hftbacktest

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HftBacktest

codeql python pypi downloads rustc crates license docs roadmap github

High-Frequency Trading Backtesting Tool

This framework is designed for developing high frequency trading and market making strategies. It focuses on accounting for both feed and order latencies, as well as the order queue position for order fill simulation. The framework aims to provide more accurate market replay-based backtesting, based on full order book and trade tick feed data.

Key Features

• Working in Numba JIT function (Python).
• Complete tick-by-tick simulation with a customizable time interval or based on the feed and order receipt.
• Full order book reconstruction based on Level-2 Market-By-Price and Level-3 Market-By-Order feeds.
• Backtest accounting for both feed and order latency, using provided models or your own custom model.
• Order fill simulation that takes into account the order queue position, using provided models or your own custom model.
• Backtesting of multi-asset and multi-exchange models
• Deployment of a live trading bot for quick prototyping and testing using the same algorithm code: currently for Binance Futures and Bybit. (Rust-only)

Documentation

See full document here .

Tutorials you’ll likely find interesting:

• High-Frequency Grid Trading - Simplified from GLFT
• Market Making with Alpha - Order Book Imbalance
• Market Making with Alpha - APT
• Accelerated Backtesting
• Pricing Framework

Why Accurate Backtesting Matters — Not Just Conservative Approach

Trading is a highly competitive field where only the small edges usually exist, but they can still make a significant difference. Because of this, backtesting must accurately simulate real-world conditions.: It should neither rely on an