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 & Reinforcement Learning (Wiki)

_repo	_comment	_{created_at}	_{last_commit}	_{star_count}	_{repo_status}	_rating
_{Stock-Prediction-Models}	_{very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using BERT)}	_{12/18/17 10:49}	_{1/5/21 10:31}	_3599.0	_✔️	_:star:x5
_{AI Trading}	_{AI to predict stock market movements.}	_{1/9/19 8:02}	_{2/11/19 16:32}	_2857.0	_✖️	_:star:x5
_{FinRL-Library}	_{started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and gym use pyfolio for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading}	_{7/26/20 13:18}	_{4/3/21 23:21}	_1807.0	_✔️	_:star:x5
_{Deep Learning IV}	_{Bulbea: Deep Learning based Python Library.}	_{3/9/17 6:11}	_{3/19/17 7:42}	_1451.0	_✖️	_:star:x5
_RLTrader	_{predecessor to tensortrade uses open api gym and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using Optuna etc.}	_{4/27/19 18:35}	_{10/17/19 16:25}	_1304.0	_✔️	_:star:x5
_{Deep Learning III}	_{Algorithmic trading with deep learning experiments.}	_{6/18/16 18:23}	_{8/7/18 15:24}	_1264.0	_✖️	_:star:x5
_Personae	_{implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from rqalpha which is a python backtest engine and have a nice docker image to run training/testing}	_{3/10/18 11:22}	_{9/2/18 17:21}	_1142.0	_✖️	_:star:x5
_{RL Trading}	_{A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.}	_nan	_nan	_nan	_✔️	_:star:x4
_{Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020}	_{Part of FinRL and provided code for paper deep reinformacement learning for automated stock trading focuses on ensemble.}	_{7/26/20 13:12}	_{1/21/21 18:11}	_547.0	_✖️	_: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}	_541.0	_✔️	_:star:x4

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}	_922.0	_✔️
_{Fundamental LT Forecasts}	_{Research in investment finance for long term forecasts.}	_{7/22/18 8:14}	_{2/17/21 14:39}	_381.0	_✔️
_{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}	_2158.0	_✖️
_{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}	_964.0	_✔️

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