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backtest_statistics

Subject

Section titled “Subject”

Portfolio Construction and Risk

Why This Module Exists

Section titled “Why This Module Exists”

Turns raw PnL/returns into risk-adjusted diagnostics used in model selection and production monitoring.

Mathematical Foundations

Section titled “Mathematical Foundations”

Sharpe

Section titled “Sharpe”

S=μ−rfσS=\frac{\mu-r_f}{\sigma}

Information Ratio

Section titled “Information Ratio”

IR=μ−rbσ(r−rb)IR=\frac{\mu-r_b}{\sigma_{(r-r_b)}}

Usage Examples

Section titled “Usage Examples”

Rust

Section titled “Rust”

Compute Sharpe and drawdown

Section titled “Compute Sharpe and drawdown”
use openquant::backtest_statistics::{sharpe_ratio, drawdown_and_time_under_water};


let returns = vec![0.01, -0.005, 0.007, -0.002, 0.003];
let sr = sharpe_ratio(&returns, 252.0, 0.0);
let (dd, tuw) = drawdown_and_time_under_water(&returns);
println!("{sr} {dd:?} {tuw:?}");

API Reference

Section titled “API Reference”

Rust API

Section titled “Rust API”
  • sharpe_ratio
  • deflated_sharpe_ratio
  • probabilistic_sharpe_ratio
  • drawdown_and_time_under_water
  • average_holding_period

Implementation Notes

Section titled “Implementation Notes”
  • Use annualization constants consistent with your bar frequency.
  • Deflated Sharpe is useful when strategy mining many variants.