A Lightweight, High-Performance Mathematics & Quantitative Finance Toolkit

DervFlow is a comprehensive toolkit designed for high-performance mathematics and quantitative finance applications. It offers a range of features including production-ready option pricers, risk analytics, portfolio construction utilities, time-series diagnostics, and yield-curve analytics. These capabilities are backed by rigorously tested numerical kernels implemented in Rust for enhanced safety and speed.

Highlights:

• Options Pricing: Includes Black-Scholes-Merton analytics, implied volatility solvers, and exotic payoffs exposed through ergonomic Python classes.

• Risk Analytics: Offers portfolio Greeks aggregation, historical/parametric/Monte Carlo VaR and CVaR, drawdown analytics, and performance ratios.

• Portfolio Construction: Provides mean-variance optimization, efficient frontiers, and Black–Litterman blending of market and investor views.

• Yield Curves: Features bootstrapping from bonds or swaps, Nelson–Siegel parametrisations, and bond analytics.

• Time Series: Supports return transformations, rolling statistics, autocorrelation diagnostics, and GARCH-family volatility models.

• Monte Carlo Simulation: High-throughput stochastic process simulators with optional parallel path generation.