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dc.contributor.authorKim, Young Shinen_US
dc.contributor.authorRachev, Svetlozar T.en_US
dc.contributor.authorBianchi, Michele Leonardoen_US
dc.contributor.authorFabozzi, Frank J.en_US
dc.description.abstractIn this paper, we introduce a new GARCH model with an infinitely divisible distributed innovation, referred to as the rapidly decreasing tempered stable (RDTS) GARCH model. This model allows the description of some stylized empirical facts observed for stock and index returns, such as volatility clustering, the non-zero skewness and excess kurtosis for the residual distribution. Furthermore, we review the classical tempered stable (CTS) GARCH model, which has similar statistical properties. By considering a proper density transformation between infinitely divisible random variables, these GARCH models allow to find the risk-neutral price process, and hence they can be applied to option pricing. We propose algorithms to generate scenario based on GARCH models with CTS and RDTS innovation. To investigate the performance of these GARCH models, we report a parameters estimation for Dow Jones Industrial Average (DJIA) index and stocks included in this index, and furthermore to demonstrate their advantages, we calculate option prices based on these models. It should be noted that only historical data on the underlying asset and on the riskfree rate are taken into account to evaluate option prices.en_US
dc.publisher|aKIT [u.a.] |cKarlsruheen_US
dc.relation.ispartofseries|aWorking paper series in economics |x28en_US
dc.subject.keywordtempered infinitely divisible distributionen_US
dc.subject.keywordtempered stable distributionen_US
dc.subject.keywordrapidly decreasing tempered stable distributionen_US
dc.subject.keywordGARCH model option pricingen_US
dc.titleTempered stable and tempered infinitely divisible GARCH modelsen_US
dc.typeWorking Paperen_US

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