio optimisation, including classical efficient frontier and advanced methods.",Portfolio Selection and Optimisation,4/12/21 11:54,1895,479,16,5/29/18 13:30,2/25/21 13:01,robertmartin8/PyPortfolioOpt,active,,
riskparity.py,https://github.com/dppalomar/riskparity.py,NEW,Portfolio Selection and Optimisation,4/11/21 9:40,124,31,2,7/13/19 21:30,1/30/21 1:53,dppalomar/riskparity.py,active,,37:19.5
Policy Gradient Portfolio,https://github.com/ZhengyaoJiang/PGPortfolio,A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.,Portfolio Selection and Optimisation,4/9/21 10:41,1281,629,6,11/12/17 16:08,5/9/19 9:50,ZhengyaoJiang/PGPortfolio,active,,
Efficient Frontier,https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb,Modern Portfolio Theory.,Portfolio Selection and Optimisation,3/30/21 0:01,104,57,1,2/17/18 8:19,2/27/18 13:16,tthustla/efficient_frontier,inactive,,
Financial Statement Sentiment,https://github.com/MAydogdu/TextualAnalysis,Extracting sentiment from financial statements using neural networks.,Textual,3/31/21 2:10,8,7,1,6/4/18 20:54,6/4/18 20:56,MAydogdu/TextualAnalysis,inactive,,
NLP Event,https://github.com/yuriak/DLQuant,Applying Deep Learning and NLP in Quantitative Trading.,Textual,4/1/21 2:16,70,31,1,7/2/18 23:50,1/31/19 14:08,yuriak/DLQuant,inactive,,
Financial Sentiment Analysis,https://github.com/EricHe98/Financial-Statements-Text-Analysis,"Sentiment, distance and proportion analysis for trading signals.",Textual,3/31/21 23:48,48,27,1,6/23/17 0:05,1/26/19 3:35,EricHe98/Financial-Statements-Text-Analysis,inactive,,
NLP,https://github.com/toamitesh/NLPinFinance,This project assembles a lot of NLP operations needed for finance domain.,Textual,,,,,,,toamitesh/NLPinFinance,,,
Earning call transcripts,https://github.com/lin882/WebAnalyticsProject,Correlation between mutual fund investment decision and earning call transcripts.,Textual,12/17/20 8:24,3,3,1,12/30/17 8:56,1/11/18 2:11,lin882/WebAnalyticsProject,inactive,,
Buzzwords,https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds,Return performance and mutual fund selection.,Textual,10/6/20 18:54,1,4,1,2/4/18 21:51,2/4/18 21:57,swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds,inactive,,
Accounting Anomalies,https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb,Using deep-learning frameworks to identify accounting anomalies.,Textual,4/12/21 7:47,110,51,2,5/24/17 12:36,8/7/19 21:47,GitiHubi/deepAI,active,,
Extensive NLP,https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb,Comprehensive NLP techniques for accounting research.,Textual,3/21/21 7:39,73,42,1,10/25/17 7:10,6/5/20 3:28,TiesdeKok/Python_NLP_Tutorial,active,,
Fund classification,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Fund classification using text mining and NLP.,Textual,3/31/21 2:12,4,2,1,4/16/18 22:18,6/7/18 22:01,frechfrechfrech/Mutual-Fund-Market-Clusters,inactive,,
Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Project to cluster industries according to financial attributes.,Unsupervised,10/6/20 18:51,4,5,1,7/21/17 2:12,7/23/17 2:53,SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,inactive,,
Pairs Trading,https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb,Finding pairs with cluster analysis.,Unsupervised,4/4/21 17:55,79,36,0,9/5/17 19:19,9/27/17 20:42,marketneutral/pairs-trading-with-ML,inactive,,
PCA Pairs Trading,https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading,"PCA, Factor Returns, and trading strategies.",Unsupervised,,,,,,,joelQF/quant-finance,,,
Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Clustering of industries.,Unsupervised,10/6/20 18:51,4,5,1,7/21/17 2:12,7/23/17 2:53,SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,inactive,,
Fund Clusters,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Data exploration of fund clusters.,Unsupervised,3/31/21 2:12,4,2,1,4/16/18 22:18,6/7/18 22:01,frechfrechfrech/Mutual-Fund-Market-Clusters,inactive,,
VRA Stock Embedding,https://github.com/ml-hongkong/stock2vec,Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.,Unsupervised,10/20/20 11:05,32,12,1,6/21/17 4:47,6/21/17 4:51,ml-hongkong/stock2vec,inactive,,
name,url,comment,category,last_update,star_count,fork_count,contributors_count,created_at,last_commit,repo_path,repo_status,rating,finml_added_date
Venture Capital NN,https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring,Cox-PH neural network predictions for VC/innovations finance research.,Alternative Finance,,,,,,,tr7200/National-Culture-and-Venture-Capital-Monitoring,,,
Private Equity,https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb,Valuation models.,Alternative Finance,11/26/20 3:34,8.0,6.0,2.0,1/27/16 21:13,3/14/16 20:03,TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity,inactive,,
VC OLS,https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb,VC regression.,Alternative Finance,10/6/20 20:56,2.0,1.0,1.0,3/29/18 23:31,3/29/18 23:33,fionawhitefield/venture-capital-ols,inactive,,
Watch Valuation,https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb,Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued.,Alternative Finance,1/14/21 22:41,4.0,2.0,1.0,2/8/17 18:39,4/27/17 22:55,alporter08/Luxury-Watch-Valuation,inactive,,
Art Valuation,https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb,Art evaluation analytics.,Alternative Finance,2/26/21 12:10,9.0,5.0,1.0,12/11/14 0:25,12/12/14 21:25,ahmedhosny/theGreenCanvas,inactive,,
Blockchain,https://github.com/nud3l/dInvest,Repository for distributed autonomous investment banking.,Alternative Finance,2/6/21 7:38,12.0,7.0,2.0,9/5/16 19:12,4/24/17 10:48,nud3l/dInvest,inactive,,
Venture Capital,https://github.com/julian-chan/etothex,Insight into a new founder to make data-driven investment decisions.,Alternative Finance,10/6/20 20:56,3.0,2.0,1.0,12/4/17 8:59,12/13/17 5:35,julian-chan/etothex,inactive,,
Kiva Crowdfunding,https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb,Exploratory data analysis.,Alternative Finance,2/19/21 13:40,5.0,1.0,1.0,2/27/18 16:46,2/13/19 0:15,CJL89/Kiva-Crowdfunding,inactive,,
Cornell University,https://www.cornell.edu/,,Colleges Centers and Departments,,,,,,,,,,
Stanford Advanced Financial Technologies,https://fintech.stanford.edu/,Stanford Advanced Financial Technologies Laboratory,Colleges Centers and Departments,,,,,,,,,,
NYU FRE,https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering,Finance and Risk Engineering (NYU Tandon),Colleges Centers and Departments,,,,,,,,,,
Oxford Man,https://www.oxford-man.ox.ac.uk/,Oxford-Man Institute of Quantitative Finance,Colleges Centers and Departments,,,,,,,,,,
NYU Courant,https://cims.nyu.edu/,"Courant Institute of Mathematical Sciences, New York University",Colleges Centers and Departments,,,,,,,,,,
Berkeley Lab CIFT,https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/,,Colleges Centers and Departments,,,,,,,,,,
Machine Learning for Trading,https://github.com/stefan-jansen/machine-learning-for-trading,"Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading.",Courses,4/12/21 16:18,3842.0,1225.0,8.0,5/9/18 12:33,4/10/21 22:21,stefan-jansen/machine-learning-for-trading,active,,
Basic Derivatives,https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives,Basic forward contracts and hedging.,Courses,3/31/21 2:08,4.0,4.0,1.0,8/24/17 0:11,10/13/17 1:32,SeanMcOwen/FinanceAndPython.com-Derivatives,inactive,,
Python for Finance,https://github.com/siaen/python_finance_course,CEU python for finance course material.,Courses,3/31/21 2:08,16.0,15.0,4.0,12/12/17 11:54,2/25/20 20:31,siaen/python_finance_course,active,,
Algo Trading,https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading,Intro to algo trading.,Courses,3/12/21 11:02,64.0,25.0,1.0,10/29/17 20:34,1/22/19 6:56,JCreeks/Machine-Learning-in-Finance,inactive,,
Mathematical Finance,https://github.com/yadongli/nyumath2048,NYU Math-GA 2048: Scientific Computing in Finance.,Courses,1/14/21 18:01,69.0,63.0,6.0,1/25/15 21:10,3/25/20 4:24,yadongli/nyumath2048,active,,
Basic Investments,https://github.com/SeanMcOwen/FinanceAndPython.com-Investments,Basic investment tools in python.,Courses,3/23/21 6:32,9.0,5.0,1.0,8/2/17 21:52,8/17/17 3:24,SeanMcOwen/FinanceAndPython.com-Investments,inactive,,
ML Specialisation,https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization,Machine Learning in Finance.,Courses,4/5/21 13:37,34.0,32.0,1.0,1/24/19 2:55,1/3/20 21:54,Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization,active,,
Basic Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance,Source code notebooks basic finance applications.,Courses,3/31/21 2:09,10.0,8.0,1.0,5/6/17 2:39,6/21/17 4:04,SeanMcOwen/FinanceAndPython.com-BasicFinance,inactive,,
Risk Management,https://github.com/andrey-lukyanov/Risk-Management,Finance risk engagement course resources.,Courses,11/12/20 0:49,6.0,5.0,3.0,10/3/18 16:26,12/13/18 8:04,andrey-lukyanov/Risk-Management,inactive,,
Handson Python for Finance,https://github.com/PacktPublishing/Hands-on-Python-for-Finance,Hands-on Python for Finance published by Packt.,Courses,4/12/21 0:49,121.0,110.0,3.0,8/20/18 14:10,1/15/21 8:57,PacktPublishing/Hands-on-Python-for-Finance,active,,
Financial Corporate,http://raw.rutgers.edu/Corporate%20Financial%20Data.html,,Data,,,,,,,,,,
https://github.com/timestocome/StockMarketData,https://github.com/timestocome/StockMarketData,,Data,3/26/21 22:35,7.0,5.0,1.0,5/10/17 21:49,8/6/17 19:23,timestocome/StockMarketData,inactive,,
http://finance.yahoo.com/,http://finance.yahoo.com/,,Data,,,,,,,,,,
Rating Industries,http://www.ratingshistory.info/,,Data,,,,,,,,,,
https://fred.stlouisfed.org/,https://fred.stlouisfed.org/,,Data,,,,,,,,,,
Non-financial Corporate,http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html,,Data,,,,,,,,,,
https://stooq.com,https://stooq.com,,Data,,,,,,,,,,
SEC Parsing,https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb,,Data,2/27/21 6:34,9.0,6.0,1.0,6/16/18 14:30,6/16/18 17:23,healthgradient/sec-doc-info-extraction,inactive,,
Web Scraping (FirmAI),https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data,,Data,4/10/21 17:19,577.0,184.0,2.0,2/19/19 19:02,7/22/20 16:48,firmai/business-machine-learning,active,,
EDGAR,https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb,,Data,1/23/21 19:22,11.0,10.0,1.0,6/11/18 22:51,7/10/18 18:03,TiesdeKok/UW_Python_Camp,inactive,,
Employee Count SEC Filings,https://github.com/healthgradient/sec_employee_information_extraction,,Data,2/27/21 3:33,10.0,2.0,1.0,6/26/18 23:33,8/14/18 1:31,healthgradient/sec_employee_information_extraction,inactive,,
IRS,http://social-metrics.org/sox/,,Data,,,,,,,,,,
Capital Markets Data,https://www.capitalmarketsdata.com/,,Data,,,,,,,,,,
Open Edgar,https://github.com/LexPredict/openedgar,,Data,4/9/21 12:15,169.0,61.0,6.0,5/7/18 15:32,5/15/19 8:32,LexPredict/openedgar,active,,
Twitter-Trends,https://github.com/Medha11/Twitter-Trends,NEW,Data Processing Techniques and Transformations,2021-02-07 09:16:53,66.0,21.0,1.0,2017-05-22 17:07:45,2017-05-23 08:06:27,Medha11/Twitter-Trends,inactive,,2021-04-13 16:12:49.160843
cointrader,https://github.com/timolson/cointrader,NEW,Data Processing Techniques and Transformations,2021-04-10 17:16:37,339.0,140.0,9.0,2014-06-01 01:14:12,2020-10-22 00:24:50,timolson/cointrader,active,,2021-04-13 16:12:49.160843
Google-Finance-Stock-Data-Analysis,https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis,NEW,Data Processing Techniques and Transformations,2020-12-20 08:39:26,70.0,10.0,1.0,2017-07-23 02:59:59,2017-07-23 03:10:35,hpnhxxwn/Google-Finance-Stock-Data-Analysis,inactive,,2021-04-13 16:12:49.160843
finserv-application-blueprint,https://github.com/mapr-demos/finserv-application-blueprint,NEW,Data Processing Techniques and Transformations,2021-01-21 00:29:14,72.0,53.0,5.0,2016-09-26 19:42:54,2021-01-20 23:07:40,mapr-demos/finserv-application-blueprint,active,,2021-04-13 16:12:49.160843
Advanced ML,https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises,Exercises too Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,4/12/21 2:20,973.0,435.0,4.0,4/25/18 17:22,1/16/20 17:25,BlackArbsCEO/Adv_Fin_ML_Exercises,active,,
Advanced ML II,https://github.com/hudson-and-thames/research,More implementations of Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,,,,,,,hudson-and-thames/research,,,
CryptoNets,https://github.com/microsoft/CryptoNets,NEW,Data Processing Techniques and Transformations,2021-04-08 01:07:55,154.0,42.0,4.0,2019-06-02 05:48:39,2019-09-12 13:03:05,microsoft/CryptoNets,active,,2021-04-13 16:12:49.160843
a3c_trading,https://github.com/evgps/a3c_trading,NEW,Deep Learning And Reinforcement Learning,4/10/21 12:49,311.0,98.0,1.0,6/4/18 15:30,5/23/20 14:47,evgps/a3c_trading,active,,39:11.1
Trading-Gym,https://github.com/thedimlebowski/Trading-Gym,NEW,Deep Learning And Reinforcement Learning,4/10/21 8:00,507.0,147.0,3.0,6/13/17 13:14,7/10/17 8:09,thedimlebowski/Trading-Gym,inactive,,39:11.1
DQN-DDPG_Stock_Trading,https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading,merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN,Deep Learning And Reinforcement Learning,4/7/21 12:42,136.0,49.0,4.0,9/19/18 3:17,11/26/20 16:58,AI4Finance-LLC/DQN-DDPG_Stock_Trading,active,3.0,3/31/21 8:00
pairstrade-fyp-2019,https://github.com/wywongbd/pairstrade-fyp-2019,NEW,Deep Learning And Reinforcement Learning,4/4/21 23:47,110.0,41.0,2.0,9/7/18 7:51,5/13/20 5:06,wywongbd/pairstrade-fyp-2019,active,,39:11.1
rl_trading,https://github.com/ucaiado/rl_trading,NEW,Deep Learning And Reinforcement Learning,4/8/21 15:34,207.0,89.0,1.0,5/29/17 22:19,8/29/17 14:54,ucaiado/rl_trading,inactive,,39:11.1
Machine-Learning-and-Reinforcement-Learning-in-Finance,https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance,NEW,Deep Learning And Reinforcement Learning,3/30/21 9:11,175.0,98.0,1.0,6/26/18 4:30,9/23/18 16:50,joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance,inactive,,39:11.1
maro,https://github.com/microsoft/maro,NEW,Deep Learning And Reinforcement Learning,4/12/21 2:22,386.0,66.0,17.0,12/27/19 6:48,4/7/21 15:49,microsoft/maro,active,,39:11.1
TradingGym,https://github.com/cove9988/TradingGym,NEW,Deep Learning And Reinforcement Learning,3/28/21 5:37,112.0,39.0,3.0,11/6/17 0:50,11/15/17 23:55,cove9988/TradingGym,inactive,,39:11.1
RLQuant,https://github.com/yuriak/RLQuant,NEW,Deep Learning And Reinforcement Learning,4/9/21 5:01,277.0,92.0,1.0,4/5/18 5:42,8/13/18 4:18,yuriak/RLQuant,inactive,,39:11.1
RL Trading,https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW,A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.,Deep Learning And Reinforcement Learning,,,,,,,,,4.0,
QLearning_Trading,https://github.com/ucaiado/QLearning_Trading,NEW,Deep Learning And Reinforcement Learning,4/6/21 22:09,433.0,168.0,1.0,8/10/16 6:02,10/15/16 2:36,ucaiado/QLearning_Trading,inactive,,39:11.1
gym-trading,https://github.com/hackthemarket/gym-trading,NEW,Deep Learning And Reinforcement Learning,4/12/21 9:06,581.0,195.0,2.0,12/9/16 20:46,12/24/17 15:34,hackthemarket/gym-trading,inactive,,39:11.1
RL II,https://github.com/deependersingla/deep_trader,reinforcement learning on stock market and agent tries to learn trading.,Deep Learning And Reinforcement Learning,4/11/21 20:21,1340.0,489.0,3.0,6/11/16 7:27,1/22/18 14:35,deependersingla/deep_trader,inactive,3.0,
RL,https://github.com/kh-kim/stock_market_reinforcement_learning,OpenGym with Deep Q-learning and Policy Gradient.,Deep Learning And Reinforcement Learning,4/11/21 12:27,715.0,298.0,1.0,10/4/16 14:42,12/23/16 7:34,kh-kim/stock_market_reinforcement_learning,inactive,2.0,
RL V,https://github.com/gstenger98/rl-finance,Building an Agent to Trade with Reinforcement Learning.,Deep Learning And Reinforcement Learning,4/8/21 18:57,33.0,8.0,5.0,1/16/19 0:43,3/19/20 20:28,gstenger98/rl-finance,active,2.0,
RL IV,https://github.com/jjakimoto/DQN,Reinforcement Learning for finance.,Deep Learning And Reinforcement Learning,4/5/21 11:42,142.0,55.0,1.0,10/21/16 2:47,4/7/17 8:11,jjakimoto/DQN,inactive,,
tensortrade,https://github.com/tensortrade-org/tensortrade,NEW,Deep Learning And Reinforcement Learning,4/12/21 16:05,3101.0,715.0,39.0,7/30/19 21:28,3/24/21 16:25,tensortrade-org/tensortrade,active,,39:11.1
RL III,https://github.com/samre12/deep-trading-agent,Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.,Deep Learning And Reinforcement Learning,4/3/21 20:48,576.0,203.0,1.0,9/21/17 17:05,4/13/18 16:33,samre12/deep-trading-agent,inactive,3.0,
