Leave-One-Out Least Square Monte Carlo Algorithm for Pricing American Options
23 Pages Posted: 28 Oct 2018 Last revised: 28 May 2019
Date Written: October 3, 2018
The least square Monte Carlo (LSM) algorithm proposed by Longstaff and Schwartz  is widely used for pricing American options. The LSM estimator contains undesirable look-ahead bias, and the conventional technique of removing it necessitates doubling simulations. We present the leave-one-out LSM (LOOLSM) algorithm for efficiently eliminating look-ahead bias. We validate the method with several option examples, including the multi-asset cases that the LSM algorithm significantly overvalues. We also obtain the convergence rates of look-ahead bias by measuring it using the LOOLSM method. The analysis and computational evidence support our findings.
Keywords: American option, Least square Monte Carlo, Longstaff--Schwartz algorithm, Look-ahead bias, Leave-one-out-cross-validation
JEL Classification: C61, G13
Suggested Citation: Suggested Citation