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# Financial Machine Learning and Data Science
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A curated list of practical financial machine learning (FinML) tools and applications. This collection is primarily in Python.
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A listed repository should be deprecated if:
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- Repository's owner explicitly say that "this library is not maintained".
- Not committed for long time (2~3 years).
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**This repo is officially under revamp as of 3/29/2021!!**
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- TODOs and roadmap is under the github project [here](https://github.com/firmai/financial-machine-learning/projects/1)
- If you would like to contribute to this repo, please send us a pull request or contact [@dereknow](https://twitter.com/dereknow) or [@bin-yang-algotune](https://twitter.com/b3yang)
- Join us in the gitter chat [here](https://gitter.im/financial-machine-learning/community)
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___
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- All repos/links status including last commit date is updated daily
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- 10 Highest ranked repos/links for each section are displayed on main README.md and full list is available within the wiki page
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- Both Wikis/README.md is updated in realtime as soon as new information are pushed to the repo
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___
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# Trading
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## Deep Learning & Reinforcement Learning ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/deep_learning_and_reinforcement_learning))
<!-- [PLACEHOLDER_START:deep_learning_and_reinforcement_learning] -->
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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>2017-12-18 10:49:59</sub> | <sub>2021-01-05 10:31:50</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>2019-01-09 08:02:47</sub> | <sub>2019-02-11 16:32:47</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>2020-07-26 13:18:16</sub> | <sub>2021-04-11 22:02:16</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>2017-03-09 06:11:06</sub> | <sub>2017-03-19 07:42:49</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>2019-04-27 18:35:15</sub> | <sub>2019-10-17 16:25:49</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>2016-06-18 18:23:06</sub> | <sub>2018-08-07 15:24:45</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>2018-03-10 11:22:00</sub> | <sub>2018-09-02 17:21:38</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>2020-07-26 13:12:53</sub> | <sub>2021-01-21 18:11:59</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>2018-11-26 03:23:04</sub> | <sub>2021-01-01 09:41:21</sub> | <sub>551.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |<!-- [PLACEHOLDER_END:deep_learning_and_reinforcement_learning] -->
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## Other Models ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/other_models))
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<!-- [PLACEHOLDER_START:other_models] -->
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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>[Trend Following](http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html)</sub> | <sub>A futures trend following portfolio investment strategy.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance)</sub> | <sub>NEW</sub> | <sub>2018-08-29 02:07:02</sub> | <sub>2020-11-27 09:43:40</sub> | <sub>941.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Scikit-learn Stock Prediction](https://github.com/robertmartin8/MachineLearningStocks)</sub> | <sub>Using python and scikit-learn to make stock predictions.</sub> | <sub>2017-02-12 04:50:44</sub> | <sub>2021-02-04 03:48:33</sub> | <sub>931.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Hands-On-Machine-Learning-for-Algorithmic-Trading](https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading)</sub> | <sub>NEW</sub> | <sub>2019-05-07 11:04:25</sub> | <sub>2021-01-19 07:51:00</sub> | <sub>600.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[AlphaPy](https://github.com/ScottfreeLLC/AlphaPy)</sub> | <sub>NEW</sub> | <sub>2016-02-14 00:47:32</sub> | <sub>2021-02-08 21:35:40</sub> | <sub>576.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[MathAndScienceNotes](https://github.com/melling/MathAndScienceNotes)</sub> | <sub>NEW</sub> | <sub>2016-03-11 19:13:00</sub> | <sub>2020-12-21 03:54:51</sub> | <sub>460.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Fundamental LT Forecasts](https://github.com/Hvass-Labs/FinanceOps)</sub> | <sub>Research in investment finance for long term forecasts.</sub> | <sub>2018-07-22 08:14:46</sub> | <sub>2021-02-17 14:39:30</sub> | <sub>383.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[stock-trading-ml](https://github.com/yacoubb/stock-trading-ml)</sub> | <sub>NEW</sub> | <sub>2019-10-10 09:44:02</sub> | <sub>2019-10-12 11:38:49</sub> | <sub>340.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Mixture Models I](https://github.com/BlackArbsCEO/Mixture_Models)</sub> | <sub>Mixture models to predict market bottoms.</sub> | <sub>2017-03-20 18:54:24</sub> | <sub>2017-04-25 23:35:20</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[finance_ml](https://github.com/jjakimoto/finance_ml)</sub> | <sub>NEW</sub> | <sub>2018-06-29 21:21:17</sub> | <sub>2019-02-18 12:34:54</sub> | <sub>282.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:other_models] -->
