Pricing American Options in an Infinite Activity Lévy Market: Monte Carlo and Deterministic Approaches Using a Diffusion Approximation

0Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Computational methods for pricing exotic options when the underlying is driven by a Levy process are prone to numerical inaccuracy when the driving price process has infinite activity. Such inaccuracies are particularly severe for pricing of American options. In this chapter, we examine the impact of utilizing a diffusion approximation to the contribution of the small jumps in the infinite activity process. We compare the use of deterministic and stochastic (Monte Carlo) methods, and focus on designing strategies tailored to the specific difficulties of pricing American options. We demonstrate that although the implementation of Monte Carlo pricing methods for common Levy models is reasonably straightforward, and yields estimators with relatively small bias, deterministic methods for exact pricing are equally successful but can be implemented with rather lower computational overhead. Although the generality of Monte Carlo pricing methods may still be an attraction, it seems that for models commonly used in the literature, deterministic numerical approaches are competitive alternatives. © Springer-Verlag Berlin Heidelberg 2012.

Cite

CITATION STYLE

APA

Powers, L. J., Nešlehová, J., & Stephens, D. A. (2012). Pricing American Options in an Infinite Activity Lévy Market: Monte Carlo and Deterministic Approaches Using a Diffusion Approximation. In Springer Proceedings in Mathematics (Vol. 12, pp. 291–321). https://doi.org/10.1007/978-3-642-25746-9_9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free