stochastic-rs
A high-performance Rust library for simulating stochastic processes, with applications in quantitative finance, statistical modeling, and synthetic data generation.
What is stochastic-rs?
stochastic-rs is a Rust library for simulating and analyzing stochastic processes. It provides a wide range of models and tools for quantitative finance, statistical modeling, and synthetic data generation, with a focus on high performance through SIMD and parallel computing.
Quantitative developers, financial engineers, and researchers who need high-performance simulation of stochastic models for pricing, risk analysis, or statistical research.
It offers an extensive collection of models, high performance via Rust and optional GPU acceleration, and seamless Python integration, positioning itself as a modern, open-source alternative to libraries like QuantLib.
Overview
stochastic-rs is a Rust library designed for high-performance simulation and analysis of stochastic processes and models in quant finance.
Use Cases
Best For
- Simulating complex stochastic models for derivative pricing
- Calibrating financial models like Heston or SABR to market data
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