financial-machine-learning/README.md

FirmAI Finance II

Trading

Deep Learning

• Deep Learning - https://github.com/keon/deepstock
• Deep Learning II - https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks
• Deep Learning III - https://github.com/Rachnog/Deep-Trading
• Deep Learning IV - https://github.com/achillesrasquinha/bulbea
• Deep Learning V - https://github.com/keon/deepstock
• LTSM GRU — https://github.com/RajatHanda/Finance-Forecasting
• Time Series Stock Prediction - Using an LTSM model to predict future changes in the stock price.
• Time Series Stock Prediction - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
• Neural Network - https://github.com/VivekPa/IntroNeuralNetworks - Neural networks to predict stock prices

Reinforcement Learning

• Reinforcement Learning - https://github.com/kh-kim/stock_market_reinforcement_learning
• Reinforcement Learning II - https://github.com/deependersingla/deep_trader
• Reinforcement Learning II - https://github.com/samre12/deep-trading-agent - Github
• RL III - https://github.com/deependersingla/deep_trader
• RL IV - https://github.com/jjakimoto/DQN
• Pair Trading RL - https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading
• RL VI - https://github.com/gstenger98/rl-finance

Other Models

• Mixture Models I - https://github.com/BlackArbsCEO/Mixture_Models
• Mixture Models II - https://github.com/BlackArbsCEO/mixture_model_trading_public
• Scikit-learn Stock Prediction - https://github.com/robertmartin8/MachineLearningStocks
• Fundamental LT Forecasts - https://github.com/Hvass-Labs/FinanceOps
• Short-Term Movement Cues - https://github.com/anfederico/Clairvoyant

Data Processing

• Advanced ML - https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises - Exercises too Financial Machine Learning (De Prado).
• Advanced ML II - https://github.com/hudson-and-thames/research - More implementations of Financial Machine Learning (De Prado).

Portfolio Selection and Optimisation

• Distribution Characteristic Optimisation - Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.
• Reinforcement Learning - https://github.com/filangel/qtrader
• Efficient Frontier - https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb
• Policy Gradient Portfolio - https://github.com/ZhengyaoJiang/PGPortfolio
• Deep Portfolio Theory - https://github.com/tcloaa/Deep-Portfolio-Theory
• 401K Portfolio Optimisation - https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb

Online Portfolio

• https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynbhttps://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb
• OLMAR - https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb

Factor and Risk Analysis:

• https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb
• Pyfolio - https://github.com/quantopian/pyfolio
• Risk Basic - https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb
• CAPM - https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb
• Factor Analysis - https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb - Factor analysis for mutual funds.
• VaR GaN - Estimate Value-at-Risk for market risk management using Keras and TensorFlow.
• VaR - https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb
• Python for Finance - https://github.com/yhilpisch/py4fi/tree/master/jupyter36
• Mathematical Finance - https://github.com/Auquan/Tutorials
• Performance Analysis - https://github.com/quantopian/alphalens
• Quant Finance - https://github.com/mrefermat/quant_finance
• Risk and Return - https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials
• Convex Optimisation - https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb
• Factor Analysis - https://github.com/alpha-miner/alpha-mind/tree/master/notebooks
• Quant Factors - https://github.com/mrefermat/quant_finance

Derivatives and Hedging:

• Options - https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D
• Derivative Markets: https://github.com/broughtj/Fin6470/tree/master/Notebooks
• Black Scholes - https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb
• Computational Derivatives - https://github.com/chenbowen184/Computational_Finance
• Reinforcement Learning - Hedging portfolios with reinforcement learning.
• Delta Hedging - https://github.com/RobinsonGarcia/delta-hedging
• Options Risk Measures - https://github.com/wanglouis49/risk_estimation
• Pairs Trading - https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb
• Derivatives Python - https://github.com/yhilpisch/dawp/tree/master/python36
• Volatility and Variance Derivatives - https://github.com/yhilpisch/lvvd/tree/master/lvvd
• Options - https://github.com/PHBS/2018.M1.ASP/tree/master/py
• Statistical Finance - https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments
• Option Strategies - https://github.com/rstreppa/valuation-OptionStrategies
• Derman - https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb
• Hull White - https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb

Unsupervised:

