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http://dx.doi.org/10.5351/KJAS.2016.29.1.181

Comparison of methods of approximating option prices with Variance gamma processes  

Lee, Jaejoong (Department of Statistics, Korea University)
Song, Seongjoo (Department of Statistics, Korea University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.1, 2016 , pp. 181-192 More about this Journal
Abstract
We consider several methods to approximate option prices with correction terms to the Black-Scholes option price. These methods are able to compute option prices from various risk-neutral distributions using relatively small data and simple computation. In this paper, we compare the performance of Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method of using Normal inverse gaussian distribution, and an asymptotic method of using nonlinear regression through simulation experiments and real KOSPI200 option data. We assume the variance gamma model in the simulation experiment, which has a closed-form solution for the option price among the pure jump $L{\acute{e}}vy$ processes. As a result, we found that methods to approximate an option price directly from the approximate price formula are better than methods to approximate option prices through the approximate risk-neutral density function. The method to approximate option prices by nonlinear regression showed relatively better performance among those compared.
Keywords
asymptotic option price; Gram-Charlier expansion; $L{\acute{e}}vy$ process; variance gamma; normal inverse gaussian;
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Times Cited By KSCI : 1  (Citation Analysis)
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