Free, open source crypto trading bot
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Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
- quantitative-finance
- machine-learning
- stock-data
- platform
"Vibe-Trading: Your Personal Trading Agent"
Production-grade Rust-native trading engine with deterministic event-driven architecture
- algorithmic-trading-engine
- trading-platform
- crypto-trading
- artificial-intelligence
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
- c-sharp
- algorithmic-trading-engine
- quantconnect
- lean-engine
Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
- trading-strategies
- quantitative-trading
- trading-bot
- quantitative-finance
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
- trading-strategies
- trading-robots
- trading-platform
- algorithmic-trading-engine
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
modular quant framework.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
- high-frequency-trading
- limit-order-book
- python
- machine-learning
Python trading framework with AI agents that actually place the trade. Backtest, paper and live trade on 12 brokers: stocks, options, futures, forex, crypto and prediction markets.
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
- btc
- lstm
- rnn
- bitcoin
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.