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## Data Processing Techniques and Transformations ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/data_processing_techniques_and_transformations))
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<!-- [PLACEHOLDER_START:data_processing_techniques_and_transformations] -->
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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> |
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|:----------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
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| <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> |
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| <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> |
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| <sub>[finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint)</sub> | <sub>NEW</sub> | <sub>9/26/16 19:42</sub> | <sub>1/20/21 23:07</sub> | <sub>72.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis)</sub> | <sub>NEW</sub> | <sub>7/23/17 2:59</sub> | <sub>7/23/17 3:10</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Twitter-Trends](https://github.com/Medha11/Twitter-Trends)</sub> | <sub>NEW</sub> | <sub>5/22/17 17:07</sub> | <sub>5/23/17 8:06</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>NEW</sub> | <sub>6/1/14 1:14</sub> | <sub>10/22/20 0:24</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>NEW</sub> | <sub>6/2/19 5:48</sub> | <sub>9/12/19 13:03</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data_processing_techniques_and_transformations] -->
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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> |
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|:----------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
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| <sub>[Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises to book [advances in financial machine learning](https://www.wiley.com/en-us/Advances+in+Financial+Machine+Learning-p-9781119482109). Relevant topics include data cleaning and outlier detection (using MAD)</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>:star:x4</sub> |
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| <sub>[Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis)</sub> | <sub>data processing platform which stream data from kafka. The example shows two incoming data stream stock vs tweets and two spark streams are created to consume the kafka data then end results are stored in cassandra. Older tech stacks were used and not actively maintained.</sub> | <sub>7/23/17 2:59</sub> | <sub>7/23/17 3:10</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
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| <sub>[Twitter-Trends](https://github.com/Medha11/Twitter-Trends)</sub> | <sub>sentiment analysis baed on twitter data. Relevant topics include data cleaning/tokenization/data aggregation using mangodb etc.</sub> | <sub>5/22/17 17:07</sub> | <sub>5/23/17 8:06</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
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| <sub>[finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint)</sub> | <sub>generate streamable data using mapr converged data platfrom built mostly in java. Uses apache [zepplin](https://zeppelin.apache.org/) for web visualization </sub> | <sub>9/26/16 19:42</sub> | <sub>1/20/21 23:07</sub> | <sub>72.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
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| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>java based platform for trading crypto. Relevant sections including using esper event queries to transform data and place orders</sub> | <sub>6/1/14 1:14</sub> | <sub>10/22/20 0:24</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |
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| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with [Homomorphic Encryption](https://www.cs.cmu.edu/~odonnell/hits09/gentry-homomorphic-encryption.pdf). Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted.</sub> | <sub>6/2/19 5:48</sub> | <sub>9/12/19 13:03</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |<!-- [PLACEHOLDER_END:data_processing_techniques_and_transformations] -->
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# Portfolio Management
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<!-- [PLACEHOLDER_START:portfolio_selection_and_optimisation] -->
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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> |
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||||
|:--------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