Pair-Trading-Reinforcement-Learning,https://github.com/wai-i/Pair-Trading-Reinforcement-Learning,NEW,Deep Learning And Reinforcement Learning,4/10/21 4:53,136.0,56.0,1.0,6/9/19 22:50,1/3/20 15:36,wai-i/Pair-Trading-Reinforcement-Learning,active,,39:11.1
TradingGym,https://github.com/Yvictor/TradingGym,NEW,Deep Learning And Reinforcement Learning,4/11/21 20:20,841.0,237.0,2.0,5/1/17 13:53,2/14/18 13:58,Yvictor/TradingGym,inactive,,39:11.1
BitcoinForecast,https://github.com/PiSimo/BitcoinForecast,RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model ,Deep Learning And Reinforcement Learning,4/6/21 2:06,289.0,128.0,3.0,3/10/17 10:52,6/11/18 8:07,PiSimo/BitcoinForecast,inactive,3.0,3/31/21 8:00
FinRL,https://github.com/AI4Finance-LLC/FinRL,NEW,Deep Learning And Reinforcement Learning,2021-04-13 14:37:21,1865.0,451.0,22.0,2020-07-26 13:18:16,2021-04-11 22:02:16,AI4Finance-LLC/FinRL,active,,2021-04-13 16:13:03.716257
Deep-Learning-Machine-Learning-Stock,https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock,curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade,Deep Learning And Reinforcement Learning,4/12/21 2:58,275.0,99.0,1.0,9/29/18 23:38,3/18/21 3:16,LastAncientOne/Deep-Learning-Machine-Learning-Stock,active,3.0,3/31/21 8:00
awesome-deep-trading,https://github.com/cbailes/awesome-deep-trading,curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes,Deep Learning And Reinforcement Learning,4/11/21 9:02,551.0,140.0,1.0,11/26/18 3:23,1/1/21 9:41,cbailes/awesome-deep-trading,active,4.0,3/31/21 8:00
Deep Learning IV,https://github.com/achillesrasquinha/bulbea,Bulbea: Deep Learning based Python Library.,Deep Learning And Reinforcement Learning,4/9/21 20:38,1467.0,416.0,1.0,3/9/17 6:11,3/19/17 7:42,achillesrasquinha/bulbea,inactive,5.0,
AI Trading,https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md,AI to predict stock market movements.,Deep Learning And Reinforcement Learning,4/12/21 15:42,2876.0,1384.0,1.0,1/9/19 8:02,2/11/19 16:32,borisbanushev/stockpredictionai,inactive,5.0,
ARIMA-LTSM Hybrid,https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid,Hybrid model to predict future price correlation coefficients of two assets.,Deep Learning And Reinforcement Learning,4/11/21 4:12,222.0,86.0,1.0,8/5/18 2:13,10/1/18 11:25,imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict,inactive,3.0,
Deep-Reinforcement-Learning-in-Trading,https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading,Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman),Deep Learning And Reinforcement Learning,4/10/21 13:17,138.0,66.0,1.0,5/11/18 0:52,10/26/19 14:22,saeed349/Deep-Reinforcement-Learning-in-Trading,active,3.0,3/31/21 8:00
trading-rl,https://github.com/Kostis-S-Z/trading-rl,Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained,Deep Learning And Reinforcement Learning,4/10/21 4:59,180.0,38.0,2.0,4/22/19 10:03,9/28/20 9:07,Kostis-S-Z/trading-rl,active,3.0,3/31/21 8:00
Deep Learning III,https://github.com/Rachnog/Deep-Trading,Algorithmic trading with deep learning experiments.,Deep Learning And Reinforcement Learning,4/9/21 10:39,1266.0,675.0,1.0,6/18/16 18:23,8/7/18 15:24,Rachnog/Deep-Trading,inactive,5.0,
Stock-Prediction-Models,https://github.com/huseinzol05/Stock-Prediction-Models,very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert)),Deep Learning And Reinforcement Learning,4/12/21 13:54,3655.0,1542.0,2.0,12/18/17 10:49,1/5/21 10:31,huseinzol05/Stock-Prediction-Models,active,5.0,3/31/21 8:00
RLTrader,https://github.com/notadamking/RLTrader,predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc.,Deep Learning And Reinforcement Learning,4/12/21 2:50,1312.0,451.0,15.0,4/27/19 18:35,10/17/19 16:25,notadamking/RLTrader,active,5.0,3/31/21 8:00
Neural Network,https://github.com/VivekPa/IntroNeuralNetworks,Neural networks to predict stock prices.,Deep Learning And Reinforcement Learning,4/3/21 11:59,489.0,176.0,2.0,9/10/18 6:34,11/21/18 7:39,VivekPa/IntroNeuralNetworks,inactive,4.0,
LTSM Recurrent,https://github.com/VivekPa/AIAlpha,OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.,Deep Learning And Reinforcement Learning,4/12/21 2:39,1207.0,370.0,2.0,10/7/18 3:58,8/3/19 9:00,VivekPa/AIAlpha,active,4.0,
trading-bot,https://github.com/pskrunner14/trading-bot,Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python ,Deep Learning And Reinforcement Learning,4/11/21 5:10,292.0,143.0,1.0,8/13/18 10:44,1/23/20 4:41,pskrunner14/trading-bot,active,3.0,3/31/21 8:00
Deep Learning II,https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks,Tensorflow Regression.,Deep Learning And Reinforcement Learning,4/10/21 6:06,175.0,67.0,1.0,7/12/16 12:56,2/16/18 2:43,LiamConnell/deep-algotrading,inactive,3.0,
DeepLearningInFinance,https://github.com/sonaam1234/DeepLearningInFinance,Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. ,Deep Learning And Reinforcement Learning,3/8/21 13:09,266.0,145.0,1.0,8/21/17 16:00,8/21/17 17:23,sonaam1234/DeepLearningInFinance,inactive,3.0,3/31/21 8:00
crypto-rl,https://github.com/sadighian/crypto-rl,Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process),Deep Learning And Reinforcement Learning,4/12/21 10:24,347.0,111.0,1.0,6/21/18 1:06,11/5/20 11:08,sadighian/crypto-rl,active,3.0,3/31/21 8:00
Deep-Reinforcement-Stock-Trading,https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading,inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats,Deep Learning And Reinforcement Learning,4/3/21 22:50,141.0,42.0,2.0,5/19/19 22:20,9/27/20 19:22,Albert-Z-Guo/Deep-Reinforcement-Stock-Trading,active,3.0,3/31/21 8:00
Advanced-Deep-Trading,https://github.com/Rachnog/Advanced-Deep-Trading,"notebooks containing experiments based on Lopez de Prado book ""Advances in financial machine learning"". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. ",Deep Learning And Reinforcement Learning,3/30/21 7:29,319.0,158.0,2.0,2/16/19 21:18,11/29/20 20:12,Rachnog/Advanced-Deep-Trading,active,3.0,3/31/21 8:00
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble.,Deep Learning And Reinforcement Learning,4/12/21 16:24,560.0,249.0,6.0,7/26/20 13:12,1/21/21 18:11,AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,active,4.0,3/31/21 8:00
AutomatedStockTrading-DeepQ-Learning,https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning,cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report,Deep Learning And Reinforcement Learning,3/24/21 1:11,134.0,51.0,2.0,2/23/19 12:01,2/25/20 18:16,sachink2010/AutomatedStockTrading-DeepQ-Learning,active,3.0,3/31/21 8:00
deep-RL-trading,https://github.com/golsun/deep-RL-trading,trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916),Deep Learning And Reinforcement Learning,4/10/21 7:09,235.0,108.0,1.0,2/25/18 17:41,12/1/20 22:06,golsun/deep-RL-trading,active,3.0,3/31/21 8:00
FinRL-Library,https://github.com/AI4Finance-LLC/FinRL-Library,started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading,Deep Learning And Reinforcement Learning,4/12/21 12:45,1857.0,447.0,22.0,7/26/20 13:18,4/11/21 22:02,AI4Finance-LLC/FinRL-Library,active,5.0,3/31/21 8:00
Deep Learning,https://github.com/keon/deepstock,Technical experimentations to beat the stock market using deep learning.,Deep Learning And Reinforcement Learning,3/24/21 14:45,427.0,154.0,2.0,12/12/16 2:15,3/4/17 8:37,keon/deepstock,inactive,4.0,
Personae,https://github.com/Ceruleanacg/Personae,implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing,Deep Learning And Reinforcement Learning,4/11/21 20:20,1144.0,330.0,2.0,3/10/18 11:22,9/2/18 17:21,Ceruleanacg/Personae,inactive,5.0,3/31/21 8:00
Pair Trading RL,https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading,Using deep actor-critic model to learn best strategies in pair trading.,Deep Learning And Reinforcement Learning,3/27/21 2:19,241.0,113.0,1.0,5/18/17 16:47,5/18/17 16:56,shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading,inactive,3.0,
LTSM GRU,https://github.com/RajatHanda/Finance-Forecasting,Stock Market Forecasting using LSTM\GRU.,Deep Learning And Reinforcement Learning,3/29/21 23:59,11.0,6.0,1.0,5/13/18 2:39,2/25/19 0:26,RajatHanda/Finance-Forecasting,inactive,3.0,
Hull White,https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb,"Callable Bond, Hull White.",Derivatives and Hedging,10/6/20 20:37,4.0,6.0,1.0,6/6/18 22:06,6/6/18 22:27,rstreppa/valuation-callables-HullWhite,inactive,,
Options,https://github.com/PHBS/2018.M1.ASP/tree/master/py,Black Scholes and Copula.,Derivatives and Hedging,,,,,,,PHBS/2018.M1.ASP,,,
Derivative Markets,https://github.com/broughtj/Fin6470/tree/master/Notebooks,"The economics of futures, futures, options, and swaps.",Derivatives and Hedging,4/6/21 20:49,8.0,8.0,1.0,2/9/16 5:30,4/6/21 20:49,broughtj/Fin6470,active,,
Computational Derivatives,https://github.com/chenbowen184/Computational_Finance,Projects focusing on investigating simulations and computational techniques applied in finance.,Derivatives and Hedging,1/12/21 12:22,17.0,12.0,1.0,1/29/18 5:01,8/2/18 5:56,chen-bowen/Computational_Finance,inactive,,
Volatility and Variance Derivatives,https://github.com/yhilpisch/lvvd/tree/master/lvvd,Volatility derivatives analytics.,Derivatives and Hedging,4/7/21 19:21,79.0,78.0,1.0,10/21/16 4:12,2/22/21 13:32,yhilpisch/lvvd,active,,
Options,https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D,Introduction to options.,Derivatives and Hedging,4/9/21 21:17,335.0,163.0,36.0,7/28/17 15:48,3/17/21 17:17,QuantConnect/Tutorials,active,,
Option Strategies,https://github.com/rstreppa/valuation-OptionStrategies,"Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.",Derivatives and Hedging,2/27/21 8:50,2.0,3.0,1.0,5/22/18 18:27,5/22/18 18:30,rstreppa/valuation-OptionStrategies,inactive,,
Black Scholes,https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb,Options pricing.,Derivatives and Hedging,10/6/20 20:36,1.0,2.0,0.0,12/9/17 18:50,7/9/18 9:48,irajwani/numerical_methods_python,inactive,,
Options Risk Measures,https://github.com/wanglouis49/risk_estimation,Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).,Derivatives and Hedging,10/6/20 20:37,1.0,2.0,1.0,4/29/16 3:51,1/16/18 1:24,wanglouis49/risk_estimation,inactive,,
Derivatives Python,https://github.com/yhilpisch/dawp/tree/master/python36,Derivative analytics with Python.,Derivatives and Hedging,4/12/21 14:39,388.0,299.0,1.0,7/9/15 12:27,2/22/21 13:29,yhilpisch/dawp,active,,
Derman,https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb,Binomial tree for American call.,Derivatives and Hedging,10/6/20 20:37,1.0,3.0,1.0,5/18/18 18:08,9/21/18 19:59,rstreppa/valuation-convertibles-Goldman1994,inactive,,
Reinforcement Learning,https://github.com/FinTechies/HedgingRL,Hedging portfolios with reinforcement learning.,Derivatives and Hedging,1/20/21 8:12,16.0,9.0,1.0,4/21/17 10:58,8/2/17 21:41,FinTechies/HedgingRL,inactive,,
Delta Hedging,https://github.com/RobinsonGarcia/delta-hedging,Advanced derivatives.,Derivatives and Hedging,2/27/21 8:48,3.0,2.0,1.0,3/2/18 23:53,7/17/18 23:32,RobinsonGarcia/delta-hedging,inactive,,
Currency PCA,https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb,Forex spots PCA.,Extended Research,10/26/20 0:55,3.0,1.0,1.0,3/12/19 21:11,3/12/19 22:09,shanemulqueen/python-finance-pca,inactive,,
Simulation,https://github.com/chenbowen184/Computational_Finance,Investigating simulations as part of computational finance.,Extended Research,1/12/21 12:22,17.0,12.0,1.0,1/29/18 5:01,8/2/18 5:56,chen-bowen/Computational_Finance,inactive,,
Critical Transitions,https://github.com/ryanholbrook/critical-transitions,Detecting critical transitions in financial networks with topological data analysis.,Extended Research,1/30/21 11:50,10.0,3.0,1.0,1/22/19 10:59,3/12/19 18:35,ryanholbrook/critical-transitions,inactive,,
Real Estate Property Fraud,https://github.com/aviroop1/Real_Estate_Property_Fraud,Unsupervised fraud detection model that can identify likely candidates of fraud.,Extended Research,,,,,,,aviroop1/Real_Estate_Property_Fraud,,,
Deep Portfolio,https://github.com/DLColumbia/DL_forFinance,Deep learning for finance Predict volume of bonds.,Extended Research,1/12/21 11:48,27.0,19.0,2.0,5/8/18 19:34,5/9/18 15:39,DLColumbia/DL_forFinance,inactive,,
NLP Finance Papers,https://github.com/chenbowen184/Research_Documents_Curation_with_NLP,Curating quantitative finance papers using machine learning.,Extended Research,2/27/21 6:33,8.0,9.0,1.0,10/11/18 20:32,12/24/18 23:27,chen-bowen/Research_Documents_Curation_with_NLP,inactive,,
Bayesian Finance,https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb,Notebook PyMC3 implementation.,Extended Research,4/10/21 19:50,233.0,55.0,1.0,8/28/18 14:45,8/6/20 22:03,marketneutral/alphatools,active,,
Liquidity and Momentum,https://github.com/mrefermat/quant_finance,Various factors and portfolio constructions.,Extended Research,3/30/21 0:09,31.0,15.0,1.0,8/11/18 22:59,11/12/19 4:49,mrefermat/quant_finance,active,,
High Frequency,https://github.com/cswaney/prickle,A Python toolkit for high-frequency trade research.,Extended Research,3/22/21 2:19,24.0,17.0,2.0,7/6/16 20:32,6/9/18 10:53,cswaney/prickle,inactive,,
Life-cycle,https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb,Company life cycle.,Extended Research,12/21/20 14:42,3.0,3.0,1.0,1/19/19 18:16,2/18/19 16:57,atulram/Finance-and-Stocks,inactive,,
Computational Finance,https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance,Applied Computational Economics and Finance.,Extended Research,3/7/21 17:47,12.0,13.0,1.0,8/27/17 3:46,8/26/17 4:26,lnsongxf/Applied_Computational_Economics_and_Finance,inactive,,
Market Crash Prediction,https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb,Predicting market crashes using an LPPL model.,Extended Research,10/6/20 21:01,1.0,3.0,1.0,1/24/19 13:37,2/13/19 16:48,sarachmax/MarketCrashes_Prediction,inactive,,
Commodity,https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb,Commodity influence over Brazilian stocks.,Extended Research,,,,,,,felipessalvatore/fin2vec,,,
Finance Graph Theory,https://github.com/AvijitGhosh82/Finance_Graph_Theory,Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.,Extended Research,3/28/21 2:22,17.0,7.0,3.0,8/2/18 2:48,3/16/19 18:39,evijit/Finance_Graph_Theory,inactive,,
Financial Economics,https://github.com/rsvp/fecon235/tree/master/nb,Financial Economics Models.,Extended Research,4/10/21 17:02,713.0,275.0,2.0,11/9/14 4:49,12/3/18 16:30,rsvp/fecon235,inactive,,
Economic Foundations,https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations,Basic economic models.,Extended Research,10/6/20 21:01,2.0,3.0,1.0,5/25/17 2:27,6/30/17 3:53,SeanMcOwen/FinanceAndPython.com-EconomicFoundations,inactive,,
Behavioural Economics,https://github.com/pcmichaud/notebooks,Behavioural Economics and Finance Python Notebooks.,Extended Research,2/3/21 7:22,9.0,4.0,1.0,12/20/18 0:21,3/26/19 11:51,pcmichaud/notebooks,inactive,,
Mathematical Finance,https://github.com/Auquan/Tutorials,Notebooks for math and financial tutorials.,Extended Research,4/8/21 19:37,664.0,425.0,9.0,1/21/17 11:24,8/1/20 17:03,Auquan/Tutorials,active,,
HFT,https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy,High frequency trading.,Extended Research,4/11/21 23:36,748.0,333.0,1.0,7/21/16 5:14,2/14/17 16:47,rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy,inactive,,
Corporate Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance,Basic corporate finance.,Extended Research,1/16/21 19:01,9.0,4.0,1.0,9/9/17 3:35,9/9/17 23:04,SeanMcOwen/FinanceAndPython.com-CorporateFinance,inactive,,
M&A,https://github.com/atulram/Finance-and-Stocks,Mergers and Acquisitions.,Extended Research,12/21/20 14:42,3.0,3.0,1.0,1/19/19 18:16,2/18/19 16:57,atulram/Finance-and-Stocks,inactive,,
Backtests,https://github.com/AlgoTraders/stock-analysis-engine,Trading data and algorithms.,Extended Research,4/12/21 2:28,620.0,165.0,3.0,9/16/18 20:00,9/5/20 13:01,AlgoTraders/stock-analysis-engine,active,,
Bayesian Finance I,https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb,Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs.,Extended Research,11/28/20 3:02,25.0,6.0,0.0,1/4/19 12:30,2/18/19 9:55,AlexIoannides/pymc-stochastic-process,inactive,,
Applied Corporate Finance,https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance,Studies the empirical behaviours in stock market.,Extended Research,2/19/21 13:40,8.0,9.0,1.0,1/29/18 5:14,7/19/18 6:25,chen-bowen/Data_Science_in_Applied_Corporate_Finance,inactive,,
