TODOs and roadmap is under the github project here
If you would like to contribute to this repo, please send us a pull request or contact @dereknow or @bin-yang-algotune
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All repos/links status including last commit date is updated weekly
10 Highest ranked repos/links for each section are displayed on main README.md and full list is available within the wiki page
Both Wikis/README.md is updated in realtime as soon as new information are pushed to the repo

Trading

Deep Learning (Wiki)

_repo	_comment	_{created_at}	_{last_commit}	_{star_count}	_{repo_status}	_rating
_{Stock-Prediction-Models}	_NEW	_{12/18/17 10:49}	_{1/5/21 10:31}	_3584.0	_✔️	_:star:x5
_{AI Trading}	_{AI to predict stock market movements.}	_{1/9/19 8:02}	_{2/11/19 16:32}	_2852.0	_✖️	_:star:x5
_{FinRL-Library}	_NEW	_{7/26/20 13:18}	_{3/28/21 13:46}	_1780.0	_✔️	_:star:x5
_{Deep Learning IV}	_{Bulbea: Deep Learning based Python Library.}	_{3/9/17 6:11}	_{3/19/17 7:42}	_1448.0	_✔️	_:star:x5
_RLTrader	_NEW	_{4/27/19 18:35}	_{10/17/19 16:25}	_1300.0	_✔️	_:star:x5
_{Deep Learning III}	_{Algorithmic trading with deep learning experiments.}	_{6/18/16 18:23}	_{8/7/18 15:24}	_1262.0	_✖️	_:star:x5
_Personae	_NEW	_{3/10/18 11:22}	_{9/2/18 17:21}	_1142.0	_✖️	_:star:x5
_{Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020}	_NEW	_{7/26/20 13:12}	_{1/21/21 18:11}	_542.0	_✔️	_:star:x4
_{awesome-deep-trading}	_{curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes}	_{11/26/18 3:23}	_{1/1/21 9:41}	_528.0	_✔️	_:star:x4
_{Neural Network}	_{Neural networks to predict stock prices.}	_{9/10/18 6:34}	_{11/21/18 7:39}	_488.0	_✖️	_:star:x4

Reinforcement Learning (Wiki)

_repo	_comment	_{created_at}	_{last_commit}	_{star_count}	_{repo_status}
_{RL Trading}	_{A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.}	_nan	_nan	_nan	_✔️
_RL	_{OpenGym with Deep Q-learning and Policy Gradient.}	_{10/4/16 14:42}	_{12/23/16 7:34}	_712.0	_✔️
_{RL III}	_{Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.}	_{9/21/17 17:05}	_{4/13/18 16:33}	_575.0	_✔️
_{RL V}	_{Building an Agent to Trade with Reinforcement Learning.}	_{1/16/19 0:43}	_{3/19/20 20:28}	_32.0	_✔️
_{Pair Trading RL}	_{Using deep actor-critic model to learn best strategies in pair trading.}	_{5/18/17 16:47}	_{5/18/17 16:56}	_241.0	_✔️
_{RL IV}	_{Reinforcement Learning for finance.}	_{10/21/16 2:47}	_{4/7/17 8:11}	_140.0	_✔️
_{RL II}	_{reinforcement learning on stock market and agent tries to learn trading.}	_{6/11/16 7:27}	_{1/22/18 14:35}	_1340.0	_✔️

Other Models (Wiki)

_repo	_comment	_{created_at}	_{last_commit}	_{star_count}	_{repo_status}
_{Trend Following}	_{A futures trend following portfolio investment strategy.}	_nan	_nan	_nan	_✔️
_{Scikit-learn Stock Prediction}	_{Using python and scikit-learn to make stock predictions.}	_{2/12/17 4:50}	_{2/4/21 3:48}	_919.0	_✔️
_{Fundamental LT Forecasts}	_{Research in investment finance for long term forecasts.}	_{7/22/18 8:14}	_{2/17/21 14:39}	_379.0	_✔️
_{Mixture Models I}	_{Mixture models to predict market bottoms.}	_{3/20/17 18:54}	_{4/25/17 23:35}	_31.0	_✔️
_{Short-Term Movement Cues}	_{Identify social/historical cues for short term stock movement.}	_{9/12/16 18:38}	_{8/29/18 20:27}	_2157.0	_✔️
_{Mixture Models II}	_{Mixture models and stock trading.}	_{12/11/17 17:05}	_{5/13/20 23:50}	_166.0	_✔️

Data Processing Techniques and Transformations (Wiki)

_repo	_comment	_{created_at}	_{last_commit}	_{star_count}	_{repo_status}	_rating
_{Advanced ML II}	_{More implementations of Financial Machine Learning (De Prado).}	_nan	_nan	_nan	_✔️
_{Advanced ML}	_{Exercises too Financial Machine Learning (De Prado).}	_{4/25/18 17:22}	_{1/16/20 17:25}	_958.0	_✔️

Portfolio Management

Portfolio Selection and Optimisation (Wiki)

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.
PyPortfolioOpt - Financial portfolio optimisation, including classical efficient frontier and advanced methods.
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.
DeepDow - Portfolio optimization with deep learning.

Factor and Risk Analysis (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

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 (Wiki)

Colleges, Centers and Departments (Wiki)

NYU FRE - Finance and Risk Engineering (NYU Tandon)
Cornell University
NYU Courant - Courant Institute of Mathematical Sciences, New York University
Oxford Man - Oxford-Man Institute of Quantitative Finance
Stanford Advanced Financial Technologies - Stanford Advanced Financial Technologies Laboratory
Berkeley Lab CIFT