A semi-analytic method for valuing high-dimensional options on the maximum and minimum of multiple assets

Xun Li, Zhenyu Wu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Valuing high-dimensional options has many important applications in finance but when the true distributions are unknown or complex, numerical approximations must be used. Approximation methods based on Monte-Carlo simulation show a steep trade-off between estimation accuracy and computational efficiency. This article presents an alternative semi-analytic approximation method for pricing options on the maximum or minimum of multiple assets with unknown distributions. Computational efficiency is shown to improve significantly without sacrificing estimation accuracy. The method is illustrated with applications to options on underlying assets with mean-reverting prices, time-dependent correlations, and stochastic volatility.
Original languageEnglish
Pages (from-to)179-205
Number of pages27
JournalAnnals of Finance
Volume2
Issue number2
DOIs
Publication statusPublished - 1 Mar 2006
Externally publishedYes

Keywords

  • High-dimensional options
  • Maximum
  • Mean-reverting
  • Minimum
  • Stochastic volatility

ASJC Scopus subject areas

  • Finance
  • Economics, Econometrics and Finance(all)

Cite this