Hybrid Monte Carlo-Methods in Credit Risk Management

TL;DR

This paper compares Monte Carlo, Quasi-Monte Carlo, and hybrid Monte Carlo methods in credit risk management, showing that hybrid methods often outperform pure approaches in relevant scenarios.

Contribution

It demonstrates that hybrid Monte Carlo methods can outperform traditional methods in credit risk simulations, providing a practical improvement for credit risk management.

Findings

Hybrid sequences perform better than pure methods in many situations.

Hybrid methods never perform worse than pure Monte Carlo or Quasi-Monte Carlo.

Hybrid Monte Carlo methods improve simulation accuracy in credit risk models.

Abstract

In this paper we analyze and compare the use of Monte Carlo, Quasi-Monte Carlo and hybrid Monte Carlo-methods in the credit risk management system Credit Metrics by J.P.Morgan. We show that hybrid sequences used for simulations, in a suitable way, in many relevant situations, perform better than pure Monte Carlo and pure Quasi-Monte Carlo methods, and they essentially never perform worse than these methods.