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| <sub>[Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb)</sub> | <sub>Universal portfolios; modern portfolio theory.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Online Portfolio Selection](https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb)</sub> | <sub>****Comparing OLPS algorithms on a diversified set of ETFs.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb)</sub> | <sub>Universal portfolios; modern portfolio theory.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[OLMAR Algorithm](https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb)</sub> | <sub>Relative importance of each component of the OLMAR algorithm.</sub> | <sub>7/26/16 16:20</sub> | <sub>12/30/16 11:40</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Riskfolio-Lib](https://github.com/dcajasn/Riskfolio-Lib)</sub> | <sub>NEW</sub> | <sub>3/2/20 19:49</sub> | <sub>4/1/21 3:50</sub> | <sub>371.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Reinforcement Learning](https://github.com/filangel/qtrader)</sub> | <sub>Reinforcement Learning for Portfolio Management.</sub> | <sub>10/7/17 9:14</sub> | <sub>6/26/18 9:22</sub> | <sub>364.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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<!-- [PLACEHOLDER_START:factor_and_risk_analysis] -->
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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> |
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|:-----------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
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| <sub>[stock-market-analysis-using-python-numpy-pandas](https://github.com/Ashishsinha10/stock-market-analysis-using-python-numpy-pandas)</sub> | <sub>NEW</sub> | <sub>4/10/18 5:15</sub> | <sub>4/10/18 5:28</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Machine_learning_In_Finance](https://github.com/chaudharigauravi/Machine_learning_In_Finance)</sub> | <sub>NEW</sub> | <sub>8/3/19 4:04</sub> | <sub>8/3/19 4:05</sub> | <sub>8.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[stock-market-analysis-using-python-numpy-pandas](https://github.com/Ashishsinha10/stock-market-analysis-using-python-numpy-pandas)</sub> | <sub>NEW</sub> | <sub>4/10/18 5:15</sub> | <sub>4/10/18 5:28</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[-L-](https://github.com/jettbrains/-L-)</sub> | <sub>NEW</sub> | <sub>10/28/19 21:50</sub> | <sub>10/28/19 21:51</sub> | <sub>6.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[TradeFinexLive](https://github.com/XinFinOrg/TradeFinexLive)</sub> | <sub>NEW</sub> | <sub>3/21/18 10:05</sub> | <sub>3/18/21 9:48</sub> | <sub>5.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <sub>[Performance Analysis](https://github.com/quantopian/alphalens)</sub> | <sub>Performance analysis of predictive (alpha) stock factors.</sub> | <sub>6/3/16 21:49</sub> | <sub>4/27/20 18:40</sub> | <sub>1847.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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|:-------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
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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> |
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| <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> |
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| <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> |
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| <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> |
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| <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> |
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| <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] -->
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| <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> |
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| <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> |
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| <sub>[Eigen-Portfolio](https://github.com/Gustrigos/Eigen-Portfolio)</sub> | <sub>NEW</sub> | <sub>9/5/18 5:29</sub> | <sub>4/9/20 21:40</sub> | <sub>35.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <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> |
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| <sub>[hmm_market_behavior](https://github.com/lamres/hmm_market_behavior)</sub> | <sub>NEW</sub> | <sub>9/8/19 17:37</sub> | <sub>5/10/20 14:36</sub> | <sub>25.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[all-classification-templetes-for-ML](https://github.com/sayantann11/all-classification-templetes-for-ML)</sub> | <sub>NEW</sub> | <sub>5/5/20 10:28</sub> | <sub>5/5/20 10:30</sub> | <sub>22.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[AnomalyDetectionOnRisk](https://github.com/SimonWesterlindVPD/AnomalyDetectionOnRisk)</sub> | <sub>NEW</sub> | <sub>5/31/18 15:53</sub> | <sub>5/31/18 16:18</sub> | <sub>11.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Credit-Card-Fraud-Detection](https://github.com/sharmaroshan/Credit-Card-Fraud-Detection)</sub> | <sub>NEW</sub> | <sub>3/31/19 5:33</sub> | <sub>3/31/19 5:38</sub> | <sub>10.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:unsupervised] -->
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## Textual ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/textual))
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@@ -145,7 +149,13 @@ ___
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| <sub>[Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis)</sub> | <sub>Sentiment, distance and proportion analysis for trading signals.</sub> | <sub>6/23/17 0:05</sub> | <sub>1/26/19 3:35</sub> | <sub>48.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Fund classification](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb)</sub> | <sub>Fund classification using text mining and NLP.</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> |