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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> |
|:-------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------|:--------------------|
| <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>2018-04-25 17:22:40</sub> | <sub>2020-01-16 17:25:41</sub> | <sub>973.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data_processing_techniques_and_transformations] -->
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# Portfolio Management
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## Portfolio Selection and Optimisation ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/portfolio_selection_and_optimisation))
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<!-- [PLACEHOLDER_START:portfolio_selection_and_optimisation] -->
| <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>[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>2016-07-26 16:20:10</sub> | <sub>2016-12-30 11:40:53</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>2020-03-02 19:49:06</sub> | <sub>2021-04-01 03:50:59</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>2017-10-07 09:14:33</sub> | <sub>2018-06-26 09:22:27</sub> | <sub>364.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[DeepDow](https://github.com/jankrepl/deepdow)</sub> | <sub>Portfolio optimization with deep learning.</sub> | <sub>2020-02-02 08:46:33</sub> | <sub>2021-02-16 18:50:53</sub> | <sub>311.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Distribution Characteristic Optimisation](https://github.com/VivekPa/OptimalPortfolio)</sub> | <sub>Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.</sub> | <sub>2018-11-16 12:20:25</sub> | <sub>2019-07-04 01:41:46</sub> | <sub>232.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt)</sub> | <sub>Financial portfolio optimisation, including classical efficient frontier and advanced methods.</sub> | <sub>2018-05-29 13:30:30</sub> | <sub>2021-02-25 13:01:56</sub> | <sub>1895.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[401K Portfolio Optimisation](https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb)</sub> | <sub>Portfolio analyses and optimisation for 401K.</sub> | <sub>2018-08-01 19:48:24</sub> | <sub>2019-09-05 11:18:56</sub> | <sub>14.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Policy Gradient Portfolio](https://github.com/ZhengyaoJiang/PGPortfolio)</sub> | <sub>A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.</sub> | <sub>2017-11-12 16:08:44</sub> | <sub>2019-05-09 09:50:18</sub> | <sub>1281.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:portfolio_selection_and_optimisation] -->
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## Factor and Risk Analysis ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/factor_and_risk_analysis))
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<!-- [PLACEHOLDER_START:factor_and_risk_analysis] -->
| <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>[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>2018-08-06 16:09:44</sub> | <sub>2020-11-22 19:02:07</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>2017-08-07 14:44:32</sub> | <sub>2017-08-08 22:52:11</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>2015-06-01 15:31:39</sub> | <sub>2020-02-28 17:30:19</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>2018-08-11 22:59:53</sub> | <sub>2019-11-12 04:49:01</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</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>2016-05-10 11:03:48</sub> | <sub>2016-05-17 03:44:56</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>2016-05-10 11:03:48</sub> | <sub>2016-05-17 03:44:56</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</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>2018-03-13 07:39:20</sub> | <sub>2018-03-13 07:42:36</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>2015-10-04 09:10:54</sub> | <sub>2020-03-28 18:33:58</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>2016-06-03 21:49:15</sub> | <sub>2020-04-27 18:40:41</sub> | <sub>1847.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Convex Optimisation](https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb)</sub> | <sub>Convex Optimization for Finance.</sub> | <sub>2018-06-26 20:36:47</sub> | <sub>2019-10-22 21:56:46</sub> | <sub>18.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:factor_and_risk_analysis] -->