• PCA - https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading
• Fund Clusters - https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb
• Fund and Broker Clusters - https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb
• VRA Stock Embedding - https://github.com/ml-hongkong/stock2vec
• Industry Clustering - https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries

Textual:

• 10-K Keywords extraction
• NLP - https://github.com/toamitesh/NLPinFinance
• Earning call transcripts - Correlation between mutual fund investment decision and earning call transcripts.
• Buzzwords - Return performance and mutual fund selection.
• Fund classification - Fund classification using text mining and NLP.
• NLP Event - https://github.com/yuriak/DLQuant
• Financial Sentiment Analysis - Sentiment, distance and proportion analysis for trading signals.
• Extensive NLP - Comprehensive NLP techniques for accounting research.
• Accounting Anomalies - Using deep-learning frameworks to identify accounting anomalies.

Fixed Income

• Vasicek - https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb
• Black Derman - https://github.com/RobinsonGarcia/fixed-income/blob/master/1.0%20Black%20Derman%20Toy.ipynb
• Binomial Tree - https://github.com/hy-lei/math-finance-exercise

Alternative Finance

• Kiva Crowdfunding - Exploratory data analysis.
• Venture Capital - https://github.com/julian-chan/etothex
• Venture Capital NN - https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring
• Private Equity - https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb
• VC OLS - https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb
• Watch Valuation - https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb
• Art Valuation - https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb
• Blockchain - https://github.com/nud3l/dInvest

Extended Research:

• HFT - https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy - High frequency trading
• Commodity - https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb
• Quant Finance - https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading
• Finance Graph Theory - https://github.com/AvijitGhosh82/Finance_Graph_Theory
• Computational Finance - https://github.com/hyeukjung93/Computational-Methods-in-Finance
• Real Estate Property Fraud - https://github.com/aviroop1/Real_Estate_Property_Fraud
• Behavioural Economics - https://github.com/pcmichaud/notebooks
• Bayesian Finance - https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb
• Bayesian Finance - https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb
• Currency PCA - https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipyn
• Backtests - https://github.com/AlgoTraders/stock-analysis-engine
• High Frequency - https://github.com/cswaney/prickle
• Financial Economics - https://github.com/rsvp/fecon235/tree/master/nb
• Critical Transitions - https://github.com/ryanholbrook/critical-transitions
• Economic Foundations - https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations
• Corporate Finance - https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance
• M&A- https://github.com/atulram/Finance-and-Stocks
• Lifecycle - https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb
• Computational Finance - https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance
• Liquidity and Momentum - https://github.com/mrefermat/quant_finance/stargazers
• Meta labeling and signal efficacy - https://github.com/hudson-and-thames/presentations/blob/master/Does%20Meta%20Labeling%20Add%20to%20Signal%20Efficacy.pdf
• Good AFML notes: http://reasonabledeviations.science/notes/adv_fin_ml/
• Good Blockchain Notes - http://reasonabledeviations.science/notes/princeton_bitcoin/
• Quantopian Lecture Notes - http://reasonabledeviations.science/notes/quantopian_lectures/
• http://www.unofficialgoogledatascience.com/2017/04/our-quest-for-robust-time-series.html How Google does series predictions

Data

• Employee Count SEC Filings
• SEC Parsing
• Open Edgar
• EDGAR - A walk-through in how to obtain EDGAR data.
• IRS - Accessing and parsing IRS filings.
• Rating Industries
• Web Scraping (FirmAI) - Web scraping solutions for Facebook, Glassdoor, Instagram, Morningstar, Similarweb, Yelp, Spyfu, Linkedin, Angellist.
• Financial Corporate - Rutgers corporate financial datasets.
• Non-financial Corporate - Rutgers non-financial corporate dataset.
• http://finance.yahoo.com/
• https://fred.stlouisfed.org/
• https://stooq.com
• https://github.com/timestocome/StockMarketData

Courses

• Mathematical Finance - https://github.com/yadongli/nyumath2048
• Algo Trading - https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading
• Python for Finance - https://github.com/siaen/python_finance_course
• Handson Python for Finance - https://github.com/PacktPublishing/Hands-on-Python-for-Finance
• Machine Learning for Trading (Good) - https://github.com/stefan-jansen/machine-learning-for-trading
• ML Specialisation - https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization
• Risk Management - Finance risk engagement course resources.