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| <sub>[Earning call transcripts](https://github.com/lin882/WebAnalyticsProject)</sub> | <sub>Correlation between mutual fund investment decision and earning call transcripts.</sub> | <sub>12/30/17 8:56</sub> | <sub>1/11/18 2:11</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[news-emotion](https://github.com/dongyuanxin/news-emotion)</sub> | <sub>NEW</sub> | <sub>9/14/17 2:59</sub> | <sub>6/11/18 13:47</sub> | <sub>245.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[awesome-financial-nlp](https://github.com/icoxfog417/awesome-financial-nlp)</sub> | <sub>NEW</sub> | <sub>10/3/19 3:53</sub> | <sub>2/1/20 8:28</sub> | <sub>226.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[FinNLP-Progress](https://github.com/YangLinyi/FinNLP-Progress)</sub> | <sub>NEW</sub> | <sub>5/21/20 9:59</sub> | <sub>3/23/21 8:14</sub> | <sub>164.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[financial-news-dataset](https://github.com/philipperemy/financial-news-dataset)</sub> | <sub>NEW</sub> | <sub>8/23/16 13:29</sub> | <sub>3/4/21 6:34</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[FinBERT](https://github.com/psnonis/FinBERT)</sub> | <sub>NEW</sub> | <sub>7/9/19 16:34</sub> | <sub>5/19/20 2:02</sub> | <sub>140.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Accounting Anomalies](https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb)</sub> | <sub>Using deep-learning frameworks to identify accounting anomalies.</sub> | <sub>5/24/17 12:36</sub> | <sub>8/7/19 21:47</sub> | <sub>110.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[BDCI2019-Negative_Finance_Info_Judge](https://github.com/A-Rain/BDCI2019-Negative_Finance_Info_Judge)</sub> | <sub>NEW</sub> | <sub>12/27/19 3:49</sub> | <sub>12/4/20 3:38</sub> | <sub>107.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds)</sub> | <sub>Return performance and mutual fund selection.</sub> | <sub>2/4/18 21:51</sub> | <sub>2/4/18 21:57</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:textual] -->
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# Other Assets
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@@ -198,20 +208,20 @@ ___
|
||||
<!-- [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>[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>[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>[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>[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>[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))
|
||||
@@ -233,14 +243,14 @@ ___
|
||||
<!-- [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>[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>[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>[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>[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>[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>[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>[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>[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>[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> |
|
||||
@@ -252,9 +262,9 @@ ___
|
||||
<!-- [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 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>[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>[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> |<!-- [PLACEHOLDER_END:colleges_centers_and_departments] -->
|
||||
| <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>[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>[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> |<!-- [PLACEHOLDER_END:colleges_centers_and_departments] -->
|
||||
|
||||
@@ -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 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>[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>[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>[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>[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> |
|
||||
@@ -1,13 +1,13 @@
|
||||
| <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>[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>[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>[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>[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>[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>[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>[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>[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>[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> |
|
||||
|
||||
@@ -1,9 +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>[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>9/26/16 19:42</sub> | <sub>1/20/21 23:07</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>7/23/17 2:59</sub> | <sub>7/23/17 3:10</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>5/22/17 17:07</sub> | <sub>5/23/17 8:06</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>NEW</sub> | <sub>6/1/14 1:14</sub> | <sub>10/22/20 0:24</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>NEW</sub> | <sub>6/2/19 5:48</sub> | <sub>9/12/19 13:03</sub> | <sub>154.0</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](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)</sub> | <sub>Exercises to book [advances in financial machine learning](https://www.wiley.com/en-us/Advances+in+Financial+Machine+Learning-p-9781119482109). Relevant topics include data cleaning and outlier detection (using MAD)</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>:star:x4</sub> |
