Crate fast_sde 

fast-sde: High-Performance Monte Carlo for Quantitative Finance

A Rust library for Monte Carlo simulation of Stochastic Differential Equations (SDEs) with applications to option pricing, risk management, and quantitative finance.

Key Features

• High Performance: Parallel Monte Carlo with Rayon, optimized for speed
• Variance Reduction: Antithetic variates and control variates
• Multiple SDE Models: Black-Scholes, Heston, SABR, Merton jump-diffusion
• Robust Numerics: Multiple discretization schemes (Euler, Milstein, SRK)
• Complete Greeks: Delta, Gamma, Vega, Rho via pathwise and finite difference
• Production Ready: Comprehensive error handling and validation

Quick Start

use fast_sde::mc::mc_engine::{mc_price_option_gbm, McConfig};
use fast_sde::mc::payoffs::Payoff;
 
// Configure European call option
let config = McConfig {
    paths: 100_000,
    s0: 100.0,      // Spot price
    r: 0.05,        // Risk-free rate
    sigma: 0.2,     // Volatility
    t: 1.0,         // Time to expiration
    payoff: Payoff::EuropeanCall { k: 100.0 },
    ..Default::default()
};
 
// Price the option
let (price, variance) = mc_price_option_gbm(&config).expect("Valid configuration");
println!("Option price: {:.4} ± {:.4}", price, variance.sqrt());

Mathematical Foundation

The library implements Monte Carlo methods for pricing derivatives under various stochastic models. The core approach simulates asset price paths and computes expected payoffs under the risk-neutral measure.

Re-exports

pub use error::SdeError;

pub use error::SdeResult;

Modules

analytics

error

math_utils

mc

models

output

rng

Random Number Generation for Monte Carlo Simulations

solvers