Computable Error Bounds of Laplace Inversion for Pricing Asian Options

Yingda Song (), Ning Cai () and Steven Kou ()
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Yingda Song: Antai College of Economics and Management, Shanghai Jiao Tong University, 200030 Shanghai, China
Ning Cai: Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
Steven Kou: Risk Management Institute and Department of Mathematics, National University of Singapore, Singapore; National University of Singapore Suzhou Research Institute, Suzhou Industrial Park, 215123 Suzhou, China

INFORMS Journal on Computing, 2018, vol. 30, issue 4, 634-645

Abstract: The prices of Asian options, which are among the most important options in financial engineering, can often be written in terms of Laplace transforms. However, computable error bounds of the Laplace inversions are rarely available to guarantee their accuracy. We conduct a thorough analysis of the inversion of the Laplace transforms for continuously and discretely monitored Asian option prices under general continuous-time Markov chains (CTMCs), which can be used to approximate any one-dimensional Markov process. More precisely, we derive computable bounds for the discretization and truncation errors involved in the inversion of Laplace transforms. Numerical results indicate that the algorithm is fast and easy to implement, and the computable error bounds are especially suitable to provide benchmark prices under CTMCs. The online supplement is available at https://doi.org/10.1287/ijoc.2017.0805 .

Keywords: discretely monitored Asian options; continuously monitored Asian options; continuous-time Markov chains; Laplace inversion (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:30:y:2018:i:4:p:634-645

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