Dynamic Programming Approach for Valuing Options in the GARCH Model

Hatem Ben-Ameur (), Michèle Breton () and Juan-Manuel Martinez ()
Additional contact information
Hatem Ben-Ameur: GERAD, Brock University and HEC Montréal, Montréal, Québec H3T 2A7, Canada
Michèle Breton: GERAD and HEC Montréal, Montréal, Québec H3T 2A7, Canada
Juan-Manuel Martinez: HEC Montréal, Montréal, Québec H3T 2A7, Canada

Management Science, 2009, vol. 55, issue 2, 252-266

Abstract: In this paper, we develop an efficient algorithm to value options under discrete-time GARCH processes. We propose a procedure based on dynamic programming coupled with piecewise polynomial approximation to compute the value of a given option, at all observation dates and levels of the state vector. The method can be used for the large GARCH family of models based on Gaussian innovations and may accommodate all low-dimensional European as well as American derivatives. Numerical implementations show that this method competes very advantageously with other available valuation methods.

Keywords: dynamic programming; applications; finance; asset pricing; Markov; infinite state (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1080.0925 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:55:y:2009:i:2:p:252-266

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().