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CryptoQuant AI is an advanced, open-source quantitative trading platform designed to bridge the gap between algorithmic market execution and artificial intelligence. Built entirely on a modern Node.js, Vite, and TypeScript stack, this project provides a robust, highly responsive frontend dashboard paired with powerful automation capabilities.
Command-line cryptocurrency price predictor that uses an XGBoost regression model trained on historical data from Yahoo Finance to forecast future prices.
AI-powered equity research and portfolio backtesting system using XGBoost, momentum signals, financial feature engineering, and RAG-based investment insights.
Quantitative finance machine learning pipeline engineered to predict short-horizon market returns from anonymized tabular data using an optimized LightGBM ensemble architecture
AI-powered crypto decision agent that analyzes market data using technical indicators and LLM reasoning to generate buy/sell/hold signals with risk and confidence scoring.
An end-to-end Machine Learning pipeline that predicts next-day price direction (Up/Down) for financial assets using XGBoost, technical feature engineering, and rigorous backtesting methodologies. Built with strict quantitative finance principles to avoid data leakage and false market signals.
A production-ready GDP nowcasting engine utilizing Mixed-Frequency Dynamic Factor Models (MIDAS) and Kalman Filtering to extract real-time macroeconomic health.