Python中实用金融机器学习（FinML）工具和应用程序的精选列表

python中实用金融机器学习（FinML）工具和应用程序的精选列表

Financial Machine Learning and Data Science

A curated list of practical financial machine learning (FinML) tools and applications. This collection is primarily in Python.

If you want to contribute to this list (please do), send me a pull request or contact me @dereknow or on linkedin. Also, a listed repository should be deprecated if:

Repository's owner explicitly say that "this library is not maintained".Not committed for long time (2~3 years).

Trading

Deep Learning

Deep Learning - Technical experimentations to beat the stock market using deep learning.Deep Learning II - Tensorflow Regression.Deep Learning III - Algorithmic trading with deep learning experiments.Deep Learning IV - Bulbea: Deep Learning based Python Library.LTSM GRU - Stock Market Forecasting using LSTM\GRU.Multilayer neural network architecture for stock return prediction. LTSM Recurrent - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.ARIMA-LTSM Hybrid - Hybrid model to predict future price correlation coefficients of two assets.Neural Network - Neural networks to predict stock prices.AI Trading - AI to predict stock market movements.

Reinforcement Learning

RL Trading - A collection of 25+ Reinforcement Learning Trading Strategies - Google Colab.RL - OpenGym with Deep Q-learning and Policy Gradient.RL II - reinforcement learning on stock market and agent tries to learn trading.RL III - Github - Deep Reinforcement Learning based Trading Agent for Bitcoin.RL IV - Reinforcement Learning for finance.RL V - Building an Agent to Trade with Reinforcement Learning.Pair Trading RL - Using deep actor-critic model to learn best strategies in pair trading.

Other Models

Mixture Models I - Mixture models to predict market bottoms.Mixture Models II - Mixture models and stock trading.Scikit-learn Stock Prediction - Using python and scikit-learn to make stock predictions.Fundamental LT Forecasts - Research in investment finance for long term forecasts.Short-Term Movement Cues - Identify social/historical cues for short term stock movement.Trend Following - A futures trend following portfolio investment strategy.

Data Processing Techniques and Transformations

Advanced ML - Exercises too Financial Machine Learning (De Prado).Advanced ML II - More implementations of Financial Machine Learning (De Prado).

Portfolio Management

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 - Reinforcement Learning for Portfolio Management.Efficient Frontier - Modern Portfolio Theory.Policy Gradient Portfolio - A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.Deep Portfolio Theory - Autoencoder framework for portfolio selection.401K Portfolio Optimisation - Portfolio analyses and optimisation for 401K.Online Portfolio Selection - ****Comparing OLPS algorithms on a diversified set of ETFs.OLMAR Algorithm - Relative importance of each component of the OLMAR algorithm.Modern Portfolio Theory - Universal portfolios; modern portfolio theory.

Factor and Risk Analysis:

Various Risk Measures - Risk measures and factors for alternative and responsible investments.Pyfolio - Portfolio and risk analytics in Python.Risk Basic - Active portfolio risk management .CAPM - Expected returns using CAPM.Factor Analysis - Factor analysis for mutual funds.VaR GaN - Estimate Value-at-Risk for market risk management using Keras and TensorFlow.VaR - Value-at-risk calculations.Python for Finance - Various financial notebooks.Performance Analysis - Performance analysis of predictive (alpha) stock factors.Quant Finance - General quant repository.Risk and Return - Riskiness of portfolios and assets.Convex Optimisation - Convex Optimization for Finance.Factor Analysis - Factor strategy notebooks.Statistical Finance - Various financial experiments.

Techniques

Unsupervised:

PCA Pairs Trading - PCA, Factor Returns, and trading strategies.Fund Clusters - Data exploration of fund clusters.VRA Stock Embedding - Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.Industry Clustering - Clustering of industries.Pairs Trading - Finding pairs with cluster analysis.Industry Clustering - Project to cluster industries according to financial attributes.

Textual:

NLP - This project assembles a lot of NLP operations needed for finance domain.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 - Applying Deep Learning and NLP in Quantitative Trading.Financial Sentiment Analysis - Sentiment, distance and proportion analysis for trading signals.Financial Statement Sentiment - Extracting sentiment from financial statements using neural networks.Extensive NLP - Comprehensive NLP techniques for accounting research.Accounting Anomalies - Using deep-learning frameworks to identify accounting anomalies.

