mirror of
https://github.com/firmai/financial-machine-learning.git
synced 2026-08-08 08:37:48 +00:00
{chore: autopublish 2021-04-12T21:23:25Z}
This commit is contained in:
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| <sub>[Personae](https://github.com/Ceruleanacg/Personae)</sub> | <sub>implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from [rqalpha](https://github.com/ricequant/rqalpha) which is a python backtest engine and have a nice docker image to run training/testing</sub> | <sub>3/10/18 11:22</sub> | <sub>9/2/18 17:21</sub> | <sub>1144.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x5</sub> |
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| <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> |
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| <sub>[Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020](https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020)</sub> | <sub>Part of FinRL and provided code for paper [deep reinformacement learning for automated stock trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996) focuses on ensemble.</sub> | <sub>7/26/20 13:12</sub> | <sub>1/21/21 18:11</sub> | <sub>560.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
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| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>551.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |<!-- [PLACEHOLDER_END:deep_learning_and_reinforcement_learning] -->
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| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>551.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
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| <sub>[Neural Network](https://github.com/VivekPa/IntroNeuralNetworks)</sub> | <sub>Neural networks to predict stock prices.</sub> | <sub>9/10/18 6:34</sub> | <sub>11/21/18 7:39</sub> | <sub>489.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
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| <sub>[Deep Learning](https://github.com/keon/deepstock)</sub> | <sub>Technical experimentations to beat the stock market using deep learning.</sub> | <sub>12/12/16 2:15</sub> | <sub>3/4/17 8:37</sub> | <sub>427.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x4</sub> |
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| <sub>[LTSM Recurrent](https://github.com/VivekPa/AIAlpha)</sub> | <sub>OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.</sub> | <sub>10/7/18 3:58</sub> | <sub>8/3/19 9:00</sub> | <sub>1207.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x4</sub> |
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| <sub>[RL III](https://github.com/samre12/deep-trading-agent)</sub> | <sub>Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.</sub> | <sub>9/21/17 17:05</sub> | <sub>4/13/18 16:33</sub> | <sub>576.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x3</sub> |
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| <sub>[crypto-rl](https://github.com/sadighian/crypto-rl)</sub> | <sub>Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process)</sub> | <sub>6/21/18 1:06</sub> | <sub>11/5/20 11:08</sub> | <sub>347.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x3</sub> |<!-- [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> |
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|:-----------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
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| <sub>[Hands-On-Machine-Learning-for-Algorithmic-Trading](https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading)</sub> | <sub>repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have</sub> | <sub>5/7/19 11:04</sub> | <sub>1/19/21 7:51</sub> | <sub>600.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
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| <sub>[CryptoBot](https://github.com/AdeelMufti/CryptoBot)</sub> | <sub>Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained</sub> | <sub>1/17/17 12:44</sub> | <sub>1/17/17 12:48</sub> | <sub>234.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
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| <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> |
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| <sub>[awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance)</sub> | <sub>NEW</sub> | <sub>8/29/18 2:07</sub> | <sub>11/27/20 9:43</sub> | <sub>941.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Scikit-learn Stock Prediction](https://github.com/robertmartin8/MachineLearningStocks)</sub> | <sub>Using python and scikit-learn to make stock predictions.</sub> | <sub>2/12/17 4:50</sub> | <sub>2/4/21 3:48</sub> | <sub>931.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[AlphaPy](https://github.com/ScottfreeLLC/AlphaPy)</sub> | <sub>NEW</sub> | <sub>2/14/16 0:47</sub> | <sub>2/8/21 21:35</sub> | <sub>576.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[MathAndScienceNotes](https://github.com/melling/MathAndScienceNotes)</sub> | <sub>Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/)</sub> | <sub>3/11/16 19:13</sub> | <sub>12/21/20 3:54</sub> | <sub>460.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Fundamental LT Forecasts](https://github.com/Hvass-Labs/FinanceOps)</sub> | <sub>Research in investment finance for long term forecasts.</sub> | <sub>7/22/18 8:14</sub> | <sub>2/17/21 14:39</sub> | <sub>383.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[stock-trading-ml](https://github.com/yacoubb/stock-trading-ml)</sub> | <sub>NEW</sub> | <sub>10/10/19 9:44</sub> | <sub>10/12/19 11:38</sub> | <sub>340.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Mixture Models I](https://github.com/BlackArbsCEO/Mixture_Models)</sub> | <sub>Mixture models to predict market bottoms.</sub> | <sub>3/20/17 18:54</sub> | <sub>4/25/17 23:35</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END: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> |
