{"repo":"PVinh-Quant/Kairos-v2","free":true,"listed":false,"github":"https://github.com/PVinh-Quant/Kairos-v2","clone":"git clone https://github.com/PVinh-Quant/Kairos-v2.git","description":"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.","language":"Python","stars":32,"topics":["crypto","python","quantitative-finance"],"license":"MIT","category":"trading","readme_excerpt":"KAIROS QUANT SYSTEM End-to-End Data Analytics Pipeline for Financial Market Research Stack: Python 3.12+ • Pandas • Polars • PyTorch • DuckDB • PyQt6 • CCXT --- Quick Start Want to run it immediately? Follow these 3 steps: See Installation & Setup for more details. --- Core Capabilities & Value Proposition KAIROS QUANT SYSTEM is an end-to-end data analytics and quantitative research platform designed to help strategy developers and traders transform raw market data into investment decisions backed by statistical rigor and machine learning. 🎯 Core Value & Utility (Why Kairos?) Eliminate Look-Ahead Bias: A strict 4-step multi-timeframe alignment pipeline guarantees that backtested signals reflect exactly what was historically available at the moment of execution. Rigorous Statistical Validation: Eliminate \"lucky\" parameters and overfitting via Walk-Forward Validation and Deflated Sharpe Ratio (DSR) metrics. 100x+ Research Acceleration: High-performance vectorized computations powered by Polars & Pandas allow you to backtest millions of rows of data in seconds. Zero Train-Serve Skew: The exact same feature-generation logic ( calc core features ) is shared between offline ML training and real-time live trading. --- ⚙️ Main System Functionalities Core Feature Description --- --- Automated ETL Pipeline Raw API $\\rightarrow$ Clean Dataset. Automatically downloads multi-timeframe OHLCV (1m–1d) from Binance, OKX, and Bybit using CCXT & WebSockets. Handles timestamp alignment and auto","default_branch":null,"files":null,"tree":[],"storefront":"/r/PVinh-Quant","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/PVinh-Quant/Kairos-v2/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."}