| repo | comment | created_at | last_commit | star_count | repo_status | rating | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------------|:------------------------------------|:--------------------| | [Hands-On-Machine-Learning-for-Algorithmic-Trading](https://github.com/PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading) | repo for book [hands-on-machine learning for algorithmic trading](https://www.packtpub.com/product/hands-on-machine-learning-for-algorithmic-trading/9781789346411) covering topic from data/unsupervised learning/NPL/RNN & CNN/reinforcement learning etc. Leverage zipline/alphalens/sklearn/openai-gym etc as well. Good references to have | 5/7/19 11:04 | 1/19/21 7:51 | 600.0 | :heavy_check_mark: | :star:x5 | | [Awesome-Quant-Machine-Learning-Trading](https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading) | curated list of books/online courses/youtube videos/blogs/interviews/papers/code etc. Updates are pretty infrequent | 11/5/18 21:09 | 10/8/20 16:48 | 1005.0 | :heavy_check_mark: | :star:x5 | | [AlphaPy](https://github.com/ScottfreeLLC/AlphaPy) | machine learning framework built on sklearn and pandas. Support pyfolio/xgboost/lightgmb/catboost(gradient boosting on decision tress) etc. Examples include financial market prediction/sports prediction/kaggle. Configurations are set though yaml file for all model process including feature selection/grid search on parameters and aggregate results for each model | 2/14/16 0:47 | 2/8/21 21:35 | 576.0 | :heavy_check_mark: | :star:x4 | | [Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original](https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original) | official repo for [machine learning for algorithmic trading](https://www.amazon.com/Machine-Learning-Algorithmic-Trading-alternative/dp/1839217715?pf_rd_r=GZH2XZ35GB3BET09PCCA&pf_rd_p=c5b6893a-24f2-4a59-9d4b-aff5065c90ec&pd_rd_r=91a679c7-f069-4a6e-bdbb-a2b3f548f0c8&pd_rd_w=2B0Q0&pd_rd_wg=GMY5S&ref_=pd_gw_ci_mcx_mr_hp_d) book. Covering topics including backtesting/boosting/nlp/deep&reinforcement learning. Leverage open source libraries including [backtrader](https://www.backtrader.com/) [zipline](https://github.com/quantopian/zipline) and [talib](https://github.com/mrjbq7/ta-lib) | 11/15/19 8:51 | 1/21/21 7:56 | 279.0 | :heavy_check_mark: | :star:x4 | | [Scikit-learn Stock Prediction](https://github.com/robertmartin8/MachineLearningStocks) | using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained | 2/12/17 4:50 | 2/4/21 3:48 | 931.0 | :heavy_multiplication_x: | :star:x3 | | [MathAndScienceNotes](https://github.com/melling/MathAndScienceNotes) | Collections of news/articles on various topics including quant trading and machine learning. Some articles are from [ycombinator message board](https://news.ycombinator.com/news) and [rediit algotrading forum](https://www.reddit.com/r/algotrading/) | 3/11/16 19:13 | 12/21/20 3:54 | 460.0 | :heavy_check_mark: | :star:x3 | | [stock-trading-ml](https://github.com/yacoubb/stock-trading-ml) | lstm model using keras to predict msft prices. Data is from [alphavantage](https://www.alphavantage.co/) which provides some free data through web services. Showing how to use concatenation layer to join timeseries data with TA data. Might be abit of overfitting on the model though | 10/10/19 9:44 | 10/12/19 11:38 | 340.0 | :heavy_check_mark: | :star:x3 | | [ML_Finance_Codes](https://github.com/mfrdixon/ML_Finance_Codes) | accompanying materials for book [Machine Learning in Finance](https://www.springer.com/gp/book/9783030410674) covering probabilistic modeling/sequence modeling/neural networks/reinforcement learning etc. | 9/27/19 16:13 | 6/13/20 21:20 | 250.0 | :heavy_check_mark: | :star:x3 | | [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) | open source library maintained by hudson and thames though much of the content has moved to a subscription model. Idea is to implement academic research in python code and aggregate it as a package. Sources from [Journal of financial data science](https://jfds.pm-research.com/) / [journal of portfolio management](https://jpm.pm-research.com/) / [journal of algorithmic finance](http://www.algorithmicfinance.org/) / [cambridge university press](https://www.cambridge.org/) | 2/13/19 16:57 | 4/12/21 10:50 | 2295.0 | :heavy_check_mark: | :star:x3 | | [mosquito](https://github.com/miro-ka/mosquito) | base framework trading bot for crypto. Stores data in local mongodb instance and supports backtest and live trading on [poloniex](https://poloniex.com/) and [bittrex](https://bittrex.com/) which are 12-15th ranked crypto exchanges by volume. Leverage [talib](https://github.com/mrjbq7/ta-lib) for ta data and [plotly](https://github.com/plotly/plotly.py) for visualization | 6/18/17 19:57 | 3/14/21 22:22 | 220.0 | :heavy_check_mark: | :star:x3 | | [surpriver](https://github.com/tradytics/surpriver) | Machine