Simple version of auto forex trader build upon the concept of DQN

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

🔎 📈 🐍 💰 Backtest trading strategies in Python.

QKeras: a quantization deep learning library for Tensorflow Keras

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Boll…

Collecting, analyzing, visualizing & paper trading options market data

NLP in Python with Deep Learning

PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).

A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize traffic efficiency.

Portfolio optimization and simulation in Python

Portfolio optimization with deep learning.

A complete set of volatility estimators based on Euan Sinclair's Volatility Trading

A nimble options backtesting library for Python

Q-Learning Based Cryptocurrency Trader and Portfolio Optimizer for the Poloniex Exchange

QuantStart Forex Backtesting and Live Trading

Simple algorithmic stock and option trading for Node.js.

Generating multiple choice questions from text using Machine Learning.

A multi-asset, multi-strategy, event-driven trade execution and management platform for running many algorithms/bots at many venues simultaneously with unified risk management and reporting. Uses M…

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Deep Learning with PyTorch Quick Start Guide, published by Packt

A long term short term memory recurrent neural network to predict forex data time series

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

My Forex algotrading platform in Python - based on my posts at http://jon.io

Tensorflow implementation of Deepminds dqn with double dueling networks

In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)i…