Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market
AbstractThis paper develops the method for pricing bivariate contingent claims under general autoregressive conditionally heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as well as the time-varying volatility that are often found in financial data, generalized hyperbolic (GH) distribution is used for innovations. As the association between the underlying assets may vary over time, the dynamic copula approach is considered. Therefore, the proposed method proves to play an important role in pricing bivariate option. The approach is illustrated for Chinese market with one type of better-of-two markets claims: call option on the better performer of Shanghai Stock Composite Index and Shenzhen Stock Composite Index. Results show that the option prices obtained by the GARCH-GH model with time-varying copula differ substantially from the prices implied by the GARCH-Gaussian dynamic copula model. Moreover, the empirical work displays the advantage of the suggested method.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal The European Journal of Finance.
Volume (Year): 15 (2009)
Issue (Month): 7-8 ()
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Other versions of this item:
- Dominique Guégan & Jing Zhang, 2007. "Pricing bivariate option under GARCH-GH model with dynamic copula : application for Chinese market," Documents de travail du Centre d'Economie de la Sorbonne b07057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
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- Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00375765, HAL.
- Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00368334, HAL.
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