Smile from the Past: A general option pricing framework with multiple volatility and leverage components
A. A. Majewski,
G. Bormetti and
F. Corsi
Working Papers from Department of Economics, City University London
Abstract:
In the current literature, the analytical tractability of discrete time option pricing models is guarantee only for rather specific type of models and pricing kernels. We propose a very general and fully analytical option pricing framework encompassing a wide class of discrete time models featuring multiple components structure in both volatility and leverage and a flexible pricing kernel with multiple risk premia. Although the proposed framework is general enough to include either GARCH-type volatility, Realized Volatility or a combination of the two, in this paper we focus on realized volatility option pricing models by extending the Heterogeneous Autoregressive Gamma (HARG) model of Corsi et al. (2012) to incorporate heterogeneous leverage structures with multiple components, while preserving closed-form solutions for option prices. Applying our analytically tractable asymmetric HARG model to a large sample of S&P 500 index options, we evidence its superior ability to price out-of-the-money options compared to existing benchmarks.
Date: 2013
New Economics Papers: this item is included in nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://openaccess.city.ac.uk/id/eprint/2925/1/13_11_CorsiWP.pdf
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cty:dpaper:13/11
Access Statistics for this paper
More papers in Working Papers from Department of Economics, City University London Department of Economics, Social Sciences Building, City University London, Whiskin Street, London, EC1R 0JD, United Kingdom,. Contact information at EDIRC.
Bibliographic data for series maintained by Research Publications Librarian ().