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# Trading
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## Deep Learning ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Deep-Learning))
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## Deep Learning ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/deep_learning))
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- [Deep Learning](https://github.com/keon/deepstock) - Technical experimentations to beat the stock market using deep learning.
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- [Deep Learning II](https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks) - Tensorflow Regression.
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- [Deep Learning III](https://github.com/Rachnog/Deep-Trading) - Algorithmic trading with deep learning experiments.
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- [AI Trading](https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md) - AI to predict stock market movements.
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## Reinforcement Learning ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Reinforcement-Learning))
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## Reinforcement Learning ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/reinforcement_learning))
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- [RL Trading](https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW) - A collection of 25+ Reinforcement Learning Trading Strategies - Google Colab.
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- [RL](https://github.com/kh-kim/stock_market_reinforcement_learning) - OpenGym with Deep Q-learning and Policy Gradient.
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- [RL II](https://github.com/deependersingla/deep_trader) - reinforcement learning on stock market and agent tries to learn trading.
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- [RL V](https://github.com/gstenger98/rl-finance) - Building an Agent to Trade with Reinforcement Learning.
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- [Pair Trading RL](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading) - Using deep actor-critic model to learn best strategies in pair trading.
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## Other Models ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Other-Models))
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## Other Models ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/other_models))
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- [Mixture Models I](https://github.com/BlackArbsCEO/Mixture_Models) - Mixture models to predict market bottoms.
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- [Mixture Models II](https://github.com/BlackArbsCEO/mixture_model_trading_public) - Mixture models and stock trading.
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- [Scikit-learn Stock Prediction](https://github.com/robertmartin8/MachineLearningStocks) - Using python and scikit-learn to make stock predictions.
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- [Trend Following](http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html) - A futures trend following portfolio investment strategy.
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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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## Data Processing Techniques and Transformations ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/data_processing_techniques_and_transformations))
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- [Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises) - Exercises too Financial Machine Learning (De Prado).
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- [Advanced ML II](https://github.com/hudson-and-thames/research) - More implementations of Financial Machine Learning (De Prado).
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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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## Portfolio Selection and Optimisation ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/portfolio_selection_and_optimisation))
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- [Distribution Characteristic Optimisation](https://github.com/VivekPa/OptimalPortfolio) - Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.
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- [Reinforcement Learning](https://github.com/filangel/qtrader) - Reinforcement Learning for Portfolio Management.
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- [Efficient Frontier](https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb) - Modern Portfolio Theory.
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- [Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb) - Universal portfolios; modern portfolio theory.
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- [DeepDow](https://github.com/jankrepl/deepdow) - Portfolio optimization with deep learning.
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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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## Factor and Risk Analysis ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/factor_and_risk_analysis))
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- [Various Risk Measures](https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb) - Risk measures and factors for alternative and responsible investments.
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- [Pyfolio](https://github.com/quantopian/pyfolio) - Portfolio and risk analytics in Python.
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- [Risk Basic](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb) - Active portfolio risk management .
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# Techniques
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## Unsupervised ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Unsupervised))
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## Unsupervised ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/unsupervised))
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- [PCA Pairs Trading](https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading) - PCA, Factor Returns, and trading strategies.
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- [Fund Clusters](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb) - Data exploration of fund clusters.
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- [VRA Stock Embedding](https://github.com/ml-hongkong/stock2vec) - Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.
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- [Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries) - Project to cluster industries according to financial attributes.
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## Textual ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Textual))
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## Textual ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/textual))
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- [NLP](https://github.com/toamitesh/NLPinFinance) - This project assembles a lot of NLP operations needed for finance domain.
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- [Earning call transcripts](https://github.com/lin882/WebAnalyticsProject) - Correlation between mutual fund investment decision and earning call transcripts.
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- [Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds) - Return performance and mutual fund selection.
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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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## Derivatives and Hedging ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/derivatives_and_hedging))
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- [Options](https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D) - Introduction to options.
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- [Derivative Markets](https://github.com/broughtj/Fin6470/tree/master/Notebooks) - The economics of futures, futures, options, and swaps.
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- [Black Scholes](https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb) - Options pricing.
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- [Derman](https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb) - Binomial tree for American call.
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- [Hull White](https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb) - Callable Bond, Hull White.
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## Fixed Income ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Fixed-Income))
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## Fixed Income ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/fixed_income))
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- [Vasicek](https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb) - Bootstrapping and interpolation.
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- [Binomial Tree](https://github.com/hy-lei/math-finance-exercise) - Utility functions in fixed income securities.
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- [Corporate Bonds](https://github.com/ishank011/gs-quantify-bond-prediction) - Predicting the buying and selling volume of the corporate bonds.
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## Alternative Finance ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Alternative-Finance))
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## Alternative Finance ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/alternative_finance))
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- [Kiva Crowdfunding](https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb) - Exploratory data analysis.
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- [Venture Capital](https://github.com/julian-chan/etothex) - Insight into a new founder to make data-driven investment decisions.
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- [Venture Capital NN](https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring) - Cox-PH neural network predictions for VC/innovations finance research.
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- [Art Valuation](https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb) - Art evaluation analytics.
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- [Blockchain](https://github.com/nud3l/dInvest) - Repository for distributed autonomous investment banking.
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# Extended Research ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Extended-Research))
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# Extended Research ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/extended_research))
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- [HFT](https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy) - High frequency trading.
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- [Deep Portfolio](https://github.com/DLColumbia/DL_forFinance) - Deep learning for finance Predict volume of bonds.
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- [Mathematical Finance](https://github.com/Auquan/Tutorials) - Notebooks for math and financial tutorials.
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- [Liquidity and Momentum](https://github.com/mrefermat/quant_finance) - Various factors and portfolio constructions.
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# Courses ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Courses))
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# Courses ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/courses))
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- [Mathematical Finance](https://github.com/yadongli/nyumath2048) - NYU Math-GA 2048: Scientific Computing in Finance.
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- [Algo Trading](https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading) - Intro to algo trading.
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- [Python for Finance](https://github.com/siaen/python_finance_course) - CEU python for finance course material.
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- [Basic Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance) - Source code notebooks basic finance applications.
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# Data ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/Data))
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# Data ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/data))
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- [Capital Markets Data](https://www.capitalmarketsdata.com/) (and [chartpack](https://1drv.ms/b/s!AjyO2n0JmhakhJIy-jZXLsLGxOw38Q?e=uOuPKY))
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- [Employee Count SEC Filings](https://github.com/healthgradient/sec_employee_information_extraction)
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- [SEC Parsing](https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb)
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- [https://github.com/timestocome/StockMarketData](https://github.com/timestocome/StockMarketData)
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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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# Colleges, Centers and Departments ([Wiki](https://github.com/firmai/financial-machine-learning/wiki/colleges_centers_and_departments))
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- [NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering) - Finance and Risk Engineering (NYU Tandon)
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- [Cornell University](https://www.cornell.edu/)
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- [NYU Courant](https://cims.nyu.edu/) - Courant Institute of Mathematical Sciences, New York University
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