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# Techniques
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## Unsupervised ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/unsupervised))
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<!-- [PLACEHOLDER_START:unsupervised] -->
| <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>[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>2017-09-05 19:19:19</sub> | <sub>2017-09-27 20:42:14</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>2017-07-21 02:12:51</sub> | <sub>2017-07-23 02:53:37</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>2017-07-21 02:12:51</sub> | <sub>2017-07-23 02:53:37</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>2018-04-16 22:18:55</sub> | <sub>2018-06-07 22:01:32</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>2017-06-21 04:47:14</sub> | <sub>2017-06-21 04:51:13</sub> | <sub>32.0</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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<!-- [PLACEHOLDER_START:textual] -->
| <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>[NLP](https://github.com/toamitesh/NLPinFinance)</sub> | <sub>This project assembles a lot of NLP operations needed for finance domain.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Financial Statement Sentiment](https://github.com/MAydogdu/TextualAnalysis)</sub> | <sub>Extracting sentiment from financial statements using neural networks.</sub> | <sub>2018-06-04 20:54:14</sub> | <sub>2018-06-04 20:56:02</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Extensive NLP](https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb)</sub> | <sub>Comprehensive NLP techniques for accounting research.</sub> | <sub>2017-10-25 07:10:26</sub> | <sub>2020-06-05 03:28:46</sub> | <sub>73.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[NLP Event](https://github.com/yuriak/DLQuant)</sub> | <sub>Applying Deep Learning and NLP in Quantitative Trading.</sub> | <sub>2018-07-02 23:50:52</sub> | <sub>2019-01-31 14:08:20</sub> | <sub>70.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis)</sub> | <sub>Sentiment, distance and proportion analysis for trading signals.</sub> | <sub>2017-06-23 00:05:49</sub> | <sub>2019-01-26 03:35:55</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>2018-04-16 22:18:55</sub> | <sub>2018-06-07 22:01:32</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>2017-12-30 08:56:03</sub> | <sub>2018-01-11 02:11:11</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</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>2017-05-24 12:36:38</sub> | <sub>2019-08-07 21:47:08</sub> | <sub>110.0</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>2018-02-04 21:51:16</sub> | <sub>2018-02-04 21:57:09</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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## Derivatives and Hedging ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/derivatives_and_hedging))
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<!-- [PLACEHOLDER_START:derivatives_and_hedging] -->
| <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>[Options](https://github.com/PHBS/2018.M1.ASP/tree/master/py)</sub> | <sub>Black Scholes and Copula.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Derivative Markets](https://github.com/broughtj/Fin6470/tree/master/Notebooks)</sub> | <sub>The economics of futures, futures, options, and swaps.</sub> | <sub>2016-02-09 05:30:27</sub> | <sub>2021-04-06 20:49:41</sub> | <sub>8.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Volatility and Variance Derivatives](https://github.com/yhilpisch/lvvd/tree/master/lvvd)</sub> | <sub>Volatility derivatives analytics.</sub> | <sub>2016-10-21 04:12:50</sub> | <sub>2021-02-22 13:32:00</sub> | <sub>79.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Hull White](https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb)</sub> | <sub>Callable Bond, Hull White.</sub> | <sub>2018-06-06 22:06:06</sub> | <sub>2018-06-06 22:27:02</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Derivatives Python](https://github.com/yhilpisch/dawp/tree/master/python36)</sub> | <sub>Derivative analytics with Python.</sub> | <sub>2015-07-09 12:27:29</sub> | <sub>2021-02-22 13:29:18</sub> | <sub>388.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Options](https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D)</sub> | <sub>Introduction to options.</sub> | <sub>2017-07-28 15:48:29</sub> | <sub>2021-03-17 17:17:08</sub> | <sub>335.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Delta Hedging](https://github.com/RobinsonGarcia/delta-hedging)</sub> | <sub>Advanced derivatives.</sub> | <sub>2018-03-02 23:53:53</sub> | <sub>2018-07-17 23:32:23</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <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>2018-05-22 18:27:26</sub> | <sub>2018-05-22 18:30:24</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>2018-01-29 05:01:52</sub> | <sub>2018-08-02 05:56:49</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>2017-04-21 10:58:56</sub> | <sub>2017-08-02 21:41:06</sub> | <sub>16.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:derivatives_and_hedging] -->
