Asymptotic option pricing under pure-jump Levy processes via nonlinear regression
- Authors
- Song, Seongjoo; Jeong, Jaehong; Song, Jongwoo
- Issue Date
- 6월-2011
- Publisher
- KOREAN STATISTICAL SOC
- Keywords
- Option pricing; Levy process; Nonlinear regression; Asymptotic expansion
- Citation
- JOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.40, no.2, pp.227 - 238
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- JOURNAL OF THE KOREAN STATISTICAL SOCIETY
- Volume
- 40
- Number
- 2
- Start Page
- 227
- End Page
- 238
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/112267
- DOI
- 10.1016/j.jkss.2010.10.001
- ISSN
- 1226-3192
- Abstract
- When the underlying asset price process follows a Levy process, the market becomes incomplete, in which the option pricing can be a complicated problem. This paper proposes a method of asymptotic option pricing when the underlying asset price process follows a pure-jump Levy process. We express the option price as the expected value of the discounted payoff and expand it at the Black-Scholes price assuming that the price process converges weakly to the Black-Scholes model. The price can be approximated by a formula with 4 parameters, which can easily be estimated using option prices observed in the market. The proposed price explains the market option data better than the Black-Scholes price in real data application with KOSPI 200. (C) 2010 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
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