Discriminating between GARCH models for option pricing by their ability to compute accurate VIX measures
Christophe Chorro () and
Fanirisoa Rahantamialisoa Hasinavonizaka Zazaravaka ()
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Christophe Chorro: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Fanirisoa Rahantamialisoa Hasinavonizaka Zazaravaka: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, University of Ca’ Foscari [Venice, Italy]
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
In this paper, we discuss the pricing performances of a large collection of GARCH models by questioning the global synergy between the choice of the affine/non-affine GARCH specification, the use of competing alternatives to the Gaussian distribution, the selection of an appropriate pricing kernel and the choice of different estimation strategies based on several sets of financial information. Furthermore, the study answers an important question in relation to the correlation between the performance of a pricing scheme and its ability to forecast VIX dynamics. VIX analysis clearly appears as a parsimonious first-stage filter to discard the worst GARCH option pricing models.
Keywords: non-monotonic stochastic discount factors; estimation strategies; GARCH implied VIX; GARCH option pricing models (search for similar items in EconPapers)
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Published in 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-02323959
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