Other Assets

Derivatives and Hedging:

Options - Introduction to options.Derivative Markets - The economics of futures, futures, options, and swaps.Black Scholes - Options pricing.Computational Derivatives - Projects focusing on investigating simulations and computational techniques applied in finance.Reinforcement Learning - Hedging portfolios with reinforcement learning.Delta Hedging - Advanced derivatives.Options Risk Measures - Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).Derivatives Python - Derivative analytics with Python.Volatility and Variance Derivatives - Volatility derivatives analytics.Options - Black Scholes and Copula.Option Strategies - Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.Derman - Binomial tree for American call.Hull White - Callable Bond, Hull White.

Fixed Income

Vasicek - Bootstrapping and interpolation.Binomial Tree - Utility functions in fixed income securities.Corporate Bonds - Predicting the buying and selling volume of the corporate bonds.

Alternative Finance

Kiva Crowdfunding - Exploratory data analysis.Venture Capital - Insight into a new founder to make data-driven investment decisions.Venture Capital NN - Cox-PH neural network predictions for VC/innovations finance research.Private Equity - Valuation models.VC OLS - VC regression.Watch Valuation - Analysis of luxury watch data to classify whether a certain model is likely to be over- or undervalued.Art Valuation - Art evaluation analytics.Blockchain - Repository for distributed autonomous investment banking.

Extended Research:

HFT - High frequency trading.Deep Portfolio - Deep learning for finance Predict volume of bonds.Mathematical Finance - Notebooks for math and financial tutorials.NLP Finance Papers - Curating quantitative finance papers using machine learning.Simulation - Investigating simulations as part of computational finance.Market Crash Prediction - Predicting market crashes using an LPPL model.Commodity - Commodity influence over Brazilian stocks.Finance Graph Theory - Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.Real Estate Property Fraud - Unsupervised fraud detection model that can identify likely candidates of fraud.Behavioural Economics - Behavioural Economics and Finance Python Notebooks.Bayesian Finance - Notebook PyMC3 implementation.Bayesian Finance I - Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs.Currency PCA - Forex spots PCA.Backtests - Trading data and algorithms.High Frequency - A Python toolkit for high-frequency trade research.Financial Economics - Financial Economics Models.Critical Transitions - Detecting critical transitions in financial networks with topological data analysis.Economic Foundations - Basic economic models.Corporate Finance - Basic corporate finance.Applied Corporate Finance - Studies the empirical behaviours in stock market.M&A - Mergers and Acquisitions.Life-cycle - Company life cycle.Computational Finance - Applied Computational Economics and Finance.Liquidity and Momentum - Various factors and portfolio constructions.

Courses

Mathematical Finance - NYU Math-GA 2048: Scientific Computing in Finance.Algo Trading - Intro to algo trading.Python for Finance - CEU python for finance course material.Handson Python for Finance - Hands-on Python for Finance published by Packt.Machine Learning for Trading - Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading.ML Specialisation - Machine Learning in Finance.Risk Management - Finance risk engagement course resources.Basic Investments - Basic investment tools in python.Basic Derivatives - Basic forward contracts and hedging.Basic Finance - Source code notebooks basic finance applications.

Data

Employee Count SEC FilingsSEC ParsingOpen EdgarEDGARIRSRating IndustriesWeb Scraping (FirmAI)Financial CorporateNon-financial Corporatehttp://finance.yahoo.com/https://fred.stlouisfed.org/https://stooq.comhttps://github.com/timestocome/StockMarketData

Personal Papers

Financial Event Prediction using Machine LearningMachine Learning in Asset Management—Part 1: Portfolio Construction—Trading StrategiesMachine Learning in Asset Management—Part 2: Portfolio Construction—Weight OptimizationMachine Learning in Asset Management

Colleges, Centers and Departments

NYU FRECornell UniversityCourant NYUOxford ManStanford Advanced Financial TechnologiesBerkley CIFT

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