Pyfolio,https://github.com/quantopian/pyfolio,Portfolio and risk analytics in Python.,Factor and Risk Analysis,4/12/21 11:55,3673.0,1157.0,42.0,6/1/15 15:31,2/28/20 17:30,quantopian/pyfolio,active,,
Statistical Finance,https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments,Various financial experiments.,Factor and Risk Analysis,3/30/21 0:09,21.0,16.0,1.0,10/4/15 9:10,3/28/20 18:33,mrefermat/FinancePhD,active,,
VaR GaN,https://github.com/hamaadshah/market_risk_gan_keras,Estimate Value-at-Risk for market risk management using Keras and TensorFlow.,Factor and Risk Analysis,3/20/21 21:53,41.0,28.0,1.0,8/6/18 16:09,11/22/20 19:02,hamaadshah/market_risk_gan_tensorflow,active,,
Performance Analysis,https://github.com/quantopian/alphalens,Performance analysis of predictive (alpha) stock factors.,Factor and Risk Analysis,4/10/21 12:58,1847.0,700.0,17.0,6/3/16 21:49,4/27/20 18:40,quantopian/alphalens,active,,
Factor Analysis,https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb,Factor analysis for mutual funds.,Factor and Risk Analysis,12/21/20 14:26,3.0,4.0,1.0,3/13/18 7:39,3/13/18 7:42,garvit-kudesia91/factor_analysis,inactive,,
Python for Finance,https://github.com/yhilpisch/py4fi/tree/master/jupyter36,Various financial notebooks.,Factor and Risk Analysis,4/9/21 8:12,1298.0,794.0,1.0,12/15/14 11:23,7/10/18 6:38,yhilpisch/py4fi,inactive,,
Various Risk Measures,https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb,Risk measures and factors for alternative and responsible investments.,Factor and Risk Analysis,11/4/20 7:04,4.0,5.0,1.0,8/7/17 14:44,8/8/17 22:52,Jorgencr/Alternative-and-Responsible-Investments,inactive,,
CAPM,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb,Expected returns using CAPM.,Factor and Risk Analysis,3/1/21 13:53,31.0,18.0,1.0,5/10/16 11:03,5/17/16 3:44,RJT1990/Active-Portfolio-Management-Notes,inactive,,
Quant Finance,https://github.com/mrefermat/quant_finance,General quant repository.,Factor and Risk Analysis,3/30/21 0:09,31.0,15.0,1.0,8/11/18 22:59,11/12/19 4:49,mrefermat/quant_finance,active,,
Stock-Prediction,https://github.com/Ronak-59/Stock-Prediction,NEW,Factor and Risk Analysis,3/26/21 8:37,129.0,64.0,2.0,3/18/18 4:54,2/28/20 11:43,Ronak-59/Stock-Prediction,active,,37:06.3
Risk and Return,https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials,Riskiness of portfolios and assets.,Factor and Risk Analysis,4/6/21 17:03,140.0,62.0,2.0,9/12/17 13:35,8/6/20 12:35,PyDataBlog/Python-for-Data-Science,active,,
AlphaTrading,https://github.com/jerryxyx/AlphaTrading,NEW,Factor and Risk Analysis,4/10/21 6:34,149.0,74.0,1.0,5/18/18 22:09,8/7/18 18:05,jerryxyx/AlphaTrading,inactive,,37:06.3
Risk Basic,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb,Active portfolio risk management .,Factor and Risk Analysis,3/1/21 13:53,31.0,18.0,1.0,5/10/16 11:03,5/17/16 3:44,RJT1990/Active-Portfolio-Management-Notes,inactive,,
VaR,https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb,Value-at-risk calculations.,Factor and Risk Analysis,3/31/21 2:06,10.0,9.0,1.0,11/15/16 19:24,1/14/17 21:19,willb/var-notebook,inactive,,
Factor Analysis,https://github.com/alpha-miner/alpha-mind/tree/master/notebooks,Factor strategy notebooks.,Factor and Risk Analysis,4/8/21 19:02,172.0,60.0,3.0,5/1/17 7:36,4/7/21 15:25,alpha-miner/alpha-mind,active,,
Convex Optimisation,https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb,Convex Optimization for Finance.,Factor and Risk Analysis,4/8/21 19:02,18.0,10.0,1.0,6/26/18 20:36,10/22/19 21:56,ssanderson/convex-optimization-for-finance,active,,
Binomial Tree,https://github.com/hy-lei/math-finance-exercise,Utility functions in fixed income securities.,Fixed Income,10/6/20 20:55,1.0,2.0,1.0,2/2/19 8:44,5/3/19 17:16,hy-lei/math-finance-toolbox,active,,
Vasicek,https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb,Bootstrapping and interpolation.,Fixed Income,12/10/20 21:20,3.0,3.0,1.0,7/18/18 19:26,7/18/18 19:34,RobinsonGarcia/fixed-income,inactive,,
Corporate Bonds,https://github.com/ishank011/gs-quantify-bond-prediction,Predicting the buying and selling volume of the corporate bonds.,Fixed Income,1/3/21 21:46,7.0,5.0,1.0,9/27/17 19:57,9/27/17 20:00,ishank011/gs-quantify-bond-prediction,inactive,,
AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,NEW,Other Models,4/4/21 20:02,576.0,130.0,3.0,2/14/16 0:47,2/8/21 21:35,ScottfreeLLC/AlphaPy,active,,39:24.6
Awesome-Quant-Machine-Learning-Trading,https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading,NEW,Other Models,4/10/21 13:38,1005.0,319.0,3.0,11/5/18 21:09,10/8/20 16:48,grananqvist/Awesome-Quant-Machine-Learning-Trading,active,,39:24.6
botflow,https://github.com/kkyon/botflow,NEW,Other Models,3/31/21 10:56,1165.0,102.0,8.0,8/20/18 3:13,5/23/19 14:40,kkyon/botflow,active,,39:24.6
surpriver,https://github.com/tradytics/surpriver,NEW,Other Models,4/12/21 12:27,1189.0,221.0,6.0,8/30/20 7:56,9/21/20 4:32,tradytics/surpriver,active,,39:24.6
Pattern-Recognition-for-Forex-Trading,https://github.com/PythonProgramming/Pattern-Recognition-for-Forex-Trading,NEW,Other Models,4/5/21 3:23,173.0,91.0,1.0,3/26/15 2:22,3/26/15 2:33,PythonProgramming/Pattern-Recognition-for-Forex-Trading,inactive,,39:24.6
awesome-ai-in-finance,https://github.com/georgezouq/awesome-ai-in-finance,NEW,Other Models,4/11/21 7:43,941.0,162.0,8.0,8/29/18 2:07,11/27/20 9:43,georgezouq/awesome-ai-in-finance,active,,39:24.6
Microservices-Based-Algorithmic-Trading-System,https://github.com/saeed349/Microservices-Based-Algorithmic-Trading-System,NEW,Other Models,4/10/21 12:59,104.0,56.0,0.0,1/6/20 0:21,3/31/20 13:02,saeed349/Microservices-Based-Algorithmic-Trading-System,active,,39:24.6
Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,NEW,Other Models,4/11/21 6:02,172.0,94.0,5.0,12/6/18 11:35,1/18/21 6:40,PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python,active,,39:24.6
Stock.Indicators,https://github.com/DaveSkender/Stock.Indicators,NEW,Other Models,4/12/21 10:47,175.0,64.0,9.0,12/29/19 5:18,4/11/21 19:17,DaveSkender/Stock.Indicators,active,,39:24.6
finance_ml,https://github.com/jjakimoto/finance_ml,NEW,Other Models,4/8/21 15:28,282.0,117.0,1.0,6/29/18 21:21,2/18/19 12:34,jjakimoto/finance_ml,inactive,,39:24.6
Machine-Learning-For-Finance,https://github.com/anthonyng2/Machine-Learning-For-Finance,NEW,Other Models,4/1/21 20:11,205.0,119.0,1.0,7/11/17 9:09,2/21/18 5:36,anthonyng2/Machine-Learning-For-Finance,inactive,,39:24.6
mlfinlab,https://github.com/hudson-and-thames/mlfinlab,NEW,Other Models,4/12/21 10:51,2295.0,709.0,3.0,2/13/19 16:57,4/12/21 10:50,hudson-and-thames/mlfinlab,active,,39:24.6
Machine-Learning-for-Finance,https://github.com/PacktPublishing/Machine-Learning-for-Finance,NEW,Other Models,4/8/21 16:54,180.0,122.0,4.0,3/15/18 6:28,1/14/21 15:58,PacktPublishing/Machine-Learning-for-Finance,active,,39:24.6
MathAndScienceNotes,https://github.com/melling/MathAndScienceNotes,Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/),Other Models,4/12/21 0:49,460.0,54.0,1.0,3/11/16 19:13,12/21/20 3:54,melling/MathAndScienceNotes,active,,39:24.6
CryptoBot,https://github.com/AdeelMufti/CryptoBot,Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained,Other Models,3/25/21 9:17,234.0,94.0,1.0,1/17/17 12:44,1/17/17 12:48,AdeelMufti/CryptoBot,inactive,2.0,39:24.6
Hands-On-Machine-Learning-for-Algorithmic-Trading,https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading,repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have,Other Models,4/12/21 15:41,600.0,386.0,2.0,5/7/19 11:04,1/19/21 7:51,PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading,active,5.0,39:24.6
Trend Following,http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html,A futures trend following portfolio investment strategy.,Other Models,,,,,,,,,,
Short-Term Movement Cues,https://github.com/anfederico/Clairvoyant,Identify social/historical cues for short term stock movement.,Other Models,4/12/21 13:11,2166.0,678.0,1.0,9/12/16 18:38,8/29/18 20:27,anfederico/clairvoyant,inactive,,
Mixture Models II,https://github.com/BlackArbsCEO/mixture_model_trading_public,Mixture models and stock trading.,Other Models,3/12/21 13:21,166.0,73.0,1.0,12/11/17 17:05,5/13/20 23:50,BlackArbsCEO/mixture_model_trading_public,active,,
fin-ml,https://github.com/tatsath/fin-ml,NEW,Other Models,4/11/21 3:29,116.0,66.0,2.0,5/10/20 0:25,1/23/21 17:15,tatsath/fin-ml,active,,39:24.6
Fundamental LT Forecasts,https://github.com/Hvass-Labs/FinanceOps,Research in investment finance for long term forecasts.,Other Models,4/5/21 23:36,383.0,127.0,1.0,7/22/18 8:14,2/17/21 14:39,Hvass-Labs/FinanceOps,active,,
Speculator,https://github.com/amicks/Speculator,NEW,Other Models,3/15/21 16:27,101.0,31.0,2.0,9/3/17 17:43,9/12/18 18:58,amicks/Speculator,inactive,,39:24.6
Machine-Learning-and-AI-in-Trading,https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading,NEW,Other Models,4/8/21 11:31,261.0,101.0,1.0,8/30/17 6:14,10/29/19 8:14,PyPatel/Machine-Learning-and-AI-in-Trading,active,,39:24.6
Mixture Models I,https://github.com/BlackArbsCEO/Mixture_Models,Mixture models to predict market bottoms.,Other Models,3/2/21 19:44,31.0,31.0,1.0,3/20/17 18:54,4/25/17 23:35,BlackArbsCEO/Mixture_Models,inactive,,
stock-trading-ml,https://github.com/yacoubb/stock-trading-ml,NEW,Other Models,4/11/21 14:46,340.0,186.0,1.0,10/10/19 9:44,10/12/19 11:38,yacoubb/stock-trading-ml,active,,39:24.6
Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,NEW,Other Models,4/8/21 20:01,279.0,126.0,4.0,11/15/19 8:51,1/21/21 7:56,PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original,active,,39:24.6
mosquito,https://github.com/miro-ka/mosquito,NEW,Other Models,4/12/21 9:44,220.0,44.0,2.0,6/18/17 19:57,3/14/21 22:22,miro-ka/mosquito,active,,39:24.6
Scikit-learn Stock Prediction,https://github.com/robertmartin8/MachineLearningStocks,Using python and scikit-learn to make stock predictions.,Other Models,4/11/21 10:00,931.0,347.0,2.0,2/12/17 4:50,2/4/21 3:48,robertmartin8/MachineLearningStocks,active,,
ML_Finance_Codes,https://github.com/mfrdixon/ML_Finance_Codes,NEW,Other Models,4/11/21 8:30,250.0,104.0,3.0,9/27/19 16:13,6/13/20 21:20,mfrdixon/ML_Finance_Codes,active,,39:24.6
Machine Learning in Asset Management,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952,,Personal Papers,,,,,,,,,,
Financial Event Prediction using Machine Learning,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555,,Personal Papers,,,,,,,,,,
Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization,https://jfds.pm-research.com/content/2/2/17,,Personal Papers,,,,,,,,,,
Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies,https://jfds.pm-research.com/content/2/1/10,,Personal Papers,,,,,,,,,,
OLMAR Algorithm,https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb,Relative importance of each component of the OLMAR algorithm.,Portfolio Selection and Optimisation,4/8/21 19:07,7.0,4.0,1.0,7/26/16 16:20,12/30/16 11:40,charlessutton/OLMAR,inactive,,
Online Portfolio Selection,https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb,****Comparing OLPS algorithms on a diversified set of ETFs.,Portfolio Selection and Optimisation,,,,,,,,,,
Riskfolio-Lib,https://github.com/dcajasn/Riskfolio-Lib,NEW,Portfolio Selection and Optimisation,4/12/21 12:25,371.0,62.0,1.0,3/2/20 19:49,4/1/21 3:50,dcajasn/Riskfolio-Lib,active,,37:19.5
Efficient Frontier,https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb,Modern Portfolio Theory.,Portfolio Selection and Optimisation,3/30/21 0:01,104.0,57.0,1.0,2/17/18 8:19,2/27/18 13:16,tthustla/efficient_frontier,inactive,,
Policy Gradient Portfolio,https://github.com/ZhengyaoJiang/PGPortfolio,A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.,Portfolio Selection and Optimisation,4/9/21 10:41,1281.0,629.0,6.0,11/12/17 16:08,5/9/19 9:50,ZhengyaoJiang/PGPortfolio,active,,
Deep Portfolio Theory,https://github.com/tcloaa/Deep-Portfolio-Theory,Autoencoder framework for portfolio selection.,Portfolio Selection and Optimisation,4/6/21 11:47,105.0,57.0,1.0,2/10/17 9:03,3/8/18 16:47,tcloaa/Deep-Portfolio-Theory,inactive,,
PyPortfolioOpt,https://github.com/robertmartin8/PyPortfolioOpt,"Financial portfolio optimisation, including classical efficient frontier and advanced methods.",Portfolio Selection and Optimisation,4/12/21 11:54,1895.0,479.0,16.0,5/29/18 13:30,2/25/21 13:01,robertmartin8/PyPortfolioOpt,active,,
node-finance,https://github.com/albertosantini/node-finance,NEW,Portfolio Selection and Optimisation,4/5/21 8:01,101.0,26.0,3.0,9/17/11 17:49,4/5/21 8:01,albertosantini/node-finance,active,,37:19.5
Reinforcement Learning,https://github.com/filangel/qtrader,Reinforcement Learning for Portfolio Management.,Portfolio Selection and Optimisation,3/29/21 3:47,364.0,150.0,1.0,10/7/17 9:14,6/26/18 9:22,filangelos/qtrader,inactive,,
DeepDow,https://github.com/jankrepl/deepdow,Portfolio optimization with deep learning.,Portfolio Selection and Optimisation,4/7/21 6:57,311.0,58.0,2.0,2/2/20 8:46,2/16/21 18:50,jankrepl/deepdow,active,,
Distribution Characteristic Optimisation,https://github.com/VivekPa/OptimalPortfolio,Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.,Portfolio Selection and Optimisation,4/12/21 13:10,232.0,82.0,3.0,11/16/18 12:20,7/4/19 1:41,VivekPa/OptimalPortfolio,active,,
401K Portfolio Optimisation,https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb,Portfolio analyses and optimisation for 401K.,Portfolio Selection and Optimisation,12/25/20 9:39,14.0,5.0,1.0,8/1/18 19:48,9/5/19 11:18,otosman/Python-for-Finance,active,,
Modern Portfolio Theory,https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb,Universal portfolios; modern portfolio theory.,Portfolio Selection and Optimisation,,,,,,,,,,
riskparity.py,https://github.com/dppalomar/riskparity.py,NEW,Portfolio Selection and Optimisation,4/11/21 9:40,124.0,31.0,2.0,7/13/19 21:30,1/30/21 1:53,dppalomar/riskparity.py,active,,37:19.5
Fund classification,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Fund classification using text mining and NLP.,Textual,3/31/21 2:12,4.0,2.0,1.0,4/16/18 22:18,6/7/18 22:01,frechfrechfrech/Mutual-Fund-Market-Clusters,inactive,,
Earning call transcripts,https://github.com/lin882/WebAnalyticsProject,Correlation between mutual fund investment decision and earning call transcripts.,Textual,12/17/20 8:24,3.0,3.0,1.0,12/30/17 8:56,1/11/18 2:11,lin882/WebAnalyticsProject,inactive,,
Accounting Anomalies,https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb,Using deep-learning frameworks to identify accounting anomalies.,Textual,4/12/21 7:47,110.0,51.0,2.0,5/24/17 12:36,8/7/19 21:47,GitiHubi/deepAI,active,,
Buzzwords,https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds,Return performance and mutual fund selection.,Textual,10/6/20 18:54,1.0,4.0,1.0,2/4/18 21:51,2/4/18 21:57,swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds,inactive,,
NLP,https://github.com/toamitesh/NLPinFinance,This project assembles a lot of NLP operations needed for finance domain.,Textual,,,,,,,toamitesh/NLPinFinance,,,
Financial Sentiment Analysis,https://github.com/EricHe98/Financial-Statements-Text-Analysis,"Sentiment, distance and proportion analysis for trading signals.",Textual,3/31/21 23:48,48.0,27.0,1.0,6/23/17 0:05,1/26/19 3:35,EricHe98/Financial-Statements-Text-Analysis,inactive,,
NLP Event,https://github.com/yuriak/DLQuant,Applying Deep Learning and NLP in Quantitative Trading.,Textual,4/1/21 2:16,70.0,31.0,1.0,7/2/18 23:50,1/31/19 14:08,yuriak/DLQuant,inactive,,
Financial Statement Sentiment,https://github.com/MAydogdu/TextualAnalysis,Extracting sentiment from financial statements using neural networks.,Textual,3/31/21 2:10,8.0,7.0,1.0,6/4/18 20:54,6/4/18 20:56,MAydogdu/TextualAnalysis,inactive,,
Extensive NLP,https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb,Comprehensive NLP techniques for accounting research.,Textual,3/21/21 7:39,73.0,42.0,1.0,10/25/17 7:10,6/5/20 3:28,TiesdeKok/Python_NLP_Tutorial,active,,
Pairs Trading,https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb,Finding pairs with cluster analysis.,Unsupervised,4/4/21 17:55,79.0,36.0,0.0,9/5/17 19:19,9/27/17 20:42,marketneutral/pairs-trading-with-ML,inactive,,
PCA Pairs Trading,https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading,"PCA, Factor Returns, and trading strategies.",Unsupervised,,,,,,,joelQF/quant-finance,,,
Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Clustering of industries.,Unsupervised,10/6/20 18:51,4.0,5.0,1.0,7/21/17 2:12,7/23/17 2:53,SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,inactive,,
