qunatitative-finance

NSE is a rust cli binary and library for extracting real-time data from National Stock Exchange (India)

Quantitative Finance Research

Quantitative Finance 101: Backtesting and Optimization

QuantFlow Zero fetches live stock/crypto data via Yahoo Finance, runs 5 technical indicators (MA, RSI, MACD, Bollinger, Volume) in pure Python, and generates a sleek interactive HTML dashboard with AI predictions, risk management, and charts — zero dependencies, just run and open.

Cross-sectional momentum strategy | Python backtesting | ML experiment | Live deployment via IBKR

Predicting stock volatility regimes (CAC40/DAX/SP500) via alternative data (weather & calendar). R time-series ML benchmark comparing 6 classifiers (XGBoost, RF, GLMNet)

A quant research project that tests whether **implied volatility** tends to be overpriced relative to **model-estimated volatility**. The study compares **India (NIFTY + India VIX)** and **US (S&P 500 + VIX)** using rolling GARCH forecasts, volatility spreads, and forward 5-day outcome testing.

Fast historical stock data dumping for quant workflows. © OpenNET LLC

Leakage-aware financial ML pipeline using event-driven sampling, triple-barrier labeling, fractional differentiation, purged CV, XGBoost, meta-labeling, bet sizing, and backtesting.