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|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
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| <sub>[Hands-On-Machine-Learning-for-Algorithmic-Trading](https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading)</sub> | <sub>repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have</sub> | <sub>5/7/19 11:04</sub> | <sub>1/19/21 7:51</sub> | <sub>600.0</sub> | <sub>:heavy_check_mark:</sub> | <sub>:star:x5</sub> |
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| <sub>[CryptoBot](https://github.com/AdeelMufti/CryptoBot)</sub> | <sub>Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained</sub> | <sub>1/17/17 12:44</sub> | <sub>1/17/17 12:48</sub> | <sub>234.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub>:star:x2</sub> |
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| <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> |
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| <sub>[awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance)</sub> | <sub>NEW</sub> | <sub>8/29/18 2:07</sub> | <sub>11/27/20 9:43</sub> | <sub>941.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Scikit-learn Stock Prediction](https://github.com/robertmartin8/MachineLearningStocks)</sub> | <sub>Using python and scikit-learn to make stock predictions.</sub> | <sub>2/12/17 4:50</sub> | <sub>2/4/21 3:48</sub> | <sub>931.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[AlphaPy](https://github.com/ScottfreeLLC/AlphaPy)</sub> | <sub>NEW</sub> | <sub>2/14/16 0:47</sub> | <sub>2/8/21 21:35</sub> | <sub>576.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[MathAndScienceNotes](https://github.com/melling/MathAndScienceNotes)</sub> | <sub>Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/)</sub> | <sub>3/11/16 19:13</sub> | <sub>12/21/20 3:54</sub> | <sub>460.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Fundamental LT Forecasts](https://github.com/Hvass-Labs/FinanceOps)</sub> | <sub>Research in investment finance for long term forecasts.</sub> | <sub>7/22/18 8:14</sub> | <sub>2/17/21 14:39</sub> | <sub>383.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[stock-trading-ml](https://github.com/yacoubb/stock-trading-ml)</sub> | <sub>NEW</sub> | <sub>10/10/19 9:44</sub> | <sub>10/12/19 11:38</sub> | <sub>340.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Mixture Models I](https://github.com/BlackArbsCEO/Mixture_Models)</sub> | <sub>Mixture models to predict market bottoms.</sub> | <sub>3/20/17 18:54</sub> | <sub>4/25/17 23:35</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[finance_ml](https://github.com/jjakimoto/finance_ml)</sub> | <sub>NEW</sub> | <sub>6/29/18 21:21</sub> | <sub>2/18/19 12:34</sub> | <sub>282.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original](https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original)</sub> | <sub>NEW</sub> | <sub>11/15/19 8:51</sub> | <sub>1/21/21 7:56</sub> | <sub>279.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Machine-Learning-and-AI-in-Trading](https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading)</sub> | <sub>NEW</sub> | <sub>8/30/17 6:14</sub> | <sub>10/29/19 8:14</sub> | <sub>261.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[ML_Finance_Codes](https://github.com/mfrdixon/ML_Finance_Codes)</sub> | <sub>NEW</sub> | <sub>9/27/19 16:13</sub> | <sub>6/13/20 21:20</sub> | <sub>250.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[mlfinlab](https://github.com/hudson-and-thames/mlfinlab)</sub> | <sub>NEW</sub> | <sub>2/13/19 16:57</sub> | <sub>4/12/21 10:50</sub> | <sub>2295.0</sub> | <sub>:heavy_check_mark:</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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@@ -79,22 +89,31 @@ ___
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| <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>11/16/18 12:20</sub> | <sub>7/4/19 1:41</sub> | <sub>232.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt)</sub> | <sub>Financial portfolio optimisation, including classical efficient frontier and advanced methods.</sub> | <sub>5/29/18 13:30</sub> | <sub>2/25/21 13:01</sub> | <sub>1895.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <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>8/1/18 19:48</sub> | <sub>9/5/19 11:18</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>11/12/17 16:08</sub> | <sub>5/9/19 9:50</sub> | <sub>1281.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:portfolio_selection_and_optimisation] -->
