Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds

FinnewsHunter: Multi-agent financial intelligence platform powered by AgenticX. Real-time news analysis, sentiment fusion, and alpha factor mining.

A collection of scripts and notebooks to help you get started quickly.

Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!

Python Market Simulation Engine Built on top of Generative AI

Quantitative Finance & Statistics Projects. Topics including multiple linear regression, variance and instability estimates, display methodology.

IB Gateway in a headless docker container.

The official example scripts for the Numerai Signals Data Science Tournament

Streamlit IV surface visualizer (Yahoo Finance + Black–Scholes). Explore IV vs expiry and strike/log-moneyness.

High-performance C++ Trading Engine

I did this project as one of the parts from a Python test for my Master's degree. The objective was to practice the treatment of financial time series.

RustyQlib: A quant library for derivative pricing and quantitative finance

High-Performance Automatic Differentiation for Python

Engine and UI for tracking trading performance across stocks and derivatives (options, futures, & future options).

The open-source, fault-tolerant trading kernel behind XaiAlgo. Features separate strategy logic, ghost-order detection, and auto-backfilling. Built for rock-solid stability on Linux.

Technical analysis in R: indicators, candlestick pattern detection, and interactive trading charts.

Trading Evolved book code

AI-Gated Arbitrage Strategy for Prediction Markets. Uses XGBoost to predict trade fill probability and avoid liquidity traps in volatile order books.

ArbiterLabs

Macro-aware, explainable equity analytics system using Bronze–Silver–Gold architecture. Built with Python, SQLite (CTEs & Window Functions), and Power BI for structured stock intelligence.

This project envisions the hedge fund of the future (2030 and beyond) — one that is AI-powered, decentralized, and fully autonomous. It merges multi-agent reinforcement learning, blockchain governance, and explainable AI into a self-governing, investor-trustworthy platform for next-generation asset management.

Quant finance side projects: calculation of volatility surfaces from option chain data, LSTM time series prediction

C++ trading system for BTC/USDT with backtesting engine, live shadow trading simulation, Binance API integration, algorithmic trading strategies, risk management, order matching, performance analytics (Sharpe, Sortino, Max Drawdown), and modular architecture for quantitative finance and crypto trading research.

Modular multi-asset-class Monte Carlo engine for pricing exotic derivatives and structured products with calibrated implied volatility surfaces (Heston, local vol, SVI) and a user-friendly Django web interface.

A modular Python toolkit for advanced options pricing, volatility modeling, Greeks computation, and risk analysis. Includes Monte Carlo and Black-Scholes models, machine learning volatility surfaces, and interactive visualizations via Streamlit.

A comprehensive list of quantitative finance portfolio/strategy performance measures.

Production-grade open-source Market Risk Engine 🚀💹 – Full-stack FastAPI (Python) + React 19/TypeScript with a sleek fintech dark-theme dashboard.Compute VaR & CVaR via multiple methods, advanced stress testing (historical crises + custom), VaR backtesting (Kupiec test), and rich portfolio analytics.

Interactive Streamlit app simulating Geometric and Arithmetic Brownian Motion. Visualize financial asset price movements with adjustable parameters for paths, time steps, volatility, and initial price.

C++20 quantitative finance library for volatility surface modelling and derivatives pricing.