Sigma-Quant
A clean, modern Python library for quantitative finance metrics.
Sigma-Quant provides a collection of widely used performance and risk metrics designed for research, backtesting, and portfolio analysis. The API is high-level, composable, and easy to integrate into existing codebases.
In addition to individual metrics, Sigma-Quant emphasizes clarity and correctness, offering documentation that explains not only how each metric is computed, but also why specific design choices were made.
Portfolio and strategy performance metrics such as cumulative returns, Sharpe ratio, drawdowns, volatility, and related statistics.
Downside and tail-risk measures, including value-at-risk, expected shortfall, and stress-oriented indicators.
Utilities designed for quantitative research workflows, including factor analysis helpers and strategy evaluation tools.