A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Repository Index
47,133 repositories indexed
25–45 of 45 · Most stars
Python live trade execution library with zipline interface.
- python3
- python
- algorithmic-trading
- quant
Oracle3: open-source trading engine and MCP server for prediction markets. Finds fee-adjusted no-arbitrage violations across related event contracts and trades them live on Kalshi, Polymarket and Solana, or on paper, under pre-trade risk limits. 13 MCP tools, JSON CLI, agent skills, 600+ tests.
- algorithmic-trading
- kalshi
- polymarket
- python
A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
- trading
- trading-bot
- trading-systems
- cryptocurrency
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
- automatic-differentiation
- aad
- algorithmic-differentiation
- autodiff
Open Source Algorithmic Trading Engine
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
- btc
- lstm
- rnn
- bitcoin
Genetic Algorithm for solving optimization of trading strategies using Gekko
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Trading environnement for RL agents, backtesting and training.
- trading
- backtesting
- reinforcement-learning-agent
- reinforcement-learning
Building a population of models that trade crypto and mutate iteratively
- trading-bot
- bitcoin
- neuroevolution
- reinforcement-learning
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Parameter Optimization for Lean Algorithms
- lean
- optimization
- blazor
- sharpe-ratio
AI crypto trading bot with deep neural network (84.9% accuracy, 25 coins). BiLSTM + Attention trained on GPU. Bybit, Binance, OKX, Gate.io. Free cloud or self-hosted.
My algorithmic trading strategies with the Gekko cryptocurrency trading bot.
- gekko-strategies
- trading-strategies
- machine-learning-algorithms
- neural-networks
AI-Powered Quantitative Trading Engine — Evolve strategies with genetic algorithms
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
Wisp CLI — Interactive trading platform for backtesting and live trading across spot, perpetual futures, options, and prediction markets
Open BTC 5-minute prediction market sandbox for AI agents — register with one API call, get 1,000 test credits, and place a live order
- ai-agents
- prediction-markets
- starter-template
- trading-bot
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.
- algorithmic-trading
- cryptocurrency
- ethereum
- moving-average
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.