Fund Clusters,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Data exploration of fund clusters.,Unsupervised,3/31/21 2:12,4.0,2.0,1.0,4/16/18 22:18,6/7/18 22:01,frechfrechfrech/Mutual-Fund-Market-Clusters,inactive,,
VRA Stock Embedding,https://github.com/ml-hongkong/stock2vec,Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.,Unsupervised,10/20/20 11:05,32.0,12.0,1.0,6/21/17 4:47,6/21/17 4:51,ml-hongkong/stock2vec,inactive,,
Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Project to cluster industries according to financial attributes.,Unsupervised,10/6/20 18:51,4.0,5.0,1.0,7/21/17 2:12,7/23/17 2:53,SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,inactive,,
1 name url comment category last_update star_count fork_count contributors_count created_at last_commit repo_path repo_status rating finml_added_date
2 Venture Capital NN https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring Cox-PH neural network predictions for VC/innovations finance research. Alternative Finance tr7200/National-Culture-and-Venture-Capital-Monitoring
3 Private Equity https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb Valuation models. Alternative Finance 11/26/20 3:34 8 8.0 6 6.0 2 2.0 1/27/16 21:13 3/14/16 20:03 TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity inactive
4 VC OLS https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb VC regression. Alternative Finance 10/6/20 20:56 2 2.0 1 1.0 1 1.0 3/29/18 23:31 3/29/18 23:33 fionawhitefield/venture-capital-ols inactive
5 Watch Valuation https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued. Alternative Finance 1/14/21 22:41 4 4.0 2 2.0 1 1.0 2/8/17 18:39 4/27/17 22:55 alporter08/Luxury-Watch-Valuation inactive
6 Art Valuation https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb Art evaluation analytics. Alternative Finance 2/26/21 12:10 9 9.0 5 5.0 1 1.0 12/11/14 0:25 12/12/14 21:25 ahmedhosny/theGreenCanvas inactive
7 Blockchain https://github.com/nud3l/dInvest Repository for distributed autonomous investment banking. Alternative Finance 2/6/21 7:38 12 12.0 7 7.0 2 2.0 9/5/16 19:12 4/24/17 10:48 nud3l/dInvest inactive
8 Venture Capital https://github.com/julian-chan/etothex Insight into a new founder to make data-driven investment decisions. Alternative Finance 10/6/20 20:56 3 3.0 2 2.0 1 1.0 12/4/17 8:59 12/13/17 5:35 julian-chan/etothex inactive
9 Kiva Crowdfunding https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb Exploratory data analysis. Alternative Finance 2/19/21 13:40 5 5.0 1 1.0 1 1.0 2/27/18 16:46 2/13/19 0:15 CJL89/Kiva-Crowdfunding inactive
10 NYU Courant Cornell University https://cims.nyu.edu/ https://www.cornell.edu/ Courant Institute of Mathematical Sciences, New York University Colleges Centers and Departments
11 Oxford Man Stanford Advanced Financial Technologies https://www.oxford-man.ox.ac.uk/ https://fintech.stanford.edu/ Oxford-Man Institute of Quantitative Finance Stanford Advanced Financial Technologies Laboratory Colleges Centers and Departments
12 Berkeley Lab CIFT NYU FRE https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/ https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering Finance and Risk Engineering (NYU Tandon) Colleges Centers and Departments
13 NYU FRE Oxford Man https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering https://www.oxford-man.ox.ac.uk/ Finance and Risk Engineering (NYU Tandon) Oxford-Man Institute of Quantitative Finance Colleges Centers and Departments
14 Stanford Advanced Financial Technologies NYU Courant https://fintech.stanford.edu/ https://cims.nyu.edu/ Stanford Advanced Financial Technologies Laboratory Courant Institute of Mathematical Sciences, New York University Colleges Centers and Departments
15 Cornell University Berkeley Lab CIFT https://www.cornell.edu/ https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/ Colleges Centers and Departments
16 Basic Investments Machine Learning for Trading https://github.com/SeanMcOwen/FinanceAndPython.com-Investments https://github.com/stefan-jansen/machine-learning-for-trading Basic investment tools in python. Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading. Courses 3/23/21 6:32 4/12/21 16:18 9 3842.0 5 1225.0 1 8.0 8/2/17 21:52 5/9/18 12:33 8/17/17 3:24 4/10/21 22:21 SeanMcOwen/FinanceAndPython.com-Investments stefan-jansen/machine-learning-for-trading inactive active
17 Risk Management Basic Derivatives https://github.com/andrey-lukyanov/Risk-Management https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives Finance risk engagement course resources. Basic forward contracts and hedging. Courses 11/12/20 0:49 3/31/21 2:08 6 4.0 5 4.0 3 1.0 10/3/18 16:26 8/24/17 0:11 12/13/18 8:04 10/13/17 1:32 andrey-lukyanov/Risk-Management SeanMcOwen/FinanceAndPython.com-Derivatives inactive
18 Basic Finance Python for Finance https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance https://github.com/siaen/python_finance_course Source code notebooks basic finance applications. CEU python for finance course material. Courses 3/31/21 2:09 3/31/21 2:08 10 16.0 8 15.0 1 4.0 5/6/17 2:39 12/12/17 11:54 6/21/17 4:04 2/25/20 20:31 SeanMcOwen/FinanceAndPython.com-BasicFinance siaen/python_finance_course inactive active
19 ML Specialisation Algo Trading https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading Machine Learning in Finance. Intro to algo trading. Courses 4/5/21 13:37 3/12/21 11:02 34 64.0 32 25.0 1 1.0 1/24/19 2:55 10/29/17 20:34 1/3/20 21:54 1/22/19 6:56 Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization JCreeks/Machine-Learning-in-Finance active inactive
20 Handson Python for Finance Mathematical Finance https://github.com/PacktPublishing/Hands-on-Python-for-Finance https://github.com/yadongli/nyumath2048 Hands-on Python for Finance published by Packt. NYU Math-GA 2048: Scientific Computing in Finance. Courses 4/12/21 0:49 1/14/21 18:01 121 69.0 110 63.0 3 6.0 8/20/18 14:10 1/25/15 21:10 1/15/21 8:57 3/25/20 4:24 PacktPublishing/Hands-on-Python-for-Finance yadongli/nyumath2048 active
21 Mathematical Finance Basic Investments https://github.com/yadongli/nyumath2048 https://github.com/SeanMcOwen/FinanceAndPython.com-Investments NYU Math-GA 2048: Scientific Computing in Finance. Basic investment tools in python. Courses 1/14/21 18:01 3/23/21 6:32 69 9.0 63 5.0 6 1.0 1/25/15 21:10 8/2/17 21:52 3/25/20 4:24 8/17/17 3:24 yadongli/nyumath2048 SeanMcOwen/FinanceAndPython.com-Investments active inactive
22 Machine Learning for Trading ML Specialisation https://github.com/stefan-jansen/machine-learning-for-trading https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading. Machine Learning in Finance. Courses 4/12/21 16:18 4/5/21 13:37 3842 34.0 1225 32.0 8 1.0 5/9/18 12:33 1/24/19 2:55 4/10/21 22:21 1/3/20 21:54 stefan-jansen/machine-learning-for-trading Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization active
23 Algo Trading Basic Finance https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance Intro to algo trading. Source code notebooks basic finance applications. Courses 3/12/21 11:02 3/31/21 2:09 64 10.0 25 8.0 1 1.0 10/29/17 20:34 5/6/17 2:39 1/22/19 6:56 6/21/17 4:04 JCreeks/Machine-Learning-in-Finance SeanMcOwen/FinanceAndPython.com-BasicFinance inactive
24 Python for Finance Risk Management https://github.com/siaen/python_finance_course https://github.com/andrey-lukyanov/Risk-Management CEU python for finance course material. Finance risk engagement course resources. Courses 3/31/21 2:08 11/12/20 0:49 16 6.0 15 5.0 4 3.0 12/12/17 11:54 10/3/18 16:26 2/25/20 20:31 12/13/18 8:04 siaen/python_finance_course andrey-lukyanov/Risk-Management active inactive
25 Basic Derivatives Handson Python for Finance https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives https://github.com/PacktPublishing/Hands-on-Python-for-Finance Basic forward contracts and hedging. Hands-on Python for Finance published by Packt. Courses 3/31/21 2:08 4/12/21 0:49 4 121.0 4 110.0 1 3.0 8/24/17 0:11 8/20/18 14:10 10/13/17 1:32 1/15/21 8:57 SeanMcOwen/FinanceAndPython.com-Derivatives PacktPublishing/Hands-on-Python-for-Finance inactive active
26 Open Edgar Financial Corporate https://github.com/LexPredict/openedgar http://raw.rutgers.edu/Corporate%20Financial%20Data.html Data 4/9/21 12:15 169 61 6 5/7/18 15:32 5/15/19 8:32 LexPredict/openedgar active
27 Capital Markets Data https://github.com/timestocome/StockMarketData https://www.capitalmarketsdata.com/ https://github.com/timestocome/StockMarketData Data 3/26/21 22:35 7.0 5.0 1.0 5/10/17 21:49 8/6/17 19:23 timestocome/StockMarketData inactive
28 IRS http://finance.yahoo.com/ http://social-metrics.org/sox/ http://finance.yahoo.com/ Data
29 Employee Count SEC Filings Rating Industries https://github.com/healthgradient/sec_employee_information_extraction http://www.ratingshistory.info/ Data 2/27/21 3:33 10 2 1 6/26/18 23:33 8/14/18 1:31 healthgradient/sec_employee_information_extraction inactive
30 EDGAR https://fred.stlouisfed.org/ https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb https://fred.stlouisfed.org/ Data 1/23/21 19:22 11 10 1 6/11/18 22:51 7/10/18 18:03 TiesdeKok/UW_Python_Camp inactive
31 SEC Parsing Non-financial Corporate https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html Data 2/27/21 6:34 9 6 1 6/16/18 14:30 6/16/18 17:23 healthgradient/sec-doc-info-extraction inactive
32 Web Scraping (FirmAI) https://stooq.com https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data https://stooq.com Data 4/10/21 17:19 577 184 2 2/19/19 19:02 7/22/20 16:48 firmai/business-machine-learning active
33 Non-financial Corporate SEC Parsing http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb Data 2/27/21 6:34 9.0 6.0 1.0 6/16/18 14:30 6/16/18 17:23 healthgradient/sec-doc-info-extraction inactive
34 https://stooq.com Web Scraping (FirmAI) https://stooq.com https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data Data 4/10/21 17:19 577.0 184.0 2.0 2/19/19 19:02 7/22/20 16:48 firmai/business-machine-learning active
35 Financial Corporate EDGAR http://raw.rutgers.edu/Corporate%20Financial%20Data.html https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb Data 1/23/21 19:22 11.0 10.0 1.0 6/11/18 22:51 7/10/18 18:03 TiesdeKok/UW_Python_Camp inactive
36 https://fred.stlouisfed.org/ Employee Count SEC Filings https://fred.stlouisfed.org/ https://github.com/healthgradient/sec_employee_information_extraction Data 2/27/21 3:33 10.0 2.0 1.0 6/26/18 23:33 8/14/18 1:31 healthgradient/sec_employee_information_extraction inactive
37 Rating Industries IRS http://www.ratingshistory.info/ http://social-metrics.org/sox/ Data
38 http://finance.yahoo.com/ Capital Markets Data http://finance.yahoo.com/ https://www.capitalmarketsdata.com/ Data
39 https://github.com/timestocome/StockMarketData Open Edgar https://github.com/timestocome/StockMarketData https://github.com/LexPredict/openedgar Data 3/26/21 22:35 4/9/21 12:15 7 169.0 5 61.0 1 6.0 5/10/17 21:49 5/7/18 15:32 8/6/17 19:23 5/15/19 8:32 timestocome/StockMarketData LexPredict/openedgar inactive active
40 Advanced ML II Twitter-Trends https://github.com/hudson-and-thames/research https://github.com/Medha11/Twitter-Trends More implementations of Financial Machine Learning (De Prado). NEW Data Processing Techniques and Transformations 2021-02-07 09:16:53 66.0 21.0 1.0 2017-05-22 17:07:45 2017-05-23 08:06:27 hudson-and-thames/research Medha11/Twitter-Trends inactive 2021-04-13 16:12:49.160843
41 Advanced ML cointrader https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises https://github.com/timolson/cointrader Exercises too Financial Machine Learning (De Prado). NEW Data Processing Techniques and Transformations 4/12/21 2:20 2021-04-10 17:16:37 973 339.0 435 140.0 4 9.0 4/25/18 17:22 2014-06-01 01:14:12 1/16/20 17:25 2020-10-22 00:24:50 BlackArbsCEO/Adv_Fin_ML_Exercises timolson/cointrader active 2021-04-13 16:12:49.160843
42 awesome-deep-trading Google-Finance-Stock-Data-Analysis https://github.com/cbailes/awesome-deep-trading https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes NEW Deep Learning And Reinforcement Learning Data Processing Techniques and Transformations 4/11/21 9:02 2020-12-20 08:39:26 551 70.0 140 10.0 1 1.0 11/26/18 3:23 2017-07-23 02:59:59 1/1/21 9:41 2017-07-23 03:10:35 cbailes/awesome-deep-trading hpnhxxwn/Google-Finance-Stock-Data-Analysis active inactive 4 3/31/21 8:00 2021-04-13 16:12:49.160843
43 Deep Learning IV finserv-application-blueprint https://github.com/achillesrasquinha/bulbea https://github.com/mapr-demos/finserv-application-blueprint Bulbea: Deep Learning based Python Library. NEW Deep Learning And Reinforcement Learning Data Processing Techniques and Transformations 4/9/21 20:38 2021-01-21 00:29:14 1467 72.0 416 53.0 1 5.0 3/9/17 6:11 2016-09-26 19:42:54 3/19/17 7:42 2021-01-20 23:07:40 achillesrasquinha/bulbea mapr-demos/finserv-application-blueprint inactive active 5 2021-04-13 16:12:49.160843
44 AI Trading Advanced ML https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises AI to predict stock market movements. Exercises too Financial Machine Learning (De Prado). Deep Learning And Reinforcement Learning Data Processing Techniques and Transformations 4/12/21 15:42 4/12/21 2:20 2876 973.0 1384 435.0 1 4.0 1/9/19 8:02 4/25/18 17:22 2/11/19 16:32 1/16/20 17:25 borisbanushev/stockpredictionai BlackArbsCEO/Adv_Fin_ML_Exercises inactive active 5
45 ARIMA-LTSM Hybrid Advanced ML II https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid https://github.com/hudson-and-thames/research Hybrid model to predict future price correlation coefficients of two assets. More implementations of Financial Machine Learning (De Prado). Deep Learning And Reinforcement Learning Data Processing Techniques and Transformations 4/11/21 4:12 222 86 1 8/5/18 2:13 10/1/18 11:25 imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict hudson-and-thames/research inactive 3
46 trading-rl CryptoNets https://github.com/Kostis-S-Z/trading-rl https://github.com/microsoft/CryptoNets Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained NEW Deep Learning And Reinforcement Learning Data Processing Techniques and Transformations 4/10/21 4:59 2021-04-08 01:07:55 180 154.0 38 42.0 2 4.0 4/22/19 10:03 2019-06-02 05:48:39 9/28/20 9:07 2019-09-12 13:03:05 Kostis-S-Z/trading-rl microsoft/CryptoNets active 3 3/31/21 8:00 2021-04-13 16:12:49.160843
47 Deep Learning III a3c_trading https://github.com/Rachnog/Deep-Trading https://github.com/evgps/a3c_trading Algorithmic trading with deep learning experiments. NEW Deep Learning And Reinforcement Learning 4/9/21 10:39 4/10/21 12:49 1266 311.0 675 98.0 1 1.0 6/18/16 18:23 6/4/18 15:30 8/7/18 15:24 5/23/20 14:47 Rachnog/Deep-Trading evgps/a3c_trading inactive active 5 39:11.1
48 Stock-Prediction-Models Trading-Gym https://github.com/huseinzol05/Stock-Prediction-Models https://github.com/thedimlebowski/Trading-Gym very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert)) NEW Deep Learning And Reinforcement Learning 4/12/21 13:54 4/10/21 8:00 3655 507.0 1542 147.0 2 3.0 12/18/17 10:49 6/13/17 13:14 1/5/21 10:31 7/10/17 8:09 huseinzol05/Stock-Prediction-Models thedimlebowski/Trading-Gym active inactive 5 3/31/21 8:00 39:11.1
49 RLTrader DQN-DDPG_Stock_Trading https://github.com/notadamking/RLTrader https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc. merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN Deep Learning And Reinforcement Learning 4/12/21 2:50 4/7/21 12:42 1312 136.0 451 49.0 15 4.0 4/27/19 18:35 9/19/18 3:17 10/17/19 16:25 11/26/20 16:58 notadamking/RLTrader AI4Finance-LLC/DQN-DDPG_Stock_Trading active 5 3.0 3/31/21 8:00
50 Neural Network pairstrade-fyp-2019 https://github.com/VivekPa/IntroNeuralNetworks https://github.com/wywongbd/pairstrade-fyp-2019 Neural networks to predict stock prices. NEW Deep Learning And Reinforcement Learning 4/3/21 11:59 4/4/21 23:47 489 110.0 176 41.0 2 2.0 9/10/18 6:34 9/7/18 7:51 11/21/18 7:39 5/13/20 5:06 VivekPa/IntroNeuralNetworks wywongbd/pairstrade-fyp-2019 inactive active 4 39:11.1
51 LTSM Recurrent rl_trading https://github.com/VivekPa/AIAlpha https://github.com/ucaiado/rl_trading OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network. NEW Deep Learning And Reinforcement Learning 4/12/21 2:39 4/8/21 15:34 1207 207.0 370 89.0 2 1.0 10/7/18 3:58 5/29/17 22:19 8/3/19 9:00 8/29/17 14:54 VivekPa/AIAlpha ucaiado/rl_trading active inactive 4 39:11.1