learning algo to detect anomaly in equities data. Uses sklearn [IsolationForest](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html) model and price/volume based technical signals as features using [ta](https://github.com/bukosabino/ta) library. Opensourced by [tradytics](https://tradytics.com/). Code structures are less extensible | 8/30/20 7:56 | 9/21/20 4:32 | 1189.0 | :heavy_check_mark: | :star:x3 | | [Mixture Models I](https://github.com/BlackArbsCEO/Mixture_Models) | Mixture models to predict market bottoms and regime changes based on a seminar given to quantinsti in 2017 and summary and video is [here](https://blog.quantinsti.com/webinar-can-we-use-mixture-models-to-predict-market-bottoms/). Gaussian mixture models are build on markov models and expectation maximization thoery to detect regimes and seminar reported positive results using features asset returns/tedrate/10y2ysptread/10y3m spread from fred which can be access here [fredapi](https://github.com/mortada/fredapi). Though most of the returns came from being long equities after 2009 | 3/20/17 18:54 | 4/25/17 23:35 | 31.0 | :heavy_multiplication_x: | :star:x2 | | [CryptoBot](https://github.com/AdeelMufti/CryptoBot) | Hard fork of [bitpredit](https://github.com/cbyn/bitpredict) and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are XGBClassifier/RandomForest/GradientBoosting. Not mentained | 1/17/17 12:44 | 1/17/17 12:48 | 234.0 | :heavy_multiplication_x: | :star:x2 | | [Machine-Learning-For-Finance](https://github.com/anthonyng2/Machine-Learning-For-Finance) | accompanying materials for slide [here](https://github.com/anthonyng2/Machine-Learning-For-Finance/blob/master/Regression%20Based%20Machine%20Learning%20for%20Algorithmic%20Trading/Machine%20Learning%20-%20Linear%20Regression%20for%20Algo%20Trading%20v2017-07-13.pdf) covering more tradition quant trading topics like pair trading/kalman filter/trend following etc. Referecing interesting paper [characterization of financial time series](http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/RN_11_01.pdf) | 7/11/17 9:09 | 2/21/18 5:36 | 205.0 | :heavy_multiplication_x: | :star:x2 | | [Pattern-Recognition-for-Forex-Trading](https://github.com/PythonProgramming/Pattern-Recognition-for-Forex-Trading) | NEW | 3/26/15 2:22 | 3/26/15 2:33 | 173.0 | :heavy_multiplication_x: | :star:x2 | | [botflow](https://github.com/kkyon/botflow) | python dataflow programming framework. Similar and probably replaceable by sklearn.pipeline module. Uses [graphviz](https://graphviz.org/) for visiualization though not maintained with last commit over 3 years ago | 8/20/18 3:13 | 5/23/19 14:40 | 1165.0 | :heavy_multiplication_x: | :star:x2 | | [Trend Following](http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html) | A futures trend following portfolio investment strategy. | nan | nan | nan | :heavy_check_mark: | | | [awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance) | NEW | 8/29/18 2:07 | 11/27/20 9:43 | 941.0 | :heavy_check_mark: | | | [Fundamental LT Forecasts](https://github.com/Hvass-Labs/FinanceOps) | Research in investment finance for long term forecasts. | 7/22/18 8:14 | 2/17/21 14:39 | 383.0 | :heavy_check_mark: | | | [finance_ml](https://github.com/jjakimoto/finance_ml) | NEW | 6/29/18 21:21 | 2/18/19 12:34 | 282.0 | :heavy_multiplication_x: | | | [Machine-Learning-and-AI-in-Trading](https://github.com/PyPatel/Machine-Learning-and-AI-in-Trading) | NEW | 8/30/17 6:14 | 10/29/19 8:14 | 261.0 | :heavy_check_mark: | | | [Short-Term Movement Cues](https://github.com/anfederico/Clairvoyant) | Identify social/historical cues for short term stock movement. | 9/12/16 18:38 | 8/29/18 20:27 | 2166.0 | :heavy_multiplication_x: | | | [Machine-Learning-for-Finance](https://github.com/PacktPublishing/Machine-Learning-for-Finance) | NEW | 3/15/18 6:28 | 1/14/21 15:58 | 180.0 | :heavy_check_mark: | | | [Stock.Indicators](https://github.com/DaveSkender/Stock.Indicators) | NEW | 12/29/19 5:18 | 4/11/21 19:17 | 175.0 | :heavy_check_mark: | | | [Machine-Learning-for-Algorithmic-Trading-Bots-with-Python](https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python) | NEW | 12/6/18 11:35 | 1/18/21 6:40 | 172.0 | :heavy_check_mark: | | | [Mixture Models II](https://github.com/BlackArbsCEO/mixture_model_trading_public) | Mixture models and stock trading. | 12/11/17 17:05 | 5/13/20 23:50 | 166.0 | :heavy_check_mark: | | | [fin-ml](https://github.com/tatsath/fin-ml) | NEW | 5/10/20 0:25 | 1/23/21 17:15 | 116.0 | :heavy_check_mark: | | | [Microservices-Based-Algorithmic-Trading-System](https://github.com/saeed349/Microservices-Based-Algorithmic-Trading-System) | NEW | 1/6/20 0:21 | 3/31/20 13:02 | 104.0 | :heavy_check_mark: | | | [Speculator](https://github.com/amicks/Speculator) | NEW | 9/3/17 17:43 | 9/12/18 18:58 | 101.0 | :heavy_multiplication_x: | |