27 releases (14 breaking)
0.15.1 | Sep 1, 2021 |
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0.14.2 | Nov 23, 2020 |
0.14.0 | Mar 2, 2019 |
0.13.7 | Sep 11, 2018 |
0.7.0 | Jul 16, 2018 |
#647 in Math
33 downloads per month
Used in 5 crates
(4 directly)
27KB
373 lines
[lin-badge]: https://github.com/danielhstahl/fang_oost_rust/workflows/Rust/badge.svg [cov-badge]: https://codecov.io/gh/danielhstahl/fang_oost_rust/branch/master/graph/badge.svg
Linux | Codecov |
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![lin-badge] | ![cov-badge] |
Fang-Oosterlee Library for Rust
Implements Fang-Oosterlee algorithm in Rust. While the algorithm originally was used for option pricing, it can be used for a variety of use cases. For example, it can be used to compute the Value at Risk of a distribution, the density of a distribution, and the partial expectation.
It requires a characteristic function computed at various specific intervals. A utility function is provided which converts an analytical characteristic function into a vector.
Documentation is at docs.rs
Use
Put the following in your Cargo.toml:
[dependencies]
fang_oost = "0.15"
Import and use:
extern crate num_complex;
extern crate fang_oost;
extern crate rayon;
use rayon::prelude::*;
use num_complex::Complex;
let num_x = 1024;
let num_u = 256;
let x_min = -20.0;
let x_max = 25.0;
let mu=2.0;
let sigma:f64=5.0;
let norm_cf = |u:&Complex<f64>|(u*mu+0.5*u*u*sigma*sigma).exp();
let x_domain=fang_oost::get_x_domain(num_x, x_min, x_max);
//computes discrete gaussian characteristic function
let discrete_cf=fang_oost::get_discrete_cf(num_u, x_min, x_max, &norm_cf);
let result=fang_oost::get_expectation_single_element_real(
x_min, x_max, x, &discrete_cf,
|u_im, x, k|{
if k==0{x-x_min} else { ((x-x_min)*u_im).sin()/u_im }
}
);
Related Crates
Benchmarks
View benchmarks at https://danielhstahl.github.io/fang_oost_rust/report/index.html.
Dependencies
~2MB
~35K SLoC