52 Deep Learning II Machine-Learning-and-Reinforcement-Learning-in-Finance https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance Tensorflow Regression. NEW Deep Learning And Reinforcement Learning 4/10/21 6:06 3/30/21 9:11 175 175.0 67 98.0 1 1.0 7/12/16 12:56 6/26/18 4:30 2/16/18 2:43 9/23/18 16:50 LiamConnell/deep-algotrading joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance inactive 3 39:11.1
53 trading-bot maro https://github.com/pskrunner14/trading-bot https://github.com/microsoft/maro Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python NEW Deep Learning And Reinforcement Learning 4/11/21 5:10 4/12/21 2:22 292 386.0 143 66.0 1 17.0 8/13/18 10:44 12/27/19 6:48 1/23/20 4:41 4/7/21 15:49 pskrunner14/trading-bot microsoft/maro active 3 3/31/21 8:00 39:11.1
54 LTSM GRU TradingGym https://github.com/RajatHanda/Finance-Forecasting https://github.com/cove9988/TradingGym Stock Market Forecasting using LSTM\GRU. NEW Deep Learning And Reinforcement Learning 3/29/21 23:59 3/28/21 5:37 11 112.0 6 39.0 1 3.0 5/13/18 2:39 11/6/17 0:50 2/25/19 0:26 11/15/17 23:55 RajatHanda/Finance-Forecasting cove9988/TradingGym inactive 3 39:11.1
55 DeepLearningInFinance RLQuant https://github.com/sonaam1234/DeepLearningInFinance https://github.com/yuriak/RLQuant Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. NEW Deep Learning And Reinforcement Learning 3/8/21 13:09 4/9/21 5:01 266 277.0 145 92.0 1 1.0 8/21/17 16:00 4/5/18 5:42 8/21/17 17:23 8/13/18 4:18 sonaam1234/DeepLearningInFinance yuriak/RLQuant inactive 3 3/31/21 8:00 39:11.1
56 crypto-rl RL Trading https://github.com/sadighian/crypto-rl https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process) A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab. Deep Learning And Reinforcement Learning 4/12/21 10:24 347 111 1 6/21/18 1:06 11/5/20 11:08 sadighian/crypto-rl active 3 4.0 3/31/21 8:00
57 Deep-Reinforcement-Stock-Trading QLearning_Trading https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading https://github.com/ucaiado/QLearning_Trading inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats NEW Deep Learning And Reinforcement Learning 4/3/21 22:50 4/6/21 22:09 141 433.0 42 168.0 2 1.0 5/19/19 22:20 8/10/16 6:02 9/27/20 19:22 10/15/16 2:36 Albert-Z-Guo/Deep-Reinforcement-Stock-Trading ucaiado/QLearning_Trading active inactive 3 3/31/21 8:00 39:11.1
58 Advanced-Deep-Trading gym-trading https://github.com/Rachnog/Advanced-Deep-Trading https://github.com/hackthemarket/gym-trading notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. NEW Deep Learning And Reinforcement Learning 3/30/21 7:29 4/12/21 9:06 319 581.0 158 195.0 2 2.0 2/16/19 21:18 12/9/16 20:46 11/29/20 20:12 12/24/17 15:34 Rachnog/Advanced-Deep-Trading hackthemarket/gym-trading active inactive 3 3/31/21 8:00 39:11.1
59 Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 RL II https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 https://github.com/deependersingla/deep_trader Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble. reinforcement learning on stock market and agent tries to learn trading. Deep Learning And Reinforcement Learning 4/12/21 16:24 4/11/21 20:21 560 1340.0 249 489.0 6 3.0 7/26/20 13:12 6/11/16 7:27 1/21/21 18:11 1/22/18 14:35 AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 deependersingla/deep_trader active inactive 4 3.0 3/31/21 8:00
60 AutomatedStockTrading-DeepQ-Learning RL https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning https://github.com/kh-kim/stock_market_reinforcement_learning cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report OpenGym with Deep Q-learning and Policy Gradient. Deep Learning And Reinforcement Learning 3/24/21 1:11 4/11/21 12:27 134 715.0 51 298.0 2 1.0 2/23/19 12:01 10/4/16 14:42 2/25/20 18:16 12/23/16 7:34 sachink2010/AutomatedStockTrading-DeepQ-Learning kh-kim/stock_market_reinforcement_learning active inactive 3 2.0 3/31/21 8:00
61 deep-RL-trading RL V https://github.com/golsun/deep-RL-trading https://github.com/gstenger98/rl-finance trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916) Building an Agent to Trade with Reinforcement Learning. Deep Learning And Reinforcement Learning 4/10/21 7:09 4/8/21 18:57 235 33.0 108 8.0 1 5.0 2/25/18 17:41 1/16/19 0:43 12/1/20 22:06 3/19/20 20:28 golsun/deep-RL-trading gstenger98/rl-finance active 3 2.0 3/31/21 8:00
62 FinRL-Library RL IV https://github.com/AI4Finance-LLC/FinRL-Library https://github.com/jjakimoto/DQN started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading Reinforcement Learning for finance. Deep Learning And Reinforcement Learning 4/12/21 12:45 4/5/21 11:42 1857 142.0 447 55.0 22 1.0 7/26/20 13:18 10/21/16 2:47 4/11/21 22:02 4/7/17 8:11 AI4Finance-LLC/FinRL-Library jjakimoto/DQN active inactive 5 3/31/21 8:00
63 Deep Learning tensortrade https://github.com/keon/deepstock https://github.com/tensortrade-org/tensortrade Technical experimentations to beat the stock market using deep learning. NEW Deep Learning And Reinforcement Learning 3/24/21 14:45 4/12/21 16:05 427 3101.0 154 715.0 2 39.0 12/12/16 2:15 7/30/19 21:28 3/4/17 8:37 3/24/21 16:25 keon/deepstock tensortrade-org/tensortrade inactive active 4 39:11.1
64 Personae RL III https://github.com/Ceruleanacg/Personae https://github.com/samre12/deep-trading-agent implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing Github -Deep Reinforcement Learning based Trading Agent for Bitcoin. Deep Learning And Reinforcement Learning 4/11/21 20:20 4/3/21 20:48 1144 576.0 330 203.0 2 1.0 3/10/18 11:22 9/21/17 17:05 9/2/18 17:21 4/13/18 16:33 Ceruleanacg/Personae samre12/deep-trading-agent inactive 5 3.0 3/31/21 8:00
65 Pair Trading RL Pair-Trading-Reinforcement-Learning https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading https://github.com/wai-i/Pair-Trading-Reinforcement-Learning Using deep actor-critic model to learn best strategies in pair trading. NEW Deep Learning And Reinforcement Learning 3/27/21 2:19 4/10/21 4:53 241 136.0 113 56.0 1 1.0 5/18/17 16:47 6/9/19 22:50 5/18/17 16:56 1/3/20 15:36 shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading wai-i/Pair-Trading-Reinforcement-Learning inactive active 3 39:11.1
66 Deep-Learning-Machine-Learning-Stock TradingGym https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock https://github.com/Yvictor/TradingGym curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade NEW Deep Learning And Reinforcement Learning 4/12/21 2:58 4/11/21 20:20 275 841.0 99 237.0 1 2.0 9/29/18 23:38 5/1/17 13:53 3/18/21 3:16 2/14/18 13:58 LastAncientOne/Deep-Learning-Machine-Learning-Stock Yvictor/TradingGym active inactive 3 3/31/21 8:00 39:11.1
67 Deep-Reinforcement-Learning-in-Trading BitcoinForecast https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading https://github.com/PiSimo/BitcoinForecast Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman) RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model Deep Learning And Reinforcement Learning 4/10/21 13:17 4/6/21 2:06 138 289.0 66 128.0 1 3.0 5/11/18 0:52 3/10/17 10:52 10/26/19 14:22 6/11/18 8:07 saeed349/Deep-Reinforcement-Learning-in-Trading PiSimo/BitcoinForecast active inactive 3 3.0 3/31/21 8:00
68 BitcoinForecast FinRL https://github.com/PiSimo/BitcoinForecast https://github.com/AI4Finance-LLC/FinRL RNN model to predict short term price movement (in this case BTC for the next 9 minutes) [deepchart](https://pisimo.github.io/DeepChart/) is used to visualize the model NEW Deep Learning And Reinforcement Learning 4/6/21 2:06 2021-04-13 14:37:21 289 1865.0 128 451.0 3 22.0 3/10/17 10:52 2020-07-26 13:18:16 6/11/18 8:07 2021-04-11 22:02:16 PiSimo/BitcoinForecast AI4Finance-LLC/FinRL inactive active 3 3/31/21 8:00 2021-04-13 16:13:03.716257
69 Pair-Trading-Reinforcement-Learning Deep-Learning-Machine-Learning-Stock https://github.com/wai-i/Pair-Trading-Reinforcement-Learning https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock NEW curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade Deep Learning And Reinforcement Learning 4/10/21 4:53 4/12/21 2:58 136 275.0 56 99.0 1 1.0 6/9/19 22:50 9/29/18 23:38 1/3/20 15:36 3/18/21 3:16 wai-i/Pair-Trading-Reinforcement-Learning LastAncientOne/Deep-Learning-Machine-Learning-Stock active 3.0 39:11.1 3/31/21 8:00
70 rl_trading awesome-deep-trading https://github.com/ucaiado/rl_trading https://github.com/cbailes/awesome-deep-trading NEW curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes Deep Learning And Reinforcement Learning 4/8/21 15:34 4/11/21 9:02 207 551.0 89 140.0 1 1.0 5/29/17 22:19 11/26/18 3:23 8/29/17 14:54 1/1/21 9:41 ucaiado/rl_trading cbailes/awesome-deep-trading inactive active 4.0 39:11.1 3/31/21 8:00
71 Trading-Gym Deep Learning IV https://github.com/thedimlebowski/Trading-Gym https://github.com/achillesrasquinha/bulbea NEW Bulbea: Deep Learning based Python Library. Deep Learning And Reinforcement Learning 4/10/21 8:00 4/9/21 20:38 507 1467.0 147 416.0 3 1.0 6/13/17 13:14 3/9/17 6:11 7/10/17 8:09 3/19/17 7:42 thedimlebowski/Trading-Gym achillesrasquinha/bulbea inactive 5.0 39:11.1
72 DQN-DDPG_Stock_Trading AI Trading https://github.com/AI4Finance-LLC/DQN-DDPG_Stock_Trading https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md merged into FinRL library and uses [gym](https://gym.openai.com/) and implementation of DQN AI to predict stock market movements. Deep Learning And Reinforcement Learning 4/7/21 12:42 4/12/21 15:42 136 2876.0 49 1384.0 4 1.0 9/19/18 3:17 1/9/19 8:02 11/26/20 16:58 2/11/19 16:32 AI4Finance-LLC/DQN-DDPG_Stock_Trading borisbanushev/stockpredictionai active inactive 3 5.0 3/31/21 8:00
73 pairstrade-fyp-2019 ARIMA-LTSM Hybrid https://github.com/wywongbd/pairstrade-fyp-2019 https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid NEW Hybrid model to predict future price correlation coefficients of two assets. Deep Learning And Reinforcement Learning 4/4/21 23:47 4/11/21 4:12 110 222.0 41 86.0 2 1.0 9/7/18 7:51 8/5/18 2:13 5/13/20 5:06 10/1/18 11:25 wywongbd/pairstrade-fyp-2019 imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict active inactive 3.0 39:11.1
74 Machine-Learning-and-Reinforcement-Learning-in-Finance Deep-Reinforcement-Learning-in-Trading https://github.com/joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading NEW Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article [here](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman) Deep Learning And Reinforcement Learning 3/30/21 9:11 4/10/21 13:17 175 138.0 98 66.0 1 1.0 6/26/18 4:30 5/11/18 0:52 9/23/18 16:50 10/26/19 14:22 joelowj/Machine-Learning-and-Reinforcement-Learning-in-Finance saeed349/Deep-Reinforcement-Learning-in-Trading inactive active 3.0 39:11.1 3/31/21 8:00
75 maro trading-rl https://github.com/microsoft/maro https://github.com/Kostis-S-Z/trading-rl NEW Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained Deep Learning And Reinforcement Learning 4/12/21 2:22 4/10/21 4:59 386 180.0 66 38.0 17 2.0 12/27/19 6:48 4/22/19 10:03 4/7/21 15:49 9/28/20 9:07 microsoft/maro Kostis-S-Z/trading-rl active 3.0 39:11.1 3/31/21 8:00
76 TradingGym Deep Learning III https://github.com/cove9988/TradingGym https://github.com/Rachnog/Deep-Trading NEW Algorithmic trading with deep learning experiments. Deep Learning And Reinforcement Learning 3/28/21 5:37 4/9/21 10:39 112 1266.0 39 675.0 3 1.0 11/6/17 0:50 6/18/16 18:23 11/15/17 23:55 8/7/18 15:24 cove9988/TradingGym Rachnog/Deep-Trading inactive 5.0 39:11.1
77 a3c_trading Stock-Prediction-Models https://github.com/evgps/a3c_trading https://github.com/huseinzol05/Stock-Prediction-Models NEW very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using [BERT](https://github.com/google-research/bert)) Deep Learning And Reinforcement Learning 4/10/21 12:49 4/12/21 13:54 311 3655.0 98 1542.0 1 2.0 6/4/18 15:30 12/18/17 10:49 5/23/20 14:47 1/5/21 10:31 evgps/a3c_trading huseinzol05/Stock-Prediction-Models active 5.0 39:11.1 3/31/21 8:00
78 RLQuant RLTrader https://github.com/yuriak/RLQuant https://github.com/notadamking/RLTrader NEW predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc. Deep Learning And Reinforcement Learning 4/9/21 5:01 4/12/21 2:50 277 1312.0 92 451.0 1 15.0 4/5/18 5:42 4/27/19 18:35 8/13/18 4:18 10/17/19 16:25 yuriak/RLQuant notadamking/RLTrader inactive active 5.0 39:11.1 3/31/21 8:00
79 TradingGym Neural Network https://github.com/Yvictor/TradingGym https://github.com/VivekPa/IntroNeuralNetworks NEW Neural networks to predict stock prices. Deep Learning And Reinforcement Learning 4/11/21 20:20 4/3/21 11:59 841 489.0 237 176.0 2 2.0 5/1/17 13:53 9/10/18 6:34 2/14/18 13:58 11/21/18 7:39 Yvictor/TradingGym VivekPa/IntroNeuralNetworks inactive 4.0 39:11.1
80 QLearning_Trading LTSM Recurrent https://github.com/ucaiado/QLearning_Trading https://github.com/VivekPa/AIAlpha NEW OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network. Deep Learning And Reinforcement Learning 4/6/21 22:09 4/12/21 2:39 433 1207.0 168 370.0 1 2.0 8/10/16 6:02 10/7/18 3:58 10/15/16 2:36 8/3/19 9:00 ucaiado/QLearning_Trading VivekPa/AIAlpha inactive active 4.0 39:11.1
81 gym-trading trading-bot https://github.com/hackthemarket/gym-trading https://github.com/pskrunner14/trading-bot NEW Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python Deep Learning And Reinforcement Learning 4/12/21 9:06 4/11/21 5:10 581 292.0 195 143.0 2 1.0 12/9/16 20:46 8/13/18 10:44 12/24/17 15:34 1/23/20 4:41 hackthemarket/gym-trading pskrunner14/trading-bot inactive active 3.0 39:11.1 3/31/21 8:00
82 RL II Deep Learning II https://github.com/deependersingla/deep_trader https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks reinforcement learning on stock market and agent tries to learn trading. Tensorflow Regression. Deep Learning And Reinforcement Learning 4/11/21 20:21 4/10/21 6:06 1340 175.0 489 67.0 3 1.0 6/11/16 7:27 7/12/16 12:56 1/22/18 14:35 2/16/18 2:43 deependersingla/deep_trader LiamConnell/deep-algotrading inactive 3 3.0
83 RL DeepLearningInFinance https://github.com/kh-kim/stock_market_reinforcement_learning https://github.com/sonaam1234/DeepLearningInFinance OpenGym with Deep Q-learning and Policy Gradient. Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. Deep Learning And Reinforcement Learning 4/11/21 12:27 3/8/21 13:09 715 266.0 298 145.0 1 1.0 10/4/16 14:42 8/21/17 16:00 12/23/16 7:34 8/21/17 17:23 kh-kim/stock_market_reinforcement_learning sonaam1234/DeepLearningInFinance inactive 2 3.0 3/31/21 8:00
84 RL V crypto-rl https://github.com/gstenger98/rl-finance https://github.com/sadighian/crypto-rl Building an Agent to Trade with Reinforcement Learning. Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process) Deep Learning And Reinforcement Learning 4/8/21 18:57 4/12/21 10:24 33 347.0 8 111.0 5 1.0 1/16/19 0:43 6/21/18 1:06 3/19/20 20:28 11/5/20 11:08 gstenger98/rl-finance sadighian/crypto-rl active 2 3.0 3/31/21 8:00
85 RL Trading Deep-Reinforcement-Stock-Trading https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW https://github.com/Albert-Z-Guo/Deep-Reinforcement-Stock-Trading A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab. inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses [empyrical](https://github.com/quantopian/empyrical) for portfolio stats Deep Learning And Reinforcement Learning 4/3/21 22:50 141.0 42.0 2.0 5/19/19 22:20 9/27/20 19:22 Albert-Z-Guo/Deep-Reinforcement-Stock-Trading active 4 3.0 3/31/21 8:00
86 RL IV Advanced-Deep-Trading https://github.com/jjakimoto/DQN https://github.com/Rachnog/Advanced-Deep-Trading Reinforcement Learning for finance. notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. Deep Learning And Reinforcement Learning 4/5/21 11:42 3/30/21 7:29 142 319.0 55 158.0 1 2.0 10/21/16 2:47 2/16/19 21:18 4/7/17 8:11 11/29/20 20:12 jjakimoto/DQN Rachnog/Advanced-Deep-Trading inactive active 3.0 3/31/21 8:00
87 tensortrade Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 https://github.com/tensortrade-org/tensortrade https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 NEW Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble. Deep Learning And Reinforcement Learning 4/12/21 16:05 4/12/21 16:24 3101 560.0 715 249.0 39 6.0 7/30/19 21:28 7/26/20 13:12 3/24/21 16:25 1/21/21 18:11 tensortrade-org/tensortrade AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 active 4.0 39:11.1 3/31/21 8:00
