This repo demystifies algorithmic trading by walking through building S&P 500 equal-weight, momentum, and value strategies in Python using Jupyter notebooks and free IEX Cloud data.
Explore a Python framework for cryptocurrency algorithmic trading that uses composable boolean functions for strategy design, supporting live trading, simulation, and backtesting.
This repo teaches algorithmic trading with a disciplined Research-Backtest-Implement method using Python and AI tools. It stresses avoiding emotional mistakes with systematic workflows.
Explore a Python trading bot for Polymarket’s 15-minute BTC markets. It uses a 7-phase modular pipeline, fuses three signals, and features a self-learning weight adjustment engine.
OpenAlgo offers a self-hosted algo trading platform with unified API for 30+ Indian brokers, Python strategy hosting, no-code flow builder, and options analytics — all sharing live sessions.
QSTrader offers a modular Python backtesting framework for long-short equity strategies using daily OHLC data and calendar-driven rebalancing. Its clean separation of signal, portfolio, and execution components stands out.
A curated GitHub repo consolidates 200+ quality resources for quantitative and ML-driven algorithmic trading, bridging academic research and practical strategies.
This curated repo maps the shift in systematic trading from event-driven backtesters to AI-powered strategy discovery, covering multi-asset tools, high-frequency backtesting, and AI agents.
TradeMaster offers a full pipeline for RL-based quantitative trading with 13+ algorithms and a rigorous 6-axis, 17-measure evaluation framework across multiple asset classes and trading tasks.
Lumibot unifies backtesting and live trading for stocks, options, crypto, and forex with AI agent runtime using DuckDB, supporting multiple brokers and data sources.