|
||||
| <sub>[Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis)</sub> | <sub>data processing platform which stream data from kafka. The example shows two incoming data stream stock vs tweets and two spark streams are created to consume the kafka data then end results are stored in cassandra. Older tech stacks were used and not actively maintained.</sub> | <sub>7/23/17 2:59</sub> | <sub>7/23/17 3:10</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
|
||||
| <sub>[Twitter-Trends](https://github.com/Medha11/Twitter-Trends)</sub> | <sub>sentiment analysis baed on twitter data. Relevant topics include data cleaning/tokenization/data aggregation using mangodb etc.</sub> | <sub>5/22/17 17:07</sub> | <sub>5/23/17 8:06</sub> | <sub>66.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
|
||||
| <sub>[finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint)</sub> | <sub>generate streamable data using mapr converged data platfrom built mostly in java. Uses apache [zepplin](https://zeppelin.apache.org/) for web visualization </sub> | <sub>9/26/16 19:42</sub> | <sub>1/20/21 23:07</sub> | <sub>72.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
|
||||
| <sub>[cointrader](https://github.com/timolson/cointrader)</sub> | <sub>java based platform for trading crypto. Relevant sections including using esper event queries to transform data and place orders</sub> | <sub>6/1/14 1:14</sub> | <sub>10/22/20 0:24</sub> | <sub>339.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |
|
||||
| <sub>[CryptoNets](https://github.com/microsoft/CryptoNets)</sub> | <sub>CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with [Homomorphic Encryption](https://www.cs.cmu.edu/~odonnell/hits09/gentry-homomorphic-encryption.pdf). Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted.</sub> | <sub>6/2/19 5:48</sub> | <sub>9/12/19 13:03</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x2</sub> |
|
||||
@@ -35,6 +35,6 @@
|
||||
| <sub>[huobi_futures_Python](https://github.com/hbdmapi/huobi_futures_Python)</sub> | <sub>NEW</sub> | <sub>1/14/20 7:21</sub> | <sub>3/2/21 7:30</sub> | <sub>137.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[fast_arrow](https://github.com/westonplatter/fast_arrow)</sub> | <sub>NEW</sub> | <sub>7/19/18 23:15</sub> | <sub>4/18/20 18:05</sub> | <sub>127.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[robin_stocks](https://github.com/jmfernandes/robin_stocks)</sub> | <sub>NEW</sub> | <sub>2/23/18 0:49</sub> | <sub>2/27/21 17:48</sub> | <sub>1012.0</sub> | <sub>:heavy_check_mark:</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>[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> |
|
||||
| <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> |
|
||||
@@ -1,26 +1,26 @@
|
||||
| <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>[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>[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>[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>[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>[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>[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>[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>[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> |
|
||||
@@ -1,15 +1,15 @@
|
||||
| <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-market-analysis-using-python-numpy-pandas](https://github.com/Ashishsinha10/stock-market-analysis-using-python-numpy-pandas)</sub> | <sub>NEW</sub> | <sub>4/10/18 5:15</sub> | <sub>4/10/18 5:28</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Machine_learning_In_Finance](https://github.com/chaudharigauravi/Machine_learning_In_Finance)</sub> | <sub>NEW</sub> | <sub>8/3/19 4:04</sub> | <sub>8/3/19 4:05</sub> | <sub>8.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[stock-market-analysis-using-python-numpy-pandas](https://github.com/Ashishsinha10/stock-market-analysis-using-python-numpy-pandas)</sub> | <sub>NEW</sub> | <sub>4/10/18 5:15</sub> | <sub>4/10/18 5:28</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[-L-](https://github.com/jettbrains/-L-)</sub> | <sub>NEW</sub> | <sub>10/28/19 21:50</sub> | <sub>10/28/19 21:51</sub> | <sub>6.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[TradeFinexLive](https://github.com/XinFinOrg/TradeFinexLive)</sub> | <sub>NEW</sub> | <sub>3/21/18 10:05</sub> | <sub>3/18/21 9:48</sub> | <sub>5.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <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>[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>[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>[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>[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>[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> |
|
||||
| <sub>[Performance Analysis](https://github.com/quantopian/alphalens)</sub> | <sub>Performance analysis of predictive (alpha) stock factors.</sub> | <sub>6/3/16 21:49</sub> | <sub>4/27/20 18:40</sub> | <sub>1847.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
