Ultra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

High performance components for building Trading Platform such as ultra fast matching engine, order book processor

Free self-hosted market-making software for cryptocurrency projects and exchanges. Makes trade volume, maintains spread and liquidity/depth, set price range, and builds live-like dynamic order book.

OrderBook Heatmap visualizes the limit order book, compares resting limit orders and shows a time & sales log with live market data streamed directly from the Binance WS API. This was a short exploratory project. Keep in mind that a lot of work is needed for this to work in all market conditions.

Nasdaq Order Book Reconstructor

The bot capitalizes on Solana’s high-speed blockchain and low-cost transactions to execute large trades with minimal latency. Supporting SOL/USDT, SOL/ETH, SOL/BTC, and SOL/USDC pairs, it ensures profitability through real-time price monitoring, instant order execution, and advanced front-running protection.

Ultra-fast Limit Order Book for Node.js written in TypeScript for high-frequency trading (HFT) 🚀🚀

simple, fast and feature rich order matching engine supports limit, market, stop-loss, iceberg, IOC, FOK, GTD orders

DistributedATS is a FIX Protocol based multi matching engine exchange(CLOB) that integrates QuickFIX and LiquiBook over DDS

https://aux.exchange/

A multi-asset matching engine for market places of all sizes

Solana DEX Smart Contract – A high-performance decentralized exchange (DEX) on Solana, combining an on-chain order book with Raydium’s AMM aggregator for optimal liquidity, best price execution, and low slippage trading. Built with Rust & Anchor, it offers fast, cost-efficient, and transparent decentralized trading.

Code package to analyze high-frequency trading (HFT) races using financial-exchange message data, following Aquilina, Budish and O'Neill (2021).

Deep learning approach for market price prediction, in JAX

📊🎨 Nice looking financial chart examples.

Simple limit order book and matching engine.

A Python module for market simulation

Some codes used for the numerical examples proposed in https://hal.archives-ouvertes.fr/hal-01514987v2 and https://arxiv.org/abs/1705.01446