From e853c169bd5e8eed1a1f065b1f54d263eb00067c Mon Sep 17 00:00:00 2001 From: Derek Snow Date: Thu, 21 Mar 2019 21:09:15 +0000 Subject: [PATCH] Add files via upload --- FirmAI_Finance_II (1).md | 177 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 177 insertions(+) create mode 100644 FirmAI_Finance_II (1).md diff --git a/FirmAI_Finance_II (1).md b/FirmAI_Finance_II (1).md new file mode 100644 index 0000000..f81ff18 --- /dev/null +++ b/FirmAI_Finance_II (1).md @@ -0,0 +1,177 @@ +# 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](https://github.com/VivekPa/AIAlpha) - Using an LTSM model to predict future changes in the stock price. +- [Time Series Stock Prediction](https://github.com/NourozR/Stock-Price-Prediction-LSTM) - 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](https://github.com/VivekPa/OptimalPortfolio) - 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](https://github.com/hamaadshah/market_risk_gan_keras) - 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](https://github.com/FinTechies/HedgingRL) - 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](https://github.com/lin882/WebAnalyticsProject) - Correlation between mutual fund investment decision and earning call transcripts. +- [Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds) - Return performance and mutual fund selection. +- [Fund classification](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb) - Fund classification using text mining and NLP. +- NLP Event - https://github.com/yuriak/DLQuant +- [Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis) - Sentiment, distance and proportion analysis for trading signals. +- [Extensive NLP](https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb) - Comprehensive NLP techniques for accounting research. +- [Accounting Anomalies](https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb) - 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](https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb) - Exploratory data analysis. +- [Venture Capital](https://github.com/julian-chan/etothex) - 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](http://www.unofficialgoogledatascience.com/2017/04/our-quest-for-robust-time-series.html) How Google does series predictions + + + +# Data +- [Employee Count SEC Filings](https://github.com/healthgradient/sec_employee_information_extraction) +- [SEC Parsing](https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb) +- [Open Edgar](https://github.com/LexPredict/openedgar) +- [EDGAR](https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb) - A walk-through in how to obtain EDGAR data. +- [IRS](http://social-metrics.org/sox/) - Accessing and parsing IRS filings. +- [Rating Industries](http://www.ratingshistory.info/) +- [Web Scraping (FirmAI)](https://github.com/firmai/business-machine-learning/blob/master/www.firmai.org/data) - Web scraping solutions for Facebook, Glassdoor, Instagram, Morningstar, Similarweb, Yelp, Spyfu, Linkedin, Angellist. +- [Financial Corporate](http://raw.rutgers.edu/Corporate%20Financial%20Data.html) - Rutgers corporate financial datasets. +- [Non-financial Corporate](http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html) - Rutgers non-financial corporate dataset. +- [http://finance.yahoo.com/](http://finance.yahoo.com/) +- [https://fred.stlouisfed.org/](https://fred.stlouisfed.org/) +- [https://stooq.com](https://stooq.com) +- [https://github.com/timestocome/StockMarketData](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](https://github.com/andrey-lukyanov/Risk-Management) - Finance risk engagement course resources. +