A multi-phase, flexible, and accurate lattice for pricing complex derivatives with multiple market variables

Chuan Ju Wang*, Tian-Shyr Dai, Yuh Dauh Lyuu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

With the rapid growth of financial markets, many complex derivatives have been structured to meet specific financial goals. But most complex derivatives have no analytical formulas for their prices, e.g., when more than one market variable is factored. As a result, they must be priced by numerical methods such as lattice. A derivative is called multivariate if its value depends on more than one market variable. A lattice for a multivariate derivative is called a multivariate lattice. This paper proposes a flexible multi-phase method to build a multivariate lattice for pricing derivatives accurately. First, the original, correlated processes are transformed into uncorrelated ones by the orthogonalization method. A multivariate lattice is then constructed for the transformed, uncorrelated processes. To sharply reduce the nonlinearity error of many numerical pricing methods, our lattice has the flexibility to match the so-called "critical locations" - the locations where nonlinearity of the derivative's value function occurs. Numerical results for vulnerable options, insurance contracts guaranteed minimum withdrawal benefit, and defaultable bonds show that our methodology can be applied to the pricing of a wide range of complex financial contracts.

Original languageEnglish
Title of host publication2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2012 - Proceedings
Pages77-84
Number of pages8
DOIs
StatePublished - 27 Nov 2012
Event2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2012 - New York City, NY, United States
Duration: 29 Mar 201230 Mar 2012

Publication series

Name2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2012 - Proceedings

Conference

Conference2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2012
CountryUnited States
CityNew York City, NY
Period29/03/1230/03/12

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