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.

AlphaStream India is a production-grade, real-time investment intelligence terminal designed to empower Indian retail investors. Featuring a Bloomberg-style terminal UI, it integrates Gemini 2.0 Flash, FastAPI, and React 19 to deliver grounded, backtested, and high-alpha investment signals.

🛡️ Physics-inspired RegTech toolkit for financial market surveillance. Detects Pump-and-Dump schemes, Wash Trading, and volume-price divergence using price kinematics.

🤖 AI-powered NSE India stock analyzer. One command, full 11-indicator analysis. Free for Indian retail investors.

Adaptive volatility-targeting strategy using Hidden Markov Models (HMM) and GARCH, featuring market-specific optimization and rebalancing buffers

Multivariate Hawkes process modeling for high-frequency limit order book (LOB) dynamics

Macro-driven quantitative research framework with live paper trading, walk-forward validation, and COT-based FX positioning models across equities, FX, and crypto.

AI-powered equity research and portfolio backtesting system using XGBoost, momentum signals, financial feature engineering, and RAG-based investment insights.

Real-time Global Semiconductor Supply Chain API. Programmatic JSON-LD feed for Nvidia H100, B200, TSMC 3nm/5nm wafer pricing, ASML EUV capacity & silicon spot markets. Optimized for autonomous AI agents, LLM-scrapers & hedge fund quant-trading. Supports HTTP 402 M2M Solana settlement. Essential data for Bloomberg, Reuters & supply chain disruption.

Quantitative finance machine learning pipeline engineered to predict short-horizon market returns from anonymized tabular data using an optimized LightGBM ensemble architecture

Algorithmic trading logic designed for XAUUSD (Gold) that automates market structure mapping and executes engulfing candlestick entries.

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.

Minute-level market microstructure event study analyzing extended-hours price discovery and orderflow around MSFT earnings. Integrates SEC 8-K Loughran-McDonald sentiment analysis with intraday Polygon proxies (CVD, realized volatility, and spread).

Real-time Market Risk Scoring API & Capital Allocator. Powered by Deep Learning (VGMNet), GARCH, and ORAC-NT entropy models.

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.

Multi-stage ML pipeline for crypto market signal filtering and live trading research

AI Portfolio Analyzer is a deep learning tool that trains LSTM and Transformer models on 46 stocks to predict returns, volatility, and downside risk with a built-in sentiment analysis, portfolio optimization, and a full backtesting engine.

Research-backed time-series momentum backtester that tests 12-month trend-following signals, volatility targeting, transaction costs, parameter robustness, and walk-forward evaluation across ETFs.