# avhz/RustQuant

Rust library for quantitative finance.

Repository: https://github.com/avhz/RustQuant
Canonical: https://ross.abutalabs.com/products/rustquant
Homepage: https://avhz.github.io
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: finance, math, mathematics, quantitative-finance, rust, rust-lang, quantlib, machine-learning, option-pricing, regression, statistics, stochastic-processes, trading
Last push: 2026-01-14T00:46:56+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 62, release rhythm 28, longevity 100
- inputs: {"age_days": 1463, "days_push": 232, "days_rel": 649, "gap_med": 0, "n_releases_24m": 74}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1812, forks 209 (observed 2026-08-28T04:05:39.644719+00:00)

## What it is
RustQuant is a Rust library for quantitative finance, offering modules for option pricing, stochastic processes, autodiff, statistics, and financial data handling. It aims to be an open-source alternative to QuantLib written in Rust.

## Use cases
- price options in rust
- simulate stochastic processes like brownian motion
- compute gradients of pricing functions with automatic differentiation
- download and parse yahoo finance data
- fit yield curves and term structures
- run monte carlo simulations for derivatives
- statistical regression and distributions for finance

## When to choose
- you need a Rust-native quant finance toolkit instead of QuantLib or C++ libraries
- you want option pricing, stochastic calculus, and AAD in one crate
- you are building trading or risk analytics tooling in Rust

## When to avoid
- you need battle-tested production pricing libraries with long audit history
- you need a full GUI or trading platform rather than a library
- you require exotic instruments not yet implemented in the crate

## Facets
- artifact type: library
- maturity: active
- function: math, machine-learning, data-science, trading
- domain: fintech, mathematics, machine-learning, data-science
- platform: rust
- tags: quantitative-finance, option-pricing, stochastic-processes, monte-carlo, autodiff, statistics, regression, quantlib

## Member repositories
- avhz/RustQuant (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.644719+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:12.644100+00:00, confidence not recorded.
  - readme: https://github.com/avhz/RustQuant (fetched 2026-08-28T04:05:39.644719+00:00, sha 9750529da57a)
  - homepage: https://avhz.github.io (fetched 2026-08-29T10:59:49.380940+00:00, sha 747a9f01119e)
  - registry_crates: https://crates.io/api/v1/crates/rustquant (fetched 2026-08-29T10:59:49.389859+00:00, sha 7e7fd4fbbb00)
- Data as of 2026-08-30T08:39:29.467469+00:00.