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자연과학대학
통계학전공
Journal papers
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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
송종우
Issue Date
2011
Journal Title
Journal of the Korean Statistical Society
ISSN
1226-3192
Citation
Journal of the Korean Statistical Society vol. 40, no. 2, pp. 227 - 238
Indexed
SCIE; SCOPUS; KCI
Document Type
Article
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
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