88 RL III AutomatedStockTrading-DeepQ-Learning https://github.com/samre12/deep-trading-agent https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning Github -Deep Reinforcement Learning based Trading Agent for Bitcoin. cornerstone project repo for Udacity nanodegree program [Become a machine learning engineer](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t) and focus on trading using deep q learning. Good explanation on design choices in the report Deep Learning And Reinforcement Learning 4/3/21 20:48 3/24/21 1:11 576 134.0 203 51.0 1 2.0 9/21/17 17:05 2/23/19 12:01 4/13/18 16:33 2/25/20 18:16 samre12/deep-trading-agent sachink2010/AutomatedStockTrading-DeepQ-Learning inactive active 3 3.0 3/31/21 8:00
89 Options Risk Measures deep-RL-trading https://github.com/wanglouis49/risk_estimation https://github.com/golsun/deep-RL-trading Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling). trading game comparing RNN vs CNN vs MLP based on [paper](https://arxiv.org/abs/1803.03916) Derivatives and Hedging Deep Learning And Reinforcement Learning 10/6/20 20:37 4/10/21 7:09 1 235.0 2 108.0 1 1.0 4/29/16 3:51 2/25/18 17:41 1/16/18 1:24 12/1/20 22:06 wanglouis49/risk_estimation golsun/deep-RL-trading inactive active 3.0 3/31/21 8:00
90 Option Strategies FinRL-Library https://github.com/rstreppa/valuation-OptionStrategies https://github.com/AI4Finance-LLC/FinRL-Library Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations. started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading Derivatives and Hedging Deep Learning And Reinforcement Learning 2/27/21 8:50 4/12/21 12:45 2 1857.0 3 447.0 1 22.0 5/22/18 18:27 7/26/20 13:18 5/22/18 18:30 4/11/21 22:02 rstreppa/valuation-OptionStrategies AI4Finance-LLC/FinRL-Library inactive active 5.0 3/31/21 8:00
91 Black Scholes Deep Learning https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb https://github.com/keon/deepstock Options pricing. Technical experimentations to beat the stock market using deep learning. Derivatives and Hedging Deep Learning And Reinforcement Learning 10/6/20 20:36 3/24/21 14:45 1 427.0 2 154.0 0 2.0 12/9/17 18:50 12/12/16 2:15 7/9/18 9:48 3/4/17 8:37 irajwani/numerical_methods_python keon/deepstock inactive 4.0
92 Computational Derivatives Personae https://github.com/chenbowen184/Computational_Finance https://github.com/Ceruleanacg/Personae Projects focusing on investigating simulations and computational techniques applied in finance. implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing Derivatives and Hedging Deep Learning And Reinforcement Learning 1/12/21 12:22 4/11/21 20:20 17 1144.0 12 330.0 1 2.0 1/29/18 5:01 3/10/18 11:22 8/2/18 5:56 9/2/18 17:21 chen-bowen/Computational_Finance Ceruleanacg/Personae inactive 5.0 3/31/21 8:00
93 Delta Hedging Pair Trading RL https://github.com/RobinsonGarcia/delta-hedging https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading Advanced derivatives. Using deep actor-critic model to learn best strategies in pair trading. Derivatives and Hedging Deep Learning And Reinforcement Learning 2/27/21 8:48 3/27/21 2:19 3 241.0 2 113.0 1 1.0 3/2/18 23:53 5/18/17 16:47 7/17/18 23:32 5/18/17 16:56 RobinsonGarcia/delta-hedging shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading inactive 3.0
94 Derivatives Python LTSM GRU https://github.com/yhilpisch/dawp/tree/master/python36 https://github.com/RajatHanda/Finance-Forecasting Derivative analytics with Python. Stock Market Forecasting using LSTM\GRU. Derivatives and Hedging Deep Learning And Reinforcement Learning 4/12/21 14:39 3/29/21 23:59 388 11.0 299 6.0 1 1.0 7/9/15 12:27 5/13/18 2:39 2/22/21 13:29 2/25/19 0:26 yhilpisch/dawp RajatHanda/Finance-Forecasting active inactive 3.0
95 Derman Hull White https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb Binomial tree for American call. Callable Bond, Hull White. Derivatives and Hedging 10/6/20 20:37 1 4.0 3 6.0 1 1.0 5/18/18 18:08 6/6/18 22:06 9/21/18 19:59 6/6/18 22:27 rstreppa/valuation-convertibles-Goldman1994 rstreppa/valuation-callables-HullWhite inactive
96 Reinforcement Learning Options https://github.com/FinTechies/HedgingRL https://github.com/PHBS/2018.M1.ASP/tree/master/py Hedging portfolios with reinforcement learning. Black Scholes and Copula. Derivatives and Hedging 1/20/21 8:12 16 9 1 4/21/17 10:58 8/2/17 21:41 FinTechies/HedgingRL PHBS/2018.M1.ASP inactive
97 Volatility and Variance Derivatives Derivative Markets https://github.com/yhilpisch/lvvd/tree/master/lvvd https://github.com/broughtj/Fin6470/tree/master/Notebooks Volatility derivatives analytics. The economics of futures, futures, options, and swaps. Derivatives and Hedging 4/7/21 19:21 4/6/21 20:49 79 8.0 78 8.0 1 1.0 10/21/16 4:12 2/9/16 5:30 2/22/21 13:32 4/6/21 20:49 yhilpisch/lvvd broughtj/Fin6470 active
98 Options Computational Derivatives https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D https://github.com/chenbowen184/Computational_Finance Introduction to options. Projects focusing on investigating simulations and computational techniques applied in finance. Derivatives and Hedging 4/9/21 21:17 1/12/21 12:22 335 17.0 163 12.0 36 1.0 7/28/17 15:48 1/29/18 5:01 3/17/21 17:17 8/2/18 5:56 QuantConnect/Tutorials chen-bowen/Computational_Finance active inactive
99 Derivative Markets Volatility and Variance Derivatives https://github.com/broughtj/Fin6470/tree/master/Notebooks https://github.com/yhilpisch/lvvd/tree/master/lvvd The economics of futures, futures, options, and swaps. Volatility derivatives analytics. Derivatives and Hedging 4/6/21 20:49 4/7/21 19:21 8 79.0 8 78.0 1 1.0 2/9/16 5:30 10/21/16 4:12 4/6/21 20:49 2/22/21 13:32 broughtj/Fin6470 yhilpisch/lvvd active
100 Hull White Options https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D Callable Bond, Hull White. Introduction to options. Derivatives and Hedging 10/6/20 20:37 4/9/21 21:17 4 335.0 6 163.0 1 36.0 6/6/18 22:06 7/28/17 15:48 6/6/18 22:27 3/17/21 17:17 rstreppa/valuation-callables-HullWhite QuantConnect/Tutorials inactive active
101 Options Option Strategies https://github.com/PHBS/2018.M1.ASP/tree/master/py https://github.com/rstreppa/valuation-OptionStrategies Black Scholes and Copula. Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations. Derivatives and Hedging 2/27/21 8:50 2.0 3.0 1.0 5/22/18 18:27 5/22/18 18:30 PHBS/2018.M1.ASP rstreppa/valuation-OptionStrategies inactive
102 Mathematical Finance Black Scholes https://github.com/Auquan/Tutorials https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb Notebooks for math and financial tutorials. Options pricing. Extended Research Derivatives and Hedging 4/8/21 19:37 10/6/20 20:36 664 1.0 425 2.0 9 0.0 1/21/17 11:24 12/9/17 18:50 8/1/20 17:03 7/9/18 9:48 Auquan/Tutorials irajwani/numerical_methods_python active inactive
103 Economic Foundations Options Risk Measures https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations https://github.com/wanglouis49/risk_estimation Basic economic models. Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling). Extended Research Derivatives and Hedging 10/6/20 21:01 10/6/20 20:37 2 1.0 3 2.0 1 1.0 5/25/17 2:27 4/29/16 3:51 6/30/17 3:53 1/16/18 1:24 SeanMcOwen/FinanceAndPython.com-EconomicFoundations wanglouis49/risk_estimation inactive
104 Financial Economics Derivatives Python https://github.com/rsvp/fecon235/tree/master/nb https://github.com/yhilpisch/dawp/tree/master/python36 Financial Economics Models. Derivative analytics with Python. Extended Research Derivatives and Hedging 4/10/21 17:02 4/12/21 14:39 713 388.0 275 299.0 2 1.0 11/9/14 4:49 7/9/15 12:27 12/3/18 16:30 2/22/21 13:29 rsvp/fecon235 yhilpisch/dawp inactive active
105 Finance Graph Theory Derman https://github.com/AvijitGhosh82/Finance_Graph_Theory https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents. Binomial tree for American call. Extended Research Derivatives and Hedging 3/28/21 2:22 10/6/20 20:37 17 1.0 7 3.0 3 1.0 8/2/18 2:48 5/18/18 18:08 3/16/19 18:39 9/21/18 19:59 evijit/Finance_Graph_Theory rstreppa/valuation-convertibles-Goldman1994 inactive
106 Market Crash Prediction Reinforcement Learning https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb https://github.com/FinTechies/HedgingRL Predicting market crashes using an LPPL model. Hedging portfolios with reinforcement learning. Extended Research Derivatives and Hedging 10/6/20 21:01 1/20/21 8:12 1 16.0 3 9.0 1 1.0 1/24/19 13:37 4/21/17 10:58 2/13/19 16:48 8/2/17 21:41 sarachmax/MarketCrashes_Prediction FinTechies/HedgingRL inactive
107 Life-cycle Delta Hedging https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb https://github.com/RobinsonGarcia/delta-hedging Company life cycle. Advanced derivatives. Extended Research Derivatives and Hedging 12/21/20 14:42 2/27/21 8:48 3 3.0 3 2.0 1 1.0 1/19/19 18:16 3/2/18 23:53 2/18/19 16:57 7/17/18 23:32 atulram/Finance-and-Stocks RobinsonGarcia/delta-hedging inactive
108 Behavioural Economics Currency PCA https://github.com/pcmichaud/notebooks https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb Behavioural Economics and Finance Python Notebooks. Forex spots PCA. Extended Research 2/3/21 7:22 10/26/20 0:55 9 3.0 4 1.0 1 1.0 12/20/18 0:21 3/12/19 21:11 3/26/19 11:51 3/12/19 22:09 pcmichaud/notebooks shanemulqueen/python-finance-pca inactive
109 Applied Corporate Finance Simulation https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance https://github.com/chenbowen184/Computational_Finance Studies the empirical behaviours in stock market. Investigating simulations as part of computational finance. Extended Research 2/19/21 13:40 1/12/21 12:22 8 17.0 9 12.0 1 1.0 1/29/18 5:14 1/29/18 5:01 7/19/18 6:25 8/2/18 5:56 chen-bowen/Data_Science_in_Applied_Corporate_Finance chen-bowen/Computational_Finance inactive
110 HFT Critical Transitions https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy https://github.com/ryanholbrook/critical-transitions High frequency trading. Detecting critical transitions in financial networks with topological data analysis. Extended Research 4/11/21 23:36 1/30/21 11:50 748 10.0 333 3.0 1 1.0 7/21/16 5:14 1/22/19 10:59 2/14/17 16:47 3/12/19 18:35 rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy ryanholbrook/critical-transitions inactive
111 Corporate Finance Real Estate Property Fraud https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance https://github.com/aviroop1/Real_Estate_Property_Fraud Basic corporate finance. Unsupervised fraud detection model that can identify likely candidates of fraud. Extended Research 1/16/21 19:01 9 4 1 9/9/17 3:35 9/9/17 23:04 SeanMcOwen/FinanceAndPython.com-CorporateFinance aviroop1/Real_Estate_Property_Fraud inactive
112 M&A Deep Portfolio https://github.com/atulram/Finance-and-Stocks https://github.com/DLColumbia/DL_forFinance Mergers and Acquisitions. Deep learning for finance Predict volume of bonds. Extended Research 12/21/20 14:42 1/12/21 11:48 3 27.0 3 19.0 1 2.0 1/19/19 18:16 5/8/18 19:34 2/18/19 16:57 5/9/18 15:39 atulram/Finance-and-Stocks DLColumbia/DL_forFinance inactive
113 Backtests NLP Finance Papers https://github.com/AlgoTraders/stock-analysis-engine https://github.com/chenbowen184/Research_Documents_Curation_with_NLP Trading data and algorithms. Curating quantitative finance papers using machine learning. Extended Research 4/12/21 2:28 2/27/21 6:33 620 8.0 165 9.0 3 1.0 9/16/18 20:00 10/11/18 20:32 9/5/20 13:01 12/24/18 23:27 AlgoTraders/stock-analysis-engine chen-bowen/Research_Documents_Curation_with_NLP active inactive
114 Bayesian Finance I Bayesian Finance https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs. Notebook PyMC3 implementation. Extended Research 11/28/20 3:02 4/10/21 19:50 25 233.0 6 55.0 0 1.0 1/4/19 12:30 8/28/18 14:45 2/18/19 9:55 8/6/20 22:03 AlexIoannides/pymc-stochastic-process marketneutral/alphatools inactive active
115 Computational Finance Liquidity and Momentum https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance https://github.com/mrefermat/quant_finance Applied Computational Economics and Finance. Various factors and portfolio constructions. Extended Research 3/7/21 17:47 3/30/21 0:09 12 31.0 13 15.0 1 1.0 8/27/17 3:46 8/11/18 22:59 8/26/17 4:26 11/12/19 4:49 lnsongxf/Applied_Computational_Economics_and_Finance mrefermat/quant_finance inactive active
116 Commodity High Frequency https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb https://github.com/cswaney/prickle Commodity influence over Brazilian stocks. A Python toolkit for high-frequency trade research. Extended Research 3/22/21 2:19 24.0 17.0 2.0 7/6/16 20:32 6/9/18 10:53 felipessalvatore/fin2vec cswaney/prickle inactive
117 High Frequency Life-cycle https://github.com/cswaney/prickle https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb A Python toolkit for high-frequency trade research. Company life cycle. Extended Research 3/22/21 2:19 12/21/20 14:42 24 3.0 17 3.0 2 1.0 7/6/16 20:32 1/19/19 18:16 6/9/18 10:53 2/18/19 16:57 cswaney/prickle atulram/Finance-and-Stocks inactive
118 Currency PCA Computational Finance https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance Forex spots PCA. Applied Computational Economics and Finance. Extended Research 10/26/20 0:55 3/7/21 17:47 3 12.0 1 13.0 1 1.0 3/12/19 21:11 8/27/17 3:46 3/12/19 22:09 8/26/17 4:26 shanemulqueen/python-finance-pca lnsongxf/Applied_Computational_Economics_and_Finance inactive
119 Liquidity and Momentum Market Crash Prediction https://github.com/mrefermat/quant_finance https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb Various factors and portfolio constructions. Predicting market crashes using an LPPL model. Extended Research 3/30/21 0:09 10/6/20 21:01 31 1.0 15 3.0 1 1.0 8/11/18 22:59 1/24/19 13:37 11/12/19 4:49 2/13/19 16:48 mrefermat/quant_finance sarachmax/MarketCrashes_Prediction active inactive
120 Bayesian Finance Commodity https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb Notebook PyMC3 implementation. Commodity influence over Brazilian stocks. Extended Research 4/10/21 19:50 233 55 1 8/28/18 14:45 8/6/20 22:03 marketneutral/alphatools felipessalvatore/fin2vec active
121 NLP Finance Papers Finance Graph Theory https://github.com/chenbowen184/Research_Documents_Curation_with_NLP https://github.com/AvijitGhosh82/Finance_Graph_Theory Curating quantitative finance papers using machine learning. Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents. Extended Research 2/27/21 6:33 3/28/21 2:22 8 17.0 9 7.0 1 3.0 10/11/18 20:32 8/2/18 2:48 12/24/18 23:27 3/16/19 18:39 chen-bowen/Research_Documents_Curation_with_NLP evijit/Finance_Graph_Theory inactive
122 Deep Portfolio Financial Economics https://github.com/DLColumbia/DL_forFinance https://github.com/rsvp/fecon235/tree/master/nb Deep learning for finance Predict volume of bonds. Financial Economics Models. Extended Research 1/12/21 11:48 4/10/21 17:02 27 713.0 19 275.0 2 2.0 5/8/18 19:34 11/9/14 4:49 5/9/18 15:39 12/3/18 16:30 DLColumbia/DL_forFinance rsvp/fecon235 inactive
123 Real Estate Property Fraud Economic Foundations https://github.com/aviroop1/Real_Estate_Property_Fraud https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations Unsupervised fraud detection model that can identify likely candidates of fraud. Basic economic models. Extended Research 10/6/20 21:01 2.0 3.0 1.0 5/25/17 2:27 6/30/17 3:53 aviroop1/Real_Estate_Property_Fraud SeanMcOwen/FinanceAndPython.com-EconomicFoundations inactive
124 Critical Transitions Behavioural Economics https://github.com/ryanholbrook/critical-transitions https://github.com/pcmichaud/notebooks Detecting critical transitions in financial networks with topological data analysis. Behavioural Economics and Finance Python Notebooks. Extended Research 1/30/21 11:50 2/3/21 7:22 10 9.0 3 4.0 1 1.0 1/22/19 10:59 12/20/18 0:21 3/12/19 18:35 3/26/19 11:51 ryanholbrook/critical-transitions pcmichaud/notebooks inactive
125 Simulation Mathematical Finance https://github.com/chenbowen184/Computational_Finance https://github.com/Auquan/Tutorials Investigating simulations as part of computational finance. Notebooks for math and financial tutorials. Extended Research 1/12/21 12:22 4/8/21 19:37 17 664.0 12 425.0 1 9.0 1/29/18 5:01 1/21/17 11:24 8/2/18 5:56 8/1/20 17:03 chen-bowen/Computational_Finance Auquan/Tutorials inactive active
126 Risk and Return HFT https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy Riskiness of portfolios and assets. High frequency trading. Factor and Risk Analysis Extended Research 4/6/21 17:03 4/11/21 23:36 140 748.0 62 333.0 2 1.0 9/12/17 13:35 7/21/16 5:14 8/6/20 12:35 2/14/17 16:47 PyDataBlog/Python-for-Data-Science rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy active inactive