| <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>[Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb)</sub> | <sub>Universal portfolios; modern portfolio theory.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Online Portfolio Selection](https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb)</sub> | <sub>****Comparing OLPS algorithms on a diversified set of ETFs.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb)</sub> | <sub>Universal portfolios; modern portfolio theory.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[OLMAR Algorithm](https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb)</sub> | <sub>Relative importance of each component of the OLMAR algorithm.</sub> | <sub>7/26/16 16:20</sub> | <sub>12/30/16 11:40</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Riskfolio-Lib](https://github.com/dcajasn/Riskfolio-Lib)</sub> | <sub>NEW</sub> | <sub>3/2/20 19:49</sub> | <sub>4/1/21 3:50</sub> | <sub>371.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Reinforcement Learning](https://github.com/filangel/qtrader)</sub> | <sub>Reinforcement Learning for Portfolio Management.</sub> | <sub>10/7/17 9:14</sub> | <sub>6/26/18 9:22</sub> | <sub>364.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
|
||||
@@ -7,5 +7,11 @@
|
||||
| <sub>[Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis)</sub> | <sub>Sentiment, distance and proportion analysis for trading signals.</sub> | <sub>6/23/17 0:05</sub> | <sub>1/26/19 3:35</sub> | <sub>48.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Fund classification](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb)</sub> | <sub>Fund classification using text mining and NLP.</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>[Earning call transcripts](https://github.com/lin882/WebAnalyticsProject)</sub> | <sub>Correlation between mutual fund investment decision and earning call transcripts.</sub> | <sub>12/30/17 8:56</sub> | <sub>1/11/18 2:11</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[news-emotion](https://github.com/dongyuanxin/news-emotion)</sub> | <sub>NEW</sub> | <sub>9/14/17 2:59</sub> | <sub>6/11/18 13:47</sub> | <sub>245.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[awesome-financial-nlp](https://github.com/icoxfog417/awesome-financial-nlp)</sub> | <sub>NEW</sub> | <sub>10/3/19 3:53</sub> | <sub>2/1/20 8:28</sub> | <sub>226.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[FinNLP-Progress](https://github.com/YangLinyi/FinNLP-Progress)</sub> | <sub>NEW</sub> | <sub>5/21/20 9:59</sub> | <sub>3/23/21 8:14</sub> | <sub>164.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[financial-news-dataset](https://github.com/philipperemy/financial-news-dataset)</sub> | <sub>NEW</sub> | <sub>8/23/16 13:29</sub> | <sub>3/4/21 6:34</sub> | <sub>154.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[FinBERT](https://github.com/psnonis/FinBERT)</sub> | <sub>NEW</sub> | <sub>7/9/19 16:34</sub> | <sub>5/19/20 2:02</sub> | <sub>140.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Accounting Anomalies](https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb)</sub> | <sub>Using deep-learning frameworks to identify accounting anomalies.</sub> | <sub>5/24/17 12:36</sub> | <sub>8/7/19 21:47</sub> | <sub>110.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[BDCI2019-Negative_Finance_Info_Judge](https://github.com/A-Rain/BDCI2019-Negative_Finance_Info_Judge)</sub> | <sub>NEW</sub> | <sub>12/27/19 3:49</sub> | <sub>12/4/20 3:38</sub> | <sub>107.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds)</sub> | <sub>Return performance and mutual fund selection.</sub> | <sub>2/4/18 21:51</sub> | <sub>2/4/18 21:57</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
@@ -2,7 +2,12 @@
|
||||
|:-------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------|
|
||||
| <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>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> |
|
||||
| <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>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>[Eigen-Portfolio](https://github.com/Gustrigos/Eigen-Portfolio)</sub> | <sub>NEW</sub> | <sub>9/5/18 5:29</sub> | <sub>4/9/20 21:40</sub> | <sub>35.0</sub> | <sub>:heavy_check_mark:</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> |
|
||||
| <sub>[hmm_market_behavior](https://github.com/lamres/hmm_market_behavior)</sub> | <sub>NEW</sub> | <sub>9/8/19 17:37</sub> | <sub>5/10/20 14:36</sub> | <sub>25.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[all-classification-templetes-for-ML](https://github.com/sayantann11/all-classification-templetes-for-ML)</sub> | <sub>NEW</sub> | <sub>5/5/20 10:28</sub> | <sub>5/5/20 10:30</sub> | <sub>22.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[AnomalyDetectionOnRisk](https://github.com/SimonWesterlindVPD/AnomalyDetectionOnRisk)</sub> | <sub>NEW</sub> | <sub>5/31/18 15:53</sub> | <sub>5/31/18 16:18</sub> | <sub>11.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Credit-Card-Fraud-Detection](https://github.com/sharmaroshan/Credit-Card-Fraud-Detection)</sub> | <sub>NEW</sub> | <sub>3/31/19 5:33</sub> | <sub>3/31/19 5:38</sub> | <sub>10.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
Reference in New Issue
Block a user