Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
- c-sharp
- algorithmic-trading-engine
- quantconnect
- lean-engine
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The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
- quantitative-finance
- quant
- python
- fintech
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
11 Claude skills for day trading: scan thousands of charts, track breaking news, time every entry and exit, and replay every outcome before you risk a dollar.
- backtesting
- claude
- claude-skills
- day-trading
Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.
- trading-bot
- python
- bitcoin
- ai-trading
📈 Get real-time stocks from TradingView
- tradingview
- tradingview-api
- realtime-stocks
- stocks
modular quant framework.
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
- deep-reinforcement-learning
- stock-trading
- a2c-algorithm
- ppo
TranslatedVibe-Research: A research workbench for China A-shares, US and HK stocks · watchlist and holdings, daily review, industry news, industry research, in-depth stock analysis, backtesting, research report library, 168 data endpoints. Supports Claude Code, Codex, WorkBuddy subscriptions or any model API.
A Java library for technical analysis.
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.
High-performance technical analysis indicators and backtesting framework in Go. Zero dependencies. ✨ See how! 👀
- indicators
- technical-analysis
- stock-analysis
- stock-market
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
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.
Trady is a handy library for computing technical indicators, and it targets to be an automated trading system that provides stock data feeding, indicator computing, strategy building and automatic trading. It is built based on .NET Standard 2.0.
- strategy
- technical
- analysis
- stock
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.
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.