127 Stock-Prediction Corporate Finance https://github.com/Ronak-59/Stock-Prediction https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance NEW Basic corporate finance. Factor and Risk Analysis Extended Research 3/26/21 8:37 1/16/21 19:01 129 9.0 64 4.0 2 1.0 3/18/18 4:54 9/9/17 3:35 2/28/20 11:43 9/9/17 23:04 Ronak-59/Stock-Prediction SeanMcOwen/FinanceAndPython.com-CorporateFinance active inactive 37:06.3
128 Quant Finance M&A https://github.com/mrefermat/quant_finance https://github.com/atulram/Finance-and-Stocks General quant repository. Mergers and Acquisitions. Factor and Risk Analysis Extended Research 3/30/21 0:09 12/21/20 14:42 31 3.0 15 3.0 1 1.0 8/11/18 22:59 1/19/19 18:16 11/12/19 4:49 2/18/19 16:57 mrefermat/quant_finance atulram/Finance-and-Stocks active inactive
129 CAPM Backtests https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb https://github.com/AlgoTraders/stock-analysis-engine Expected returns using CAPM. Trading data and algorithms. Factor and Risk Analysis Extended Research 3/1/21 13:53 4/12/21 2:28 31 620.0 18 165.0 1 3.0 5/10/16 11:03 9/16/18 20:00 5/17/16 3:44 9/5/20 13:01 RJT1990/Active-Portfolio-Management-Notes AlgoTraders/stock-analysis-engine inactive active
130 Various Risk Measures Bayesian Finance I https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb Risk measures and factors for alternative and responsible investments. Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs. Factor and Risk Analysis Extended Research 11/4/20 7:04 11/28/20 3:02 4 25.0 5 6.0 1 0.0 8/7/17 14:44 1/4/19 12:30 8/8/17 22:52 2/18/19 9:55 Jorgencr/Alternative-and-Responsible-Investments AlexIoannides/pymc-stochastic-process inactive
131 Risk Basic Applied Corporate Finance https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance Active portfolio risk management . Studies the empirical behaviours in stock market. Factor and Risk Analysis Extended Research 3/1/21 13:53 2/19/21 13:40 31 8.0 18 9.0 1 1.0 5/10/16 11:03 1/29/18 5:14 5/17/16 3:44 7/19/18 6:25 RJT1990/Active-Portfolio-Management-Notes chen-bowen/Data_Science_in_Applied_Corporate_Finance inactive
132 VaR Pyfolio https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb https://github.com/quantopian/pyfolio Value-at-risk calculations. Portfolio and risk analytics in Python. Factor and Risk Analysis 3/31/21 2:06 4/12/21 11:55 10 3673.0 9 1157.0 1 42.0 11/15/16 19:24 6/1/15 15:31 1/14/17 21:19 2/28/20 17:30 willb/var-notebook quantopian/pyfolio inactive active
133 Factor Analysis Statistical Finance https://github.com/alpha-miner/alpha-mind/tree/master/notebooks https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments Factor strategy notebooks. Various financial experiments. Factor and Risk Analysis 4/8/21 19:02 3/30/21 0:09 172 21.0 60 16.0 3 1.0 5/1/17 7:36 10/4/15 9:10 4/7/21 15:25 3/28/20 18:33 alpha-miner/alpha-mind mrefermat/FinancePhD active
134 Convex Optimisation VaR GaN https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb https://github.com/hamaadshah/market_risk_gan_keras Convex Optimization for Finance. Estimate Value-at-Risk for market risk management using Keras and TensorFlow. Factor and Risk Analysis 4/8/21 19:02 3/20/21 21:53 18 41.0 10 28.0 1 1.0 6/26/18 20:36 8/6/18 16:09 10/22/19 21:56 11/22/20 19:02 ssanderson/convex-optimization-for-finance hamaadshah/market_risk_gan_tensorflow active
135 Python for Finance Performance Analysis https://github.com/yhilpisch/py4fi/tree/master/jupyter36 https://github.com/quantopian/alphalens Various financial notebooks. Performance analysis of predictive (alpha) stock factors. Factor and Risk Analysis 4/9/21 8:12 4/10/21 12:58 1298 1847.0 794 700.0 1 17.0 12/15/14 11:23 6/3/16 21:49 7/10/18 6:38 4/27/20 18:40 yhilpisch/py4fi quantopian/alphalens inactive active
136 AlphaTrading Factor Analysis https://github.com/jerryxyx/AlphaTrading https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb NEW Factor analysis for mutual funds. Factor and Risk Analysis 4/10/21 6:34 12/21/20 14:26 149 3.0 74 4.0 1 1.0 5/18/18 22:09 3/13/18 7:39 8/7/18 18:05 3/13/18 7:42 jerryxyx/AlphaTrading garvit-kudesia91/factor_analysis inactive 37:06.3
137 Performance Analysis Python for Finance https://github.com/quantopian/alphalens https://github.com/yhilpisch/py4fi/tree/master/jupyter36 Performance analysis of predictive (alpha) stock factors. Various financial notebooks. Factor and Risk Analysis 4/10/21 12:58 4/9/21 8:12 1847 1298.0 700 794.0 17 1.0 6/3/16 21:49 12/15/14 11:23 4/27/20 18:40 7/10/18 6:38 quantopian/alphalens yhilpisch/py4fi active inactive
138 Pyfolio Various Risk Measures https://github.com/quantopian/pyfolio https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb Portfolio and risk analytics in Python. Risk measures and factors for alternative and responsible investments. Factor and Risk Analysis 4/12/21 11:55 11/4/20 7:04 3673 4.0 1157 5.0 42 1.0 6/1/15 15:31 8/7/17 14:44 2/28/20 17:30 8/8/17 22:52 quantopian/pyfolio Jorgencr/Alternative-and-Responsible-Investments active inactive
139 VaR GaN CAPM https://github.com/hamaadshah/market_risk_gan_keras https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb Estimate Value-at-Risk for market risk management using Keras and TensorFlow. Expected returns using CAPM. Factor and Risk Analysis 3/20/21 21:53 3/1/21 13:53 41 31.0 28 18.0 1 1.0 8/6/18 16:09 5/10/16 11:03 11/22/20 19:02 5/17/16 3:44 hamaadshah/market_risk_gan_tensorflow RJT1990/Active-Portfolio-Management-Notes active inactive
140 Factor Analysis Quant Finance https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb https://github.com/mrefermat/quant_finance Factor analysis for mutual funds. General quant repository. Factor and Risk Analysis 12/21/20 14:26 3/30/21 0:09 3 31.0 4 15.0 1 1.0 3/13/18 7:39 8/11/18 22:59 3/13/18 7:42 11/12/19 4:49 garvit-kudesia91/factor_analysis mrefermat/quant_finance inactive active
141 Statistical Finance Stock-Prediction https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments https://github.com/Ronak-59/Stock-Prediction Various financial experiments. NEW Factor and Risk Analysis 3/30/21 0:09 3/26/21 8:37 21 129.0 16 64.0 1 2.0 10/4/15 9:10 3/18/18 4:54 3/28/20 18:33 2/28/20 11:43 mrefermat/FinancePhD Ronak-59/Stock-Prediction active 37:06.3
142 Vasicek Risk and Return https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials Bootstrapping and interpolation. Riskiness of portfolios and assets. Fixed Income Factor and Risk Analysis 12/10/20 21:20 4/6/21 17:03 3 140.0 3 62.0 1 2.0 7/18/18 19:26 9/12/17 13:35 7/18/18 19:34 8/6/20 12:35 RobinsonGarcia/fixed-income PyDataBlog/Python-for-Data-Science inactive active
143 Corporate Bonds AlphaTrading https://github.com/ishank011/gs-quantify-bond-prediction https://github.com/jerryxyx/AlphaTrading Predicting the buying and selling volume of the corporate bonds. NEW Fixed Income Factor and Risk Analysis 1/3/21 21:46 4/10/21 6:34 7 149.0 5 74.0 1 1.0 9/27/17 19:57 5/18/18 22:09 9/27/17 20:00 8/7/18 18:05 ishank011/gs-quantify-bond-prediction jerryxyx/AlphaTrading inactive 37:06.3
144 Binomial Tree Risk Basic https://github.com/hy-lei/math-finance-exercise https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb Utility functions in fixed income securities. Active portfolio risk management . Fixed Income Factor and Risk Analysis 10/6/20 20:55 3/1/21 13:53 1 31.0 2 18.0 1 1.0 2/2/19 8:44 5/10/16 11:03 5/3/19 17:16 5/17/16 3:44 hy-lei/math-finance-toolbox RJT1990/Active-Portfolio-Management-Notes active inactive
145 Hands-On-Machine-Learning-for-Algorithmic-Trading VaR https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have Value-at-risk calculations. Other Models Factor and Risk Analysis 4/12/21 15:41 3/31/21 2:06 600 10.0 386 9.0 2 1.0 5/7/19 11:04 11/15/16 19:24 1/19/21 7:51 1/14/17 21:19 PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading willb/var-notebook active inactive 5 39:24.6
146 CryptoBot Factor Analysis https://github.com/AdeelMufti/CryptoBot https://github.com/alpha-miner/alpha-mind/tree/master/notebooks Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained Factor strategy notebooks. Other Models Factor and Risk Analysis 3/25/21 9:17 4/8/21 19:02 234 172.0 94 60.0 1 3.0 1/17/17 12:44 5/1/17 7:36 1/17/17 12:48 4/7/21 15:25 AdeelMufti/CryptoBot alpha-miner/alpha-mind inactive active 2 39:24.6
147 MathAndScienceNotes Convex Optimisation https://github.com/melling/MathAndScienceNotes https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/) Convex Optimization for Finance. Other Models Factor and Risk Analysis 4/12/21 0:49 4/8/21 19:02 460 18.0 54 10.0 1 1.0 3/11/16 19:13 6/26/18 20:36 12/21/20 3:54 10/22/19 21:56 melling/MathAndScienceNotes ssanderson/convex-optimization-for-finance active 39:24.6
148 fin-ml Binomial Tree https://github.com/tatsath/fin-ml https://github.com/hy-lei/math-finance-exercise NEW Utility functions in fixed income securities. Other Models Fixed Income 4/11/21 3:29 10/6/20 20:55 116 1.0 66 2.0 2 1.0 5/10/20 0:25 2/2/19 8:44 1/23/21 17:15 5/3/19 17:16 tatsath/fin-ml hy-lei/math-finance-toolbox active 39:24.6
149 Trend Following Vasicek http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb A futures trend following portfolio investment strategy. Bootstrapping and interpolation. Other Models Fixed Income 12/10/20 21:20 3.0 3.0 1.0 7/18/18 19:26 7/18/18 19:34 RobinsonGarcia/fixed-income inactive
150 Short-Term Movement Cues Corporate Bonds https://github.com/anfederico/Clairvoyant https://github.com/ishank011/gs-quantify-bond-prediction Identify social/historical cues for short term stock movement. Predicting the buying and selling volume of the corporate bonds. Other Models Fixed Income 4/12/21 13:11 1/3/21 21:46 2166 7.0 678 5.0 1 1.0 9/12/16 18:38 9/27/17 19:57 8/29/18 20:27 9/27/17 20:00 anfederico/clairvoyant ishank011/gs-quantify-bond-prediction inactive
151 Mixture Models II AlphaPy https://github.com/BlackArbsCEO/mixture_model_trading_public https://github.com/ScottfreeLLC/AlphaPy Mixture models and stock trading. NEW Other Models 3/12/21 13:21 4/4/21 20:02 166 576.0 73 130.0 1 3.0 12/11/17 17:05 2/14/16 0:47 5/13/20 23:50 2/8/21 21:35 BlackArbsCEO/mixture_model_trading_public ScottfreeLLC/AlphaPy active 39:24.6
152 Fundamental LT Forecasts Awesome-Quant-Machine-Learning-Trading https://github.com/Hvass-Labs/FinanceOps https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading Research in investment finance for long term forecasts. NEW Other Models 4/5/21 23:36 4/10/21 13:38 383 1005.0 127 319.0 1 3.0 7/22/18 8:14 11/5/18 21:09 2/17/21 14:39 10/8/20 16:48 Hvass-Labs/FinanceOps grananqvist/Awesome-Quant-Machine-Learning-Trading active 39:24.6
153 Scikit-learn Stock Prediction botflow https://github.com/robertmartin8/MachineLearningStocks https://github.com/kkyon/botflow Using python and scikit-learn to make stock predictions. NEW Other Models 4/11/21 10:00 3/31/21 10:56 931 1165.0 347 102.0 2 8.0 2/12/17 4:50 8/20/18 3:13 2/4/21 3:48 5/23/19 14:40 robertmartin8/MachineLearningStocks kkyon/botflow active 39:24.6
154 Speculator surpriver https://github.com/amicks/Speculator https://github.com/tradytics/surpriver NEW Other Models 3/15/21 16:27 4/12/21 12:27 101 1189.0 31 221.0 2 6.0 9/3/17 17:43 8/30/20 7:56 9/12/18 18:58 9/21/20 4:32 amicks/Speculator tradytics/surpriver inactive active 39:24.6
155 Machine-Learning-and-AI-in-Trading Pattern-Recognition-for-Forex-Trading https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading https://github.com/PythonProgramming/Pattern-Recognition-for-Forex-Trading NEW Other Models 4/8/21 11:31 4/5/21 3:23 261 173.0 101 91.0 1 1.0 8/30/17 6:14 3/26/15 2:22 10/29/19 8:14 3/26/15 2:33 PyPatel/Machine-Learning-and-AI-in-Trading PythonProgramming/Pattern-Recognition-for-Forex-Trading active inactive 39:24.6
156 Mixture Models I awesome-ai-in-finance https://github.com/BlackArbsCEO/Mixture_Models https://github.com/georgezouq/awesome-ai-in-finance Mixture models to predict market bottoms. NEW Other Models 3/2/21 19:44 4/11/21 7:43 31 941.0 31 162.0 1 8.0 3/20/17 18:54 8/29/18 2:07 4/25/17 23:35 11/27/20 9:43 BlackArbsCEO/Mixture_Models georgezouq/awesome-ai-in-finance inactive active 39:24.6
157 stock-trading-ml Microservices-Based-Algorithmic-Trading-System https://github.com/yacoubb/stock-trading-ml https://github.com/saeed349/Microservices-Based-Algorithmic-Trading-System NEW Other Models 4/11/21 14:46 4/10/21 12:59 340 104.0 186 56.0 1 0.0 10/10/19 9:44 1/6/20 0:21 10/12/19 11:38 3/31/20 13:02 yacoubb/stock-trading-ml saeed349/Microservices-Based-Algorithmic-Trading-System active 39:24.6
158 Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original Machine-Learning-for-Algorithmic-Trading-Bots-with-Python https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python NEW Other Models 4/8/21 20:01 4/11/21 6:02 279 172.0 126 94.0 4 5.0 11/15/19 8:51 12/6/18 11:35 1/21/21 7:56 1/18/21 6:40 PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python active 39:24.6
159 mosquito Stock.Indicators https://github.com/miro-ka/mosquito https://github.com/DaveSkender/Stock.Indicators NEW Other Models 4/12/21 9:44 4/12/21 10:47 220 175.0 44 64.0 2 9.0 6/18/17 19:57 12/29/19 5:18 3/14/21 22:22 4/11/21 19:17 miro-ka/mosquito DaveSkender/Stock.Indicators active 39:24.6
160 Machine-Learning-for-Finance finance_ml https://github.com/PacktPublishing/Machine-Learning-for-Finance https://github.com/jjakimoto/finance_ml NEW Other Models 4/8/21 16:54 4/8/21 15:28 180 282.0 122 117.0 4 1.0 3/15/18 6:28 6/29/18 21:21 1/14/21 15:58 2/18/19 12:34 PacktPublishing/Machine-Learning-for-Finance jjakimoto/finance_ml active inactive 39:24.6
161 ML_Finance_Codes Machine-Learning-For-Finance https://github.com/mfrdixon/ML_Finance_Codes https://github.com/anthonyng2/Machine-Learning-For-Finance NEW Other Models 4/11/21 8:30 4/1/21 20:11 250 205.0 104 119.0 3 1.0 9/27/19 16:13 7/11/17 9:09 6/13/20 21:20 2/21/18 5:36 mfrdixon/ML_Finance_Codes anthonyng2/Machine-Learning-For-Finance active inactive 39:24.6
162 Machine-Learning-For-Finance mlfinlab https://github.com/anthonyng2/Machine-Learning-For-Finance https://github.com/hudson-and-thames/mlfinlab NEW Other Models 4/1/21 20:11 4/12/21 10:51 205 2295.0 119 709.0 1 3.0 7/11/17 9:09 2/13/19 16:57 2/21/18 5:36 4/12/21 10:50 anthonyng2/Machine-Learning-For-Finance hudson-and-thames/mlfinlab inactive active 39:24.6
163 Stock.Indicators Machine-Learning-for-Finance https://github.com/DaveSkender/Stock.Indicators https://github.com/PacktPublishing/Machine-Learning-for-Finance NEW Other Models 4/12/21 10:47 4/8/21 16:54 175 180.0 64 122.0 9 4.0 12/29/19 5:18 3/15/18 6:28 4/11/21 19:17 1/14/21 15:58 DaveSkender/Stock.Indicators PacktPublishing/Machine-Learning-for-Finance active 39:24.6
164 AlphaPy MathAndScienceNotes https://github.com/ScottfreeLLC/AlphaPy https://github.com/melling/MathAndScienceNotes NEW Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/) Other Models 4/4/21 20:02 4/12/21 0:49 576 460.0 130 54.0 3 1.0 2/14/16 0:47 3/11/16 19:13 2/8/21 21:35 12/21/20 3:54 ScottfreeLLC/AlphaPy melling/MathAndScienceNotes active 39:24.6
165 mlfinlab CryptoBot https://github.com/hudson-and-thames/mlfinlab https://github.com/AdeelMufti/CryptoBot NEW Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained Other Models 4/12/21 10:51 3/25/21 9:17 2295 234.0 709 94.0 3 1.0 2/13/19 16:57 1/17/17 12:44 4/12/21 10:50 1/17/17 12:48 hudson-and-thames/mlfinlab AdeelMufti/CryptoBot active inactive 2.0 39:24.6
166 Awesome-Quant-Machine-Learning-Trading Hands-On-Machine-Learning-for-Algorithmic-Trading https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading NEW repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have Other Models 4/10/21 13:38 4/12/21 15:41 1005 600.0 319 386.0 3 2.0 11/5/18 21:09 5/7/19 11:04 10/8/20 16:48 1/19/21 7:51 grananqvist/Awesome-Quant-Machine-Learning-Trading PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading active 5.0 39:24.6
167 botflow Trend Following https://github.com/kkyon/botflow http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html NEW A futures trend following portfolio investment strategy. Other Models 3/31/21 10:56 1165 102 8 8/20/18 3:13 5/23/19 14:40 kkyon/botflow active 39:24.6
168 surpriver Short-Term Movement Cues https://github.com/tradytics/surpriver https://github.com/anfederico/Clairvoyant NEW Identify social/historical cues for short term stock movement. Other Models 4/12/21 12:27 4/12/21 13:11 1189 2166.0 221 678.0 6 1.0 8/30/20 7:56 9/12/16 18:38 9/21/20 4:32 8/29/18 20:27 tradytics/surpriver anfederico/clairvoyant active inactive 39:24.6
