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http://dx.doi.org/10.7465/jkdi.2017.28.2.251

A numerical study on option pricing based on GARCH models with normal mixture errors  

Jeong, Seung Hwan (Department of Statistics, Hankuk University of Foreign Studies)
Lee, Tae Wook (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.2, 2017 , pp. 251-260 More about this Journal
Abstract
The option pricing of Black와 Scholes (1973) and Merton (1973) has been widely reported to fail to reflect the time varying volatility of financial time series in many real applications. For example, Duan (1995) proposed GARCH option pricing method through Monte Carlo simulation. However, financial time series is known to follow a fat-tailed and leptokurtic probability distribution, which is not explained by Duan (1995). In this paper, in order to overcome such defects, we proposed the option pricing method based on GARCH models with normal mixture errors. According to the analysis of KOSPI200 option price data, the option pricing based on GARCH models with normal mixture errors outperformed the option pricing based on GARCH models with normal errors in the unstable period with high volatility.
Keywords
GARCH model; KOSPI200; Normal mixture; Option pricing;
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Times Cited By KSCI : 5  (Citation Analysis)
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