{"repo":"0x596173736972/MarketRegimeTrader","free":true,"listed":false,"github":"https://github.com/0x596173736972/MarketRegimeTrader","clone":"git clone https://github.com/0x596173736972/MarketRegimeTrader.git","description":"Quantitative finance platform that uses Hidden Markov Models (HMM) to detect market regimes and deploy adaptive trading strategies. Features include automated strategy generation, realistic backtesting, topological data analysis (TDA), robust risk management, and walk-forward validation","language":"Python","stars":17,"topics":["backtesting","hidden-markov-model","machine-learning","quantitative-finance","streamlit","topological-data-analysis"],"license":"MIT","category":"trading","readme_excerpt":"HMM Regime Detection & Trading System A sophisticated financial application that uses Hidden Markov Models (HMM) to detect market regimes and implement regime-based trading strategies with comprehensive backtesting, risk management, and automated strategy evolution. 🎯 Overview This application combines advanced statistical modeling with automated strategy generation to: - Detect Market Regimes : Identify different market states (bullish, bearish, range-bound) using HMM - Generate Trading Strategies : Automatically evolve optimal trading strategies using genetic programming - Backtest Performance : Simulate trading with realistic costs and slippage - Analyze Risk : Comprehensive risk analysis and portfolio management - Walk-Forward Analysis : Robust out-of-sample testing with rolling windows - Topological Data Analysis : Advanced market structure analysis using TDA 🔧 Current Working Features - ✅ HMM Model Training with 2-4 regimes - ✅ Multiple Technical Indicators (9 features available) - ✅ Strategy Backtesting with realistic costs - ✅ Risk Analysis and Performance Metrics - ✅ Walk-Forward Analysis with parameter optimization - ✅ TDA Market Structure Analysis - ✅ Sample Data Generation for testing 🧮 Mathematical Foundations Hidden Markov Models (HMM) Hidden Markov Models detect unobservable market regimes from observable price movements: Core Components: - States (S) : Hidden market regimes (Bearish, Range-bound, Bullish) - Observations (O) : Observable features (returns, v","default_branch":null,"files":null,"tree":[],"storefront":"/r/0x596173736972","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/0x596173736972/MarketRegimeTrader/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}