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## Fixed Income ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/fixed_income))
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<!-- [PLACEHOLDER_START:fixed_income] -->
| <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>[Corporate Bonds](https://github.com/ishank011/gs-quantify-bond-prediction)</sub> | <sub>Predicting the buying and selling volume of the corporate bonds.</sub> | <sub>2017-09-27 19:57:13</sub> | <sub>2017-09-27 20:00:29</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Vasicek](https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb)</sub> | <sub>Bootstrapping and interpolation.</sub> | <sub>2018-07-18 19:26:54</sub> | <sub>2018-07-18 19:34:48</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Binomial Tree](https://github.com/hy-lei/math-finance-exercise)</sub> | <sub>Utility functions in fixed income securities.</sub> | <sub>2019-02-02 08:44:14</sub> | <sub>2019-05-03 17:16:52</sub> | <sub>1.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:fixed_income] -->
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## Alternative Finance ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/alternative_finance))
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<!-- [PLACEHOLDER_START:alternative_finance] -->
| <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>[Venture Capital NN](https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring)</sub> | <sub>Cox-PH neural network predictions for VC/innovations finance research.</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>nan</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Art Valuation](https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb)</sub> | <sub>Art evaluation analytics.</sub> | <sub>2014-12-11 00:25:39</sub> | <sub>2014-12-12 21:25:46</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Private Equity](https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb)</sub> | <sub>Valuation models.</sub> | <sub>2016-01-27 21:13:33</sub> | <sub>2016-03-14 20:03:52</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Kiva Crowdfunding](https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb)</sub> | <sub>Exploratory data analysis.</sub> | <sub>2018-02-27 16:46:02</sub> | <sub>2019-02-13 00:15:27</sub> | <sub>5.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Watch Valuation](https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb)</sub> | <sub>Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued.</sub> | <sub>2017-02-08 18:39:29</sub> | <sub>2017-04-27 22:55:55</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Venture Capital](https://github.com/julian-chan/etothex)</sub> | <sub>Insight into a new founder to make data-driven investment decisions.</sub> | <sub>2017-12-04 08:59:44</sub> | <sub>2017-12-13 05:35:27</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[VC OLS](https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb)</sub> | <sub>VC regression.</sub> | <sub>2018-03-29 23:31:13</sub> | <sub>2018-03-29 23:33:19</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Blockchain](https://github.com/nud3l/dInvest)</sub> | <sub>Repository for distributed autonomous investment banking.</sub> | <sub>2016-09-05 19:12:40</sub> | <sub>2017-04-24 10:48:56</sub> | <sub>12.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:alternative_finance] -->
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# Extended Research ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/extended_research))
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<!-- [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>[Behavioural Economics](https://github.com/pcmichaud/notebooks)</sub> | <sub>Behavioural Economics and Finance Python Notebooks.</sub> | <sub>2018-12-20 00:21:38</sub> | <sub>2019-03-26 11:51:46</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Corporate Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance)</sub> | <sub>Basic corporate finance.</sub> | <sub>2017-09-09 03:35:24</sub> | <sub>2017-09-09 23:04:48</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <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>2018-01-29 05:14:52</sub> | <sub>2018-07-19 06:25:36</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[NLP Finance Papers](https://github.com/chenbowen184/Research_Documents_Curation_with_NLP)</sub> | <sub>Curating quantitative finance papers using machine learning.</sub> | <sub>2018-10-11 20:32:37</sub> | <sub>2018-12-24 23:27:55</sub> | <sub>8.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[HFT](https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy)</sub> | <sub>High frequency trading.</sub> | <sub>2016-07-21 05:14:14</sub> | <sub>2017-02-14 16:47:25</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>2014-11-09 04:49:01</sub> | <sub>2018-12-03 16:30:28</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>2017-01-21 11:24:18</sub> | <sub>2020-08-01 17:03:32</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>2018-09-16 20:00:36</sub> | <sub>2020-09-05 13:01:05</sub> | <sub>620.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:extended_research] -->
