HftBacktest : A Comprehensive High-Frequency Trading Backtesting Tool

HftBacktest is a cutting-edge framework designed for developing and testing high-frequency trading (HFT) and market-making strategies.

It aims to provide accurate market replay-based backtesting by incorporating critical factors such as feed latency, order latency, and order queue positions.

This tool is ideal for traders and developers seeking to optimize algorithmic strategies in simulated environments before deploying them in live markets.

Key Features

  1. Tick-by-Tick Simulation: HftBacktest allows complete tick-by-tick simulation, enabling users to analyze market behavior at granular time intervals. The simulation can be customized based on feed or order receipt times.
  2. Order Book Reconstruction: It supports full order book reconstruction using L2 (Market-By-Price) and L3 (Market-By-Order) feeds, providing a detailed view of market depth.
  3. Latency Accounting: The framework incorporates feed and order latencies into backtesting, allowing users to model real-world delays using built-in or custom models.
  4. Order Fill Simulation: HftBacktest simulates order fills by considering the position of orders in the queue, which is crucial for accurate performance evaluation in HFT scenarios.
  5. Multi-Asset and Multi-Exchange Support: It enables backtesting across multiple assets and exchanges, making it versatile for complex trading strategies.
  6. Live Trading Deployment: The same algorithm code used for backtesting can be deployed as a live trading bot on platforms like Binance Futures and Bybit (Rust-only).

HftBacktest is available in both Python and Rust. The Python version utilizes Numba JIT for performance optimization, while the Rust version has been rewritten to enhance speed and scalability.

It supports Python 3.10+ and can be installed via pip or cloned from GitHub.

To install the Python version:

bashpip install hftbacktest

For Rust:

bashcargo add hftbacktest

HftBacktest is suitable for:

  • Developing market-making algorithms.
  • Testing grid trading strategies.
  • Evaluating the impact of latency on trading performance.
  • Risk mitigation through extreme market condition simulations.

HftBacktest bridges the gap between theoretical strategy development and practical implementation by providing a robust backtesting environment.

Its ability to simulate real-world trading dynamics makes it an invaluable tool for HFT practitioners.

Varshini

Varshini is a Cyber Security expert in Threat Analysis, Vulnerability Assessment, and Research. Passionate about staying ahead of emerging Threats and Technologies.

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