This project aims to simulate how an HFT (High-Frequency Trading) firm executes its strategies to profit through the stock exchanges. The project also simulates how a stock exchange manages its order book to match and execute orders efficiently using advanced data structures and algorithms to minimize the latency.

C++20 HFT simulator for CME futures. Shadow execution algorithm (% of volume, beats VWAP/TWAP). Position-aware order book with queue simulation. MDP3 decoder, iLink 3, PCAP replay. Lock-free actor framework with sub-microsecond dispatch. Distributed via ZMQ. ES/NQ futures backtesting and live trading.

A high-frequency trading simulation framework built in C++23, featuring stochastic volatility pricing, realistic order book microstructure, multi-strategy portfolio simulation, and parallelised Monte Carlo path generation.

Application of RL in trading

A High-Frequency Trading Simulator

Multi-Asset Backtesting & Simulation Engine

This technical report details the architecture and mathematical foundation of a quantitative market-making engine based on the stochastic optimal control framework proposed by Avellaneda and Stoikov (2008). The system dynamically computes optimal bid and ask quotes by balancing expected spread capture, inventory risk and etc

A distributed market data and arbitrage engine composed of an exchange simulator and an event-driven trading engine.

An empirical C++20 framework for reconstructing NASDAQ TotalView-ITCH limit order books from historical binary feeds and evaluating market-data replay, depth analytics, and order-book latency through reproducible benchmark workloads.

An experimental Unikernel for HFT simulation using x86_64 architecture

Zero-dependency HFT engine in Rust - 41 ns signal latency on Apple Silicon, ARM64 NEON register-resident signal, lock-free SPSC ring buffers, in-process exchange.

Latency-focused order book simulation with reproducible benchmarks, lifecycle events, and trace-level profiling hooks.