Option pricing with asymmetric heteroskedastic normal mixture models

Jeroen Rombouts and Lars Stentoft

No 2010049, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: This paper uses asymmetric heteroskedastic normal mixture models to fit return data and to price options. The models can be estimated straightforwardly by maximum likelihood, have high statistical fit when used on S&P 500 index return data, and allow for substantial negative skewness and time varying higher order moments of the risk neutral distribution. When forecasting out-of-sample a large set of index options between 1996 and 2009, substantial improvements are found compared to several benchmark models in terms of dollar losses and the ability to explain the smirk in implied volatilities. Overall, the dollar root mean squared error of the best performing benchmark component model is 39% larger than for the mixture model. When considering the recent financial crisis this difference increases to 69%.

Keywords: asymmetric heteroskadastic models; finite mixture models; option pricing; out-of- sample prediction; statistical fit (search for similar items in EconPapers)
JEL-codes: C11 C15 C22 G13 (search for similar items in EconPapers)
Date: 2010-08-01
New Economics Papers: this item is included in nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Journal Article: Option pricing with asymmetric heteroskedastic normal mixture models (2015)
Working Paper: Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models (2010)
Working Paper: Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2010049

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