Single-Transform Formulas for Pricing Asian Options in a General Approximation Framework under Markov Processes

20 Pages Posted: 20 Jan 2016 Last revised: 9 Oct 2017

See all articles by Zhenyu Cui

Zhenyu Cui

Stevens Institute of Technology - School of Business

Chihoon Lee

Stevens Institute of Technology

Yanchu Liu

Lingnan (University) College, Sun Yat-sen University, Guangzhou, China.

Date Written: January 20, 2016

Abstract

Recently, Cai et al. (2015) proposed closed-form double transform approxima- tion formulas for prices of both discretely and continuously monitored Asian options under the setting of a general continuous-time Markov chain. In this note, we analytically invert the Z−transform and the Laplace transform involved in their final results, respectively, for the discretely and the con- tinuously monitored cases, and we obtain explicit single Laplace transforms of option prices. This reduction in the dimension of numerical integral has meaningful consequences both in computational efficiency and in practical implementation of the formulas. Extensive numerical experiments illustrate the improved performance of our results.

Keywords: Finance, Asian option, Markov process, Continuous-Time Markov Chain, Laplace transform

JEL Classification: G12, G13

Suggested Citation

Cui, Zhenyu and Lee, Chihoon and Liu, Yanchu, Single-Transform Formulas for Pricing Asian Options in a General Approximation Framework under Markov Processes (January 20, 2016). Available at SSRN: https://ssrn.com/abstract=2718968 or http://dx.doi.org/10.2139/ssrn.2718968

Zhenyu Cui (Contact Author)

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

HOME PAGE: http://sites.google.com/site/zhenyucui86/publications

Chihoon Lee

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

Yanchu Liu

Lingnan (University) College, Sun Yat-sen University, Guangzhou, China. ( email )

Haizhu District,
Guangzhou, China.
Guangzhou, Guangdong 510275
China

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
235
Abstract Views
1,185
Rank
283,614
PlumX Metrics