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# Courses ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/courses))
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<!-- [PLACEHOLDER_START:courses] -->
| <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>[Basic Investments](https://github.com/SeanMcOwen/FinanceAndPython.com-Investments)</sub> | <sub>Basic investment tools in python.</sub> | <sub>2017-08-02 21:52:19</sub> | <sub>2017-08-17 03:24:53</sub> | <sub>9.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Mathematical Finance](https://github.com/yadongli/nyumath2048)</sub> | <sub>NYU Math-GA 2048: Scientific Computing in Finance.</sub> | <sub>2015-01-25 21:10:37</sub> | <sub>2020-03-25 04:24:25</sub> | <sub>69.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Algo Trading](https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading)</sub> | <sub>Intro to algo trading.</sub> | <sub>2017-10-29 20:34:54</sub> | <sub>2019-01-22 06:56:08</sub> | <sub>64.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Risk Management](https://github.com/andrey-lukyanov/Risk-Management)</sub> | <sub>Finance risk engagement course resources.</sub> | <sub>2018-10-03 16:26:14</sub> | <sub>2018-12-13 08:04:15</sub> | <sub>6.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Basic Derivatives](https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives)</sub> | <sub>Basic forward contracts and hedging.</sub> | <sub>2017-08-24 00:11:37</sub> | <sub>2017-10-13 01:32:23</sub> | <sub>4.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
| <sub>[Machine Learning for Trading](https://github.com/stefan-jansen/machine-learning-for-trading)</sub> | <sub>Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading.</sub> | <sub>2018-05-09 12:33:08</sub> | <sub>2021-04-10 22:21:29</sub> | <sub>3842.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[ML Specialisation](https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization)</sub> | <sub>Machine Learning in Finance.</sub> | <sub>2019-01-24 02:55:01</sub> | <sub>2020-01-03 21:54:16</sub> | <sub>34.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Python for Finance](https://github.com/siaen/python_finance_course)</sub> | <sub>CEU python for finance course material.</sub> | <sub>2017-12-12 11:54:46</sub> | <sub>2020-02-25 20:31:41</sub> | <sub>16.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Handson Python for Finance](https://github.com/PacktPublishing/Hands-on-Python-for-Finance)</sub> | <sub>Hands-on Python for Finance published by Packt.</sub> | <sub>2018-08-20 14:10:37</sub> | <sub>2021-01-15 08:57:06</sub> | <sub>121.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
| <sub>[Basic Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance)</sub> | <sub>Source code notebooks basic finance applications.</sub> | <sub>2017-05-06 02:39:05</sub> | <sub>2017-06-21 04:04:09</sub> | <sub>10.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:courses] -->
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# Data ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/data))
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<!-- [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> |
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| <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>[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> |
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| <sub>[SEC Parsing](https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb)</sub> | <sub>nan</sub> | <sub>2018-06-16 14:30:06</sub> | <sub>2018-06-16 17:23:46</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>2017-05-10 21:49:45</sub> | <sub>2017-08-06 19:23:18</sub> | <sub>7.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data] -->
Update README.md
2019-07-17 00:36:28 +01:00
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# Colleges, Centers and Departments ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/colleges_centers_and_departments))
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<!-- [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> |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------|:------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------|
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| <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> |
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| <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> |
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| <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>[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] -->
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