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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>11/12/17 16:08</sub> | <sub>5/9/19 9:50</sub> | <sub>1281.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[riskparity.py](https://github.com/dppalomar/riskparity.py)</sub> | <sub>NEW</sub> | <sub>7/13/19 21:30</sub> | <sub>1/30/21 1:53</sub> | <sub>124.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
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| <sub>[Deep Portfolio Theory](https://github.com/tcloaa/Deep-Portfolio-Theory)</sub> | <sub>Autoencoder framework for portfolio selection.</sub> | <sub>2/10/17 9:03</sub> | <sub>3/8/18 16:47</sub> | <sub>105.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[Efficient Frontier](https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb)</sub> | <sub>Modern Portfolio Theory.</sub> | <sub>2/17/18 8:19</sub> | <sub>2/27/18 13:16</sub> | <sub>104.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
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| <sub>[node-finance](https://github.com/albertosantini/node-finance)</sub> | <sub>NEW</sub> | <sub>9/17/11 17:49</sub> | <sub>4/5/21 8:01</sub> | <sub>101.0</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] -->
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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>[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>[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>[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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| <sub>[Convex Optimisation](https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb)</sub> | <sub>Convex Optimization for Finance.</sub> | <sub>6/26/18 20:36</sub> | <sub>10/22/19 21:56</sub> | <sub>18.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END: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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|:--------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------|
|
||||
| <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> |
|
||||
| <sub>[Pyfolio](https://github.com/quantopian/pyfolio)</sub> | <sub>Portfolio and risk analytics in Python.</sub> | <sub>6/1/15 15:31</sub> | <sub>2/28/20 17:30</sub> | <sub>3673.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Quant Finance](https://github.com/mrefermat/quant_finance)</sub> | <sub>General quant repository.</sub> | <sub>8/11/18 22:59</sub> | <sub>11/12/19 4:49</sub> | <sub>31.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[CAPM](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb)</sub> | <sub>Expected returns using CAPM.</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Risk Basic](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb)</sub> | <sub>Active portfolio risk management .</sub> | <sub>5/10/16 11:03</sub> | <sub>5/17/16 3:44</sub> | <sub>31.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Factor Analysis](https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb)</sub> | <sub>Factor analysis for mutual funds.</sub> | <sub>3/13/18 7:39</sub> | <sub>3/13/18 7:42</sub> | <sub>3.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Statistical Finance](https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments)</sub> | <sub>Various financial experiments.</sub> | <sub>10/4/15 9:10</sub> | <sub>3/28/20 18:33</sub> | <sub>21.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <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> |
|
||||
| <sub>[Convex Optimisation](https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb)</sub> | <sub>Convex Optimization for Finance.</sub> | <sub>6/26/18 20:36</sub> | <sub>10/22/19 21:56</sub> | <sub>18.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Factor Analysis](https://github.com/alpha-miner/alpha-mind/tree/master/notebooks)</sub> | <sub>Factor strategy notebooks.</sub> | <sub>5/1/17 7:36</sub> | <sub>4/7/21 15:25</sub> | <sub>172.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[AlphaTrading](https://github.com/jerryxyx/AlphaTrading)</sub> | <sub>NEW</sub> | <sub>5/18/18 22:09</sub> | <sub>8/7/18 18:05</sub> | <sub>149.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Risk and Return](https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials)</sub> | <sub>Riskiness of portfolios and assets.</sub> | <sub>9/12/17 13:35</sub> | <sub>8/6/20 12:35</sub> | <sub>140.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[Python for Finance](https://github.com/yhilpisch/py4fi/tree/master/jupyter36)</sub> | <sub>Various financial notebooks.</sub> | <sub>12/15/14 11:23</sub> | <sub>7/10/18 6:38</sub> | <sub>1298.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Stock-Prediction](https://github.com/Ronak-59/Stock-Prediction)</sub> | <sub>NEW</sub> | <sub>3/18/18 4:54</sub> | <sub>2/28/20 11:43</sub> | <sub>129.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:factor_and_risk_analysis] -->
|
||||
|
||||
# Techniques
|
||||
## Unsupervised ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/unsupervised))
|
