Files
foxhunt/backtesting
jgrusewski ff6ad2d039 fix(test): use median of 21 runs for inference latency check
Single-sample latency measurement was flaky under concurrent test load.
Using median eliminates outlier sensitivity (127μs median vs 1154μs spike).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-21 11:22:36 +01:00
..

Backtesting Crate

Overview

The backtesting crate provides a robust and configurable engine for simulating trading strategies against historical market data. It enables quantitative analysts and developers to evaluate strategy performance, optimize parameters, and validate hypotheses before live deployment.

Features

  • Historical Data Replay: Efficiently replays market data from Parquet files, supporting various data granularities (ticks, order book snapshots, candles).
  • Comprehensive Performance Metrics: Calculates key performance indicators such as Sharpe Ratio, Maximum Drawdown, Alpha, Beta, Sortino Ratio, and more.
  • Realistic Slippage Modeling: Configurable slippage models (e.g., fixed, percentage, volume-based) to accurately reflect real-world execution costs.
  • Commission Modeling: Supports various commission structures (e.g., fixed per trade, percentage of value, per share/contract) for accurate P&L calculation.
  • Detailed Trade Analytics: Generates in-depth reports on individual trades, cumulative P&L, win/loss ratios, and trade duration analysis.
  • Pluggable Strategy Interface: Defines a clear interface for users to implement and integrate their custom trading strategies seamlessly.

Usage

use backtesting::{Backtester, BacktestConfig};
use common::types::InstrumentId;
use std::path::PathBuf;

let config = BacktestConfig {
    start_time: "2023-01-01T00:00:00Z".parse().unwrap(),
    end_time: "2023-01-02T00:00:00Z".parse().unwrap(),
    data_path: PathBuf::from("./historical_data/"),
    instruments: vec![InstrumentId::new("BTCUSD".to_string())],
    // ... other configuration like slippage, commissions
};

// let mut backtester = Backtester::new(config);
// let strategy = MySimpleStrategy::new(); // Initialize your strategy
// backtester.run(&strategy).expect("Backtest failed");

// let results = backtester.get_results();
// println!("Sharpe Ratio: {}", results.sharpe_ratio);
// println!("Max Drawdown: {}", results.max_drawdown);

Testing

cargo test --package backtesting

Documentation

Full API documentation is available at docs.rs/backtesting.