169 finance_ml Mixture Models II https://github.com/jjakimoto/finance_ml https://github.com/BlackArbsCEO/mixture_model_trading_public NEW Mixture models and stock trading. Other Models 4/8/21 15:28 3/12/21 13:21 282 166.0 117 73.0 1 1.0 6/29/18 21:21 12/11/17 17:05 2/18/19 12:34 5/13/20 23:50 jjakimoto/finance_ml BlackArbsCEO/mixture_model_trading_public inactive active 39:24.6
170 awesome-ai-in-finance fin-ml https://github.com/georgezouq/awesome-ai-in-finance https://github.com/tatsath/fin-ml NEW Other Models 4/11/21 7:43 4/11/21 3:29 941 116.0 162 66.0 8 2.0 8/29/18 2:07 5/10/20 0:25 11/27/20 9:43 1/23/21 17:15 georgezouq/awesome-ai-in-finance tatsath/fin-ml active 39:24.6
171 Pattern-Recognition-for-Forex-Trading Fundamental LT Forecasts https://github.com/PythonProgramming/Pattern-Recognition-for-Forex-Trading https://github.com/Hvass-Labs/FinanceOps NEW Research in investment finance for long term forecasts. Other Models 4/5/21 3:23 4/5/21 23:36 173 383.0 91 127.0 1 1.0 3/26/15 2:22 7/22/18 8:14 3/26/15 2:33 2/17/21 14:39 PythonProgramming/Pattern-Recognition-for-Forex-Trading Hvass-Labs/FinanceOps inactive active 39:24.6
172 Microservices-Based-Algorithmic-Trading-System Speculator https://github.com/saeed349/Microservices-Based-Algorithmic-Trading-System https://github.com/amicks/Speculator NEW Other Models 4/10/21 12:59 3/15/21 16:27 104 101.0 56 31.0 0 2.0 1/6/20 0:21 9/3/17 17:43 3/31/20 13:02 9/12/18 18:58 saeed349/Microservices-Based-Algorithmic-Trading-System amicks/Speculator active inactive 39:24.6
173 Machine-Learning-for-Algorithmic-Trading-Bots-with-Python Machine-Learning-and-AI-in-Trading https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading NEW Other Models 4/11/21 6:02 4/8/21 11:31 172 261.0 94 101.0 5 1.0 12/6/18 11:35 8/30/17 6:14 1/18/21 6:40 10/29/19 8:14 PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python PyPatel/Machine-Learning-and-AI-in-Trading active 39:24.6
174 Machine Learning in Asset Management Mixture Models I https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952 https://github.com/BlackArbsCEO/Mixture_Models Mixture models to predict market bottoms. Personal Papers Other Models 3/2/21 19:44 31.0 31.0 1.0 3/20/17 18:54 4/25/17 23:35 BlackArbsCEO/Mixture_Models inactive
175 Financial Event Prediction using Machine Learning stock-trading-ml https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555 https://github.com/yacoubb/stock-trading-ml NEW Personal Papers Other Models 4/11/21 14:46 340.0 186.0 1.0 10/10/19 9:44 10/12/19 11:38 yacoubb/stock-trading-ml active 39:24.6
176 Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original https://jfds.pm-research.com/content/2/2/17 https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original NEW Personal Papers Other Models 4/8/21 20:01 279.0 126.0 4.0 11/15/19 8:51 1/21/21 7:56 PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original active 39:24.6
177 Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies mosquito https://jfds.pm-research.com/content/2/1/10 https://github.com/miro-ka/mosquito NEW Personal Papers Other Models 4/12/21 9:44 220.0 44.0 2.0 6/18/17 19:57 3/14/21 22:22 miro-ka/mosquito active 39:24.6
178 Online Portfolio Selection Scikit-learn Stock Prediction https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb https://github.com/robertmartin8/MachineLearningStocks ****Comparing OLPS algorithms on a diversified set of ETFs. Using python and scikit-learn to make stock predictions. Portfolio Selection and Optimisation Other Models 4/11/21 10:00 931.0 347.0 2.0 2/12/17 4:50 2/4/21 3:48 robertmartin8/MachineLearningStocks active
179 node-finance ML_Finance_Codes https://github.com/albertosantini/node-finance https://github.com/mfrdixon/ML_Finance_Codes NEW Portfolio Selection and Optimisation Other Models 4/5/21 8:01 4/11/21 8:30 101 250.0 26 104.0 3 3.0 9/17/11 17:49 9/27/19 16:13 4/5/21 8:01 6/13/20 21:20 albertosantini/node-finance mfrdixon/ML_Finance_Codes active 37:19.5 39:24.6
180 Riskfolio-Lib Machine Learning in Asset Management https://github.com/dcajasn/Riskfolio-Lib https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952 NEW Portfolio Selection and Optimisation Personal Papers 4/12/21 12:25 371 62 1 3/2/20 19:49 4/1/21 3:50 dcajasn/Riskfolio-Lib active 37:19.5
181 OLMAR Algorithm Financial Event Prediction using Machine Learning https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555 Relative importance of each component of the OLMAR algorithm. Portfolio Selection and Optimisation Personal Papers 4/8/21 19:07 7 4 1 7/26/16 16:20 12/30/16 11:40 charlessutton/OLMAR inactive
182 Reinforcement Learning Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization https://github.com/filangel/qtrader https://jfds.pm-research.com/content/2/2/17 Reinforcement Learning for Portfolio Management. Portfolio Selection and Optimisation Personal Papers 3/29/21 3:47 364 150 1 10/7/17 9:14 6/26/18 9:22 filangelos/qtrader inactive
183 DeepDow Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies https://github.com/jankrepl/deepdow https://jfds.pm-research.com/content/2/1/10 Portfolio optimization with deep learning. Portfolio Selection and Optimisation Personal Papers 4/7/21 6:57 311 58 2 2/2/20 8:46 2/16/21 18:50 jankrepl/deepdow active
184 Distribution Characteristic Optimisation OLMAR Algorithm https://github.com/VivekPa/OptimalPortfolio https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account. Relative importance of each component of the OLMAR algorithm. Portfolio Selection and Optimisation 4/12/21 13:10 4/8/21 19:07 232 7.0 82 4.0 3 1.0 11/16/18 12:20 7/26/16 16:20 7/4/19 1:41 12/30/16 11:40 VivekPa/OptimalPortfolio charlessutton/OLMAR active inactive
185 401K Portfolio Optimisation Online Portfolio Selection https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb Portfolio analyses and optimisation for 401K. ****Comparing OLPS algorithms on a diversified set of ETFs. Portfolio Selection and Optimisation 12/25/20 9:39 14 5 1 8/1/18 19:48 9/5/19 11:18 otosman/Python-for-Finance active
186 Modern Portfolio Theory Riskfolio-Lib https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb https://github.com/dcajasn/Riskfolio-Lib Universal portfolios; modern portfolio theory. NEW Portfolio Selection and Optimisation 4/12/21 12:25 371.0 62.0 1.0 3/2/20 19:49 4/1/21 3:50 dcajasn/Riskfolio-Lib active 37:19.5
187 Deep Portfolio Theory Efficient Frontier https://github.com/tcloaa/Deep-Portfolio-Theory https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb Autoencoder framework for portfolio selection. Modern Portfolio Theory. Portfolio Selection and Optimisation 4/6/21 11:47 3/30/21 0:01 105 104.0 57 57.0 1 1.0 2/10/17 9:03 2/17/18 8:19 3/8/18 16:47 2/27/18 13:16 tcloaa/Deep-Portfolio-Theory tthustla/efficient_frontier inactive
188 PyPortfolioOpt Policy Gradient Portfolio https://github.com/robertmartin8/PyPortfolioOpt https://github.com/ZhengyaoJiang/PGPortfolio Financial portfolio optimisation, including classical efficient frontier and advanced methods. A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem. Portfolio Selection and Optimisation 4/12/21 11:54 4/9/21 10:41 1895 1281.0 479 629.0 16 6.0 5/29/18 13:30 11/12/17 16:08 2/25/21 13:01 5/9/19 9:50 robertmartin8/PyPortfolioOpt ZhengyaoJiang/PGPortfolio active
189 riskparity.py Deep Portfolio Theory https://github.com/dppalomar/riskparity.py https://github.com/tcloaa/Deep-Portfolio-Theory NEW Autoencoder framework for portfolio selection. Portfolio Selection and Optimisation 4/11/21 9:40 4/6/21 11:47 124 105.0 31 57.0 2 1.0 7/13/19 21:30 2/10/17 9:03 1/30/21 1:53 3/8/18 16:47 dppalomar/riskparity.py tcloaa/Deep-Portfolio-Theory active inactive 37:19.5
190 Policy Gradient Portfolio PyPortfolioOpt https://github.com/ZhengyaoJiang/PGPortfolio https://github.com/robertmartin8/PyPortfolioOpt A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem. Financial portfolio optimisation, including classical efficient frontier and advanced methods. Portfolio Selection and Optimisation 4/9/21 10:41 4/12/21 11:54 1281 1895.0 629 479.0 6 16.0 11/12/17 16:08 5/29/18 13:30 5/9/19 9:50 2/25/21 13:01 ZhengyaoJiang/PGPortfolio robertmartin8/PyPortfolioOpt active
191 Efficient Frontier node-finance https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb https://github.com/albertosantini/node-finance Modern Portfolio Theory. NEW Portfolio Selection and Optimisation 3/30/21 0:01 4/5/21 8:01 104 101.0 57 26.0 1 3.0 2/17/18 8:19 9/17/11 17:49 2/27/18 13:16 4/5/21 8:01 tthustla/efficient_frontier albertosantini/node-finance inactive active 37:19.5
192 Financial Statement Sentiment Reinforcement Learning https://github.com/MAydogdu/TextualAnalysis https://github.com/filangel/qtrader Extracting sentiment from financial statements using neural networks. Reinforcement Learning for Portfolio Management. Textual Portfolio Selection and Optimisation 3/31/21 2:10 3/29/21 3:47 8 364.0 7 150.0 1 1.0 6/4/18 20:54 10/7/17 9:14 6/4/18 20:56 6/26/18 9:22 MAydogdu/TextualAnalysis filangelos/qtrader inactive
193 NLP Event DeepDow https://github.com/yuriak/DLQuant https://github.com/jankrepl/deepdow Applying Deep Learning and NLP in Quantitative Trading. Portfolio optimization with deep learning. Textual Portfolio Selection and Optimisation 4/1/21 2:16 4/7/21 6:57 70 311.0 31 58.0 1 2.0 7/2/18 23:50 2/2/20 8:46 1/31/19 14:08 2/16/21 18:50 yuriak/DLQuant jankrepl/deepdow inactive active
194 Financial Sentiment Analysis Distribution Characteristic Optimisation https://github.com/EricHe98/Financial-Statements-Text-Analysis https://github.com/VivekPa/OptimalPortfolio Sentiment, distance and proportion analysis for trading signals. Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account. Textual Portfolio Selection and Optimisation 3/31/21 23:48 4/12/21 13:10 48 232.0 27 82.0 1 3.0 6/23/17 0:05 11/16/18 12:20 1/26/19 3:35 7/4/19 1:41 EricHe98/Financial-Statements-Text-Analysis VivekPa/OptimalPortfolio inactive active
195 NLP 401K Portfolio Optimisation https://github.com/toamitesh/NLPinFinance https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb This project assembles a lot of NLP operations needed for finance domain. Portfolio analyses and optimisation for 401K. Textual Portfolio Selection and Optimisation 12/25/20 9:39 14.0 5.0 1.0 8/1/18 19:48 9/5/19 11:18 toamitesh/NLPinFinance otosman/Python-for-Finance active
196 Earning call transcripts Modern Portfolio Theory https://github.com/lin882/WebAnalyticsProject https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb Correlation between mutual fund investment decision and earning call transcripts. Universal portfolios; modern portfolio theory. Textual Portfolio Selection and Optimisation 12/17/20 8:24 3 3 1 12/30/17 8:56 1/11/18 2:11 lin882/WebAnalyticsProject inactive
197 Buzzwords riskparity.py https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds https://github.com/dppalomar/riskparity.py Return performance and mutual fund selection. NEW Textual Portfolio Selection and Optimisation 10/6/20 18:54 4/11/21 9:40 1 124.0 4 31.0 1 2.0 2/4/18 21:51 7/13/19 21:30 2/4/18 21:57 1/30/21 1:53 swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds dppalomar/riskparity.py inactive active 37:19.5
198 Accounting Anomalies Fund classification https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb Using deep-learning frameworks to identify accounting anomalies. Fund classification using text mining and NLP. Textual 4/12/21 7:47 3/31/21 2:12 110 4.0 51 2.0 2 1.0 5/24/17 12:36 4/16/18 22:18 8/7/19 21:47 6/7/18 22:01 GitiHubi/deepAI frechfrechfrech/Mutual-Fund-Market-Clusters active inactive
199 Extensive NLP Earning call transcripts https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb https://github.com/lin882/WebAnalyticsProject Comprehensive NLP techniques for accounting research. Correlation between mutual fund investment decision and earning call transcripts. Textual 3/21/21 7:39 12/17/20 8:24 73 3.0 42 3.0 1 1.0 10/25/17 7:10 12/30/17 8:56 6/5/20 3:28 1/11/18 2:11 TiesdeKok/Python_NLP_Tutorial lin882/WebAnalyticsProject active inactive
200 Fund classification Accounting Anomalies https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb Fund classification using text mining and NLP. Using deep-learning frameworks to identify accounting anomalies. Textual 3/31/21 2:12 4/12/21 7:47 4 110.0 2 51.0 1 2.0 4/16/18 22:18 5/24/17 12:36 6/7/18 22:01 8/7/19 21:47 frechfrechfrech/Mutual-Fund-Market-Clusters GitiHubi/deepAI inactive active
201 Industry Clustering Buzzwords https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds Project to cluster industries according to financial attributes. Return performance and mutual fund selection. Unsupervised Textual 10/6/20 18:51 10/6/20 18:54 4 1.0 5 4.0 1 1.0 7/21/17 2:12 2/4/18 21:51 7/23/17 2:53 2/4/18 21:57 SeanMcOwen/FinanceAndPython.com-ClusteringIndustries swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds inactive
202 Pairs Trading NLP https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb https://github.com/toamitesh/NLPinFinance Finding pairs with cluster analysis. This project assembles a lot of NLP operations needed for finance domain. Unsupervised Textual 4/4/21 17:55 79 36 0 9/5/17 19:19 9/27/17 20:42 marketneutral/pairs-trading-with-ML toamitesh/NLPinFinance inactive
203 PCA Pairs Trading Financial Sentiment Analysis https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading https://github.com/EricHe98/Financial-Statements-Text-Analysis PCA, Factor Returns, and trading strategies. Sentiment, distance and proportion analysis for trading signals. Unsupervised Textual 3/31/21 23:48 48.0 27.0 1.0 6/23/17 0:05 1/26/19 3:35 joelQF/quant-finance EricHe98/Financial-Statements-Text-Analysis inactive
204 Industry Clustering NLP Event https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries https://github.com/yuriak/DLQuant Clustering of industries. Applying Deep Learning and NLP in Quantitative Trading. Unsupervised Textual 10/6/20 18:51 4/1/21 2:16 4 70.0 5 31.0 1 1.0 7/21/17 2:12 7/2/18 23:50 7/23/17 2:53 1/31/19 14:08 SeanMcOwen/FinanceAndPython.com-ClusteringIndustries yuriak/DLQuant inactive
205 Fund Clusters Financial Statement Sentiment https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb https://github.com/MAydogdu/TextualAnalysis Data exploration of fund clusters. Extracting sentiment from financial statements using neural networks. Unsupervised Textual 3/31/21 2:12 3/31/21 2:10 4 8.0 2 7.0 1 1.0 4/16/18 22:18 6/4/18 20:54 6/7/18 22:01 6/4/18 20:56 frechfrechfrech/Mutual-Fund-Market-Clusters MAydogdu/TextualAnalysis inactive
206 VRA Stock Embedding Extensive NLP https://github.com/ml-hongkong/stock2vec https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history. Comprehensive NLP techniques for accounting research. Unsupervised Textual 10/20/20 11:05 3/21/21 7:39 32 73.0 12 42.0 1 1.0 6/21/17 4:47 10/25/17 7:10 6/21/17 4:51 6/5/20 3:28 ml-hongkong/stock2vec TiesdeKok/Python_NLP_Tutorial inactive active
207 Pairs Trading https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb Finding pairs with cluster analysis. Unsupervised 4/4/21 17:55 79.0 36.0 0.0 9/5/17 19:19 9/27/17 20:42 marketneutral/pairs-trading-with-ML inactive
208 PCA Pairs Trading https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading PCA, Factor Returns, and trading strategies. Unsupervised joelQF/quant-finance
209 Industry Clustering https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries Clustering of industries. Unsupervised 10/6/20 18:51 4.0 5.0 1.0 7/21/17 2:12 7/23/17 2:53 SeanMcOwen/FinanceAndPython.com-ClusteringIndustries inactive
210 Fund Clusters https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb Data exploration of fund clusters. Unsupervised 3/31/21 2:12 4.0 2.0 1.0 4/16/18 22:18 6/7/18 22:01 frechfrechfrech/Mutual-Fund-Market-Clusters inactive
211 VRA Stock Embedding https://github.com/ml-hongkong/stock2vec Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history. Unsupervised 10/20/20 11:05 32.0 12.0 1.0 6/21/17 4:47 6/21/17 4:51 ml-hongkong/stock2vec inactive
212 Industry Clustering https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries Project to cluster industries according to financial attributes. Unsupervised 10/6/20 18:51 4.0 5.0 1.0 7/21/17 2:12 7/23/17 2:53 SeanMcOwen/FinanceAndPython.com-ClusteringIndustries inactive