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

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  • Yuriy Krepkiy
  • Asif Lakhany
  • Amber Zhang

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.

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  • Yuriy Krepkiy & Asif Lakhany & Amber Zhang, 2021. "Efficient Least Squares Monte-Carlo Technique for PFE/EE Calculations," Papers 2105.07061, arXiv.org.
    • Handle: RePEc:arx:papers:2105.07061
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    References listed on IDEAS

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    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. Samim Ghamami & Bo Zhang, 2014. "Efficient Monte Carlo Counterparty Credit Risk Pricing and Measurement," Finance and Economics Discussion Series 2014-114, Board of Governors of the Federal Reserve System (U.S.).
    3. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
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