This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Numerical Methods for American Spread Options under Jump Diffusion Processes

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Finance, University of Technology, Sydney,; Gunter Meyer, School of Mathematics, Georgia Institute of Technology,; Andrew Ziogas, School of Economics (Gerald H. L. Cheang)
Gerald H. L. Cheang (Nanyang Business School, Nanyang Technological University)
Carl Chiarella (School of Economics and Finance, University of Technology, Sydney)
Gunter Meyer (School of Mathematics, Georgia Institute of Technology)
Andrew Ziogas (School of Economics and Finance, University of Technology, Sydney)

Additional information is available for the following registered author(s):

Abstract

This paper examines two numerical methods for pricing of American spread options in the case where both underlying assets follow the jump-diffusion process of Merton (1976). We extend the integral equation representation for the American spread option presented by Broadie and Detemple (1997) to the case where the return dynamics for both underlying assets involve jump terms. By use of the Fourier transform method, we derive a linked system of integral equations for the price and early exercise boundary of the American spread option. We also provide an integral equation for the delta of the American spread option, and determine the limit of the early exercise surface as time to expiry tends to zero. We consider two numerical methods for computing the price, delta and early exercise boundary of the American spread option. The first method is a two-dimensional generalisation of the method of lines for jump-diffusion, extending on the algorithm of Meyer (1998). The second method involves a numerical integration scheme for Volterra integral equations. This algorithm extends the methods of Kallast and Kivinukk (2003) and Chiarella and Ziogas (2004) to the two-dimensional jump-diffusion setting. The methods are benchmarked against a suitable Crank-Nicolson finite difference scheme, and their efficiency is explored.

Download Info
To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 137.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 04 Jul 2006
Date of revision:
Handle: RePEc:sce:scecfa:137

Contact details of provider:
Email:
Web page: http://comp-econ.org/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: American options; spread option; jump-diffusion; Volterra integral equation; free boundary problem; Fourier transform; method of lines;

Find related papers by JEL classification:
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

Statistics
Access and download statistics

Did you know? Data contributors to RePEc receive monthly emails with details about downloads and abstract views of their works.

This page was last updated on 2009-12-9.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.