||||
@@ -126,18 +145,21 @@ ___
|
||||
# Other Assets
|
||||
## Derivatives and Hedging ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/derivatives_and_hedging))
|
||||
<!-- [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>2/9/16 5:30</sub> | <sub>4/6/21 20:49</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>10/21/16 4:12</sub> | <sub>2/22/21 13:32</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>6/6/18 22:06</sub> | <sub>6/6/18 22:27</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>7/9/15 12:27</sub> | <sub>2/22/21 13:29</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>7/28/17 15:48</sub> | <sub>3/17/21 17:17</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>3/2/18 23:53</sub> | <sub>7/17/18 23:32</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>5/22/18 18:27</sub> | <sub>5/22/18 18:30</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Computational Derivatives](https://github.com/chenbowen184/Computational_Finance)</sub> | <sub>Projects focusing on investigating simulations and computational techniques applied in finance.</sub> | <sub>1/29/18 5:01</sub> | <sub>8/2/18 5:56</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Reinforcement Learning](https://github.com/FinTechies/HedgingRL)</sub> | <sub>Hedging portfolios with reinforcement learning.</sub> | <sub>4/21/17 10:58</sub> | <sub>8/2/17 21:41</sub> | <sub>16.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END: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>2/9/16 5:30</sub> | <sub>4/6/21 20:49</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>10/21/16 4:12</sub> | <sub>2/22/21 13:32</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>6/6/18 22:06</sub> | <sub>6/6/18 22:27</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>7/9/15 12:27</sub> | <sub>2/22/21 13:29</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>7/28/17 15:48</sub> | <sub>3/17/21 17:17</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>3/2/18 23:53</sub> | <sub>7/17/18 23:32</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>5/22/18 18:27</sub> | <sub>5/22/18 18:30</sub> | <sub>2.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Computational Derivatives](https://github.com/chenbowen184/Computational_Finance)</sub> | <sub>Projects focusing on investigating simulations and computational techniques applied in finance.</sub> | <sub>1/29/18 5:01</sub> | <sub>8/2/18 5:56</sub> | <sub>17.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Reinforcement Learning](https://github.com/FinTechies/HedgingRL)</sub> | <sub>Hedging portfolios with reinforcement learning.</sub> | <sub>4/21/17 10:58</sub> | <sub>8/2/17 21:41</sub> | <sub>16.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Options Risk Measures](https://github.com/wanglouis49/risk_estimation)</sub> | <sub>Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).</sub> | <sub>4/29/16 3:51</sub> | <sub>1/16/18 1:24</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Black Scholes](https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb)</sub> | <sub>Options pricing.</sub> | <sub>12/9/17 18:50</sub> | <sub>7/9/18 9:48</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Derman](https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb)</sub> | <sub>Binomial tree for American call.</sub> | <sub>5/18/18 18:08</sub> | <sub>9/21/18 19:59</sub> | <sub>1.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:derivatives_and_hedging] -->
|
||||
|
||||
## Fixed Income ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/fixed_income))
|
||||
<!-- [PLACEHOLDER_START:fixed_income] -->
|
||||
@@ -173,7 +195,12 @@ ___
|
||||
| <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> |<!-- [PLACEHOLDER_END:extended_research] -->
|
||||
| <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>[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))
|
||||
<!-- [PLACEHOLDER_START:courses] -->
|
||||
@@ -203,7 +230,11 @@ ___
|
||||
| <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>[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> |<!-- [PLACEHOLDER_END:data] -->
|
||||
| <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> |
|
||||
| <sub>[Open Edgar](https://github.com/LexPredict/openedgar)</sub> | <sub>nan</sub> | <sub>5/7/18 15:32</sub> | <sub>5/15/19 8:32</sub> | <sub>169.0</sub> | <sub>:heavy_check_mark:</sub> | <sub></sub> |
|
||||
| <sub>[EDGAR](https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb)</sub> | <sub>nan</sub> | <sub>6/11/18 22:51</sub> | <sub>7/10/18 18:03</sub> | <sub>11.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |
|
||||
| <sub>[Employee Count SEC Filings](https://github.com/healthgradient/sec_employee_information_extraction)</sub> | <sub>nan</sub> | <sub>6/26/18 23:33</sub> | <sub>8/14/18 1:31</sub> | <sub>10.0</sub> | <sub>:heavy_multiplication_x:</sub> | <sub></sub> |<!-- [PLACEHOLDER_END:data] -->
|
||||
|
||||
# Colleges, Centers and Departments ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/colleges_centers_and_departments))
|
||||
<!-- [PLACEHOLDER_START:colleges_centers_and_departments] -->
|
||||
|
||||
Reference in New Issue
Block a user