Ultra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.
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Updated
Oct 8, 2023 - Java
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.
simple, fast and feature rich order matching engine supports limit, market, stop-loss, iceberg, IOC, FOK, GTD orders
Ultra-fast Node.js Order Book written in TypeScript for high-frequency trading (HFT) 🚀🚀
Python Library for Transaction Cost Analysis (TCA)
DistributedATS is a FIX Protocol based multi matching engine exchange(CLOB) that integrates QuickFIX and LiquiBook over DDS
Code package to analyze high-frequency trading (HFT) races using financial-exchange message data, following Aquilina, Budish and O'Neill (2021).
📊🎨 Nice looking financial chart examples.
A multi-asset matching engine for market places of all sizes
A Python module for market simulation
Deep learning approach for market price prediction, in JAX
Some codes used for the numerical examples proposed in https://hal.archives-ouvertes.fr/hal-01514987v2 and https://arxiv.org/abs/1705.01446
A very simplified implementation of a stock exchange.
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