A Discrete Time Approach for Modeling Two-Factor Mean-Reverting Stochastic Processes
Warren J. Hahn () and
James S. Dyer ()
Additional contact information
Warren J. Hahn: Graziadio School of Business and Management, Pepperdine University, Malibu, California 90263
James S. Dyer: McCombs School of Business, University of Texas at Austin, Austin, Texas 78712
Decision Analysis, 2011, vol. 8, issue 3, 220-232
Abstract:
Two-factor stochastic processes have been developed to more accurately describe the intertemporal dynamics of variables such as commodity prices. In this paper we develop an approach for modeling these types of stochastic processes in discrete time as two-dimensional binomial sequences. This approach facilitates the numerical solution of dynamic optimization problems such as investment decision making under uncertainty and option valuation related to commodities. We implement this approach in a two-dimensional lattice format, apply it to two hypothetical valuation problems discussed by Schwartz and Smith, and compare the results to those from simulation- and dynamic-programming-based methods.
Keywords: stochastic processes; discrete models; dynamic programming; valuation (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://dx.doi.org/10.1287/deca.1110.0209 (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:ordeca:v:8:y:2011:i:3:p:220-232
Access Statistics for this article
More articles in Decision Analysis from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().