Variance-constrained canonical least-squares Monte Carlo: An accurate method for pricing American options

Qiang Liu and Shuxin Guo

The North American Journal of Economics and Finance, 2014, vol. 28, issue C, 77-89

Abstract: The pricing accuracy of the canonical least-squares Monte Carlo (CLM) method can be improved significantly by incorporating innovatively a variance constraint in the derivation of the canonical risk-neutral distribution. This new approach is called the variance-constrained CLM (vCLM) in the paper. Operationally, the forward variance is set to be the square of the volatility implied under vCLM by the option's market price from a previous trading day. For 16,249 American-style S&P 100 index puts, vCLM produced an average absolute pricing error of 5.94%, easily outperforming CLM, a competing nonparametric approach, and a GARCH-based benchmark.

Keywords: Canonical least-squares Monte Carlo; Variance constraint; Implied volatility; American-style S&P 100 index put; Numerical measure change (search for similar items in EconPapers)
JEL-codes: G12 G13 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:28:y:2014:i:c:p:77-89

DOI: 10.1016/j.najef.2014.02.002

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