Efficient Least Squares Monte-Carlo Technique for PFE/EE Calculations

TL;DR

This paper introduces an efficient regression-based Least Squares Monte Carlo method to accelerate exposure calculations for portfolios with exotic derivatives, reducing computational complexity in nested Monte Carlo scenarios.

Contribution

The paper presents a novel application of LSMC to speed up PFE/EE calculations in complex portfolios with exotic derivatives, addressing nested Monte Carlo challenges.

Findings

Significant reduction in computation time for exposure calculations.

Improved accuracy in PFE/EE estimates using the proposed method.

Applicable to portfolios with complex exotic derivatives.

Abstract

We describe a regression-based method, generally referred to as the Least Squares Monte Carlo (LSMC) method, to speed up exposure calculations of a portfolio. We assume that the portfolio contains several exotic derivatives that are priced using Monte-Carlo on each real world scenario and time step. Such a setting is often referred to as a Monte Carlo over a Monte Carlo or a Nested Monte Carlo method.