Billy1900/Midas

Kairos v2 is an open-source quantitative research framework developed in Python to systematically support the research and validation of Crypto Futures trading strategies. The project provides an end-to-end research workflow covering OHLC data processing, feature engineering and evaluation, factor research, backtesting, and parameter optimization.

An advanced crypto trading bot written in Python

LLM-powered trading agents that turn plain natural language into a five-pillar strategy: Trend, Mean-Reversion, Momentum, Volume, and Risk. Each strategy is hosted, self-evolving, configurable through 30+ tunable parameters, and bit-exact between backtest and live execution. Built for simulated Hyperliquid perpetuals.

Custom trading strategies using the freqtrade framework

An All-in-One Algo-Trading Framework: Backtest -> Train -> Trade -> Monitor. Machine / Deep Learning Ready. Supports All Trading: TradFi+CeFi+DeFi. Code Once, Trade Anywhere.

An open-source, high-performance quantitative trading framework in C++/Python focused on strategy analysis and backtesting Trading model R&D · Ultra-fast engine · Efficient backtesting

🦊 Open-source professional quant agent framework. Agents pick the factors working now to time entries, write full strategies, and evolve them in a sandbox — every order through machine approval, the LLM never on the order path. Multi-market, audit-grade.

Production-grade DeFi strategy framework for Quantitative Analysts, Traders and Researchers