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Asymptotic option pricing under pure-jump Lévy processes via nonlinear regression

Title
Asymptotic option pricing under pure-jump Lévy processes via nonlinear regression
Authors
Song S.Jeong J.Song J.
Ewha Authors
송종우
SCOPUS Author ID
송종우scopus
Issue Date
2011
Journal Title
Journal of the Korean Statistical Society
ISSN
1226-3192JCR Link
Citation
vol. 40, no. 2, pp. 227 - 238
Indexed
SCIE; SCOPUS; KCI WOS scopus
Abstract
When the underlying asset price process follows a Lévy 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 Lévy 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. © 2010 The Korean Statistical Society.
DOI
10.1016/j.jkss.2010.10.001
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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