stochastic-rs 2.6.0

Quantitative finance in Rust: 120+ stochastic processes, option pricing, model calibration, volatility surfaces, fixed income, risk and copulas — SIMD/GPU accelerated, with Python bindings.
Documentation 
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cff-version: 1.2.0
message: "If you use stochastic-rs in your research, please cite it as below."
title: "stochastic-rs: quantitative finance and stochastic process simulation in Rust"
abstract: >-
  stochastic-rs is an open-source Rust library for quantitative finance and
  stochastic process simulation. It provides 120+ stochastic processes
  (diffusion, jump, fractional and rough volatility, short-rate, HJM, LMM),
  option pricing and model calibration (Black-Scholes-Merton, Heston, SABR,
  rough Bergomi, Levy, double Heston), volatility surface construction
  (SVI, SSVI, SABR smile), fixed income and credit, statistical estimators
  (Hurst exponent, maximum likelihood for diffusions, realised variance),
  copulas, and neural-network volatility surrogates. Implementations are
  generic over f32/f64, SIMD-accelerated on CPU with optional CUDA, Metal
  and Accelerate backends, and exposed to Python through PyO3.
type: software
authors:
  - family-names: Boros
    given-names: Dániel
    email: dancixx@gmail.com
    orcid: "https://orcid.org/0009-0008-1207-2251"
repository-code: "https://github.com/rust-dd/stochastic-rs"
url: "https://stochastic.rust-dd.com"
license: MIT
version: 2.6.0
date-released: "2026-07-27"
doi: 10.5281/zenodo.21553307
identifiers:
  - type: doi
    value: 10.5281/zenodo.21553307
    description: Concept DOI — always resolves to the latest release.
  - type: doi
    value: 10.5281/zenodo.21553308
    description: Version DOI for v2.5.4.
keywords:
  - quantitative finance
  - stochastic processes
  - option pricing
  - model calibration
  - Monte Carlo
  - rough volatility
  - fractional Brownian motion
  - copulas
  - Rust