Modeling Default Correlations
Overview
The Gauss Hermite quadrature provides a simple numeric way to estimate integrals of the form
{% \int_{- \infty} ^{\infty} g(x) f(x) dx \approx \sum_i^n w_i f(x_i) %}
where {% g(x) = \sqrt{1/2\pi \sigma^2 } \times e ^{-0.5 [(x-\mu)/\sigma]^2} %}.
In the version recommended by Loffler-Posch, we use 32 points and the weights are precalculated.
Example - Exponent
normal
let ml = await import('/lib/finance/credit/v1.0.0/maximum-likelihood.mjs');
let test = ml.gaussHermite(Math.exp);
Try it!
Likelihood Multiple Sectors
