Discriminating between GARCH models for option pricing by their ability to compute accurate VIX measures

Christophe Chorro () and Rahantamialisoa H. Fanirisoa Zazaravaka ()
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Christophe Chorro: Centre d'Economie de la Sorbonne, https://sites.google.com/view/chorro-christophe/
Rahantamialisoa H. Fanirisoa Zazaravaka: Centre d'Economie de la Sorbonne, and Università Ca' Foscari of Venezia - Dipartimento di Economia

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: 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 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: GARCH option pricing models; GARCH implied VIX; estimation strategies; non-monotonic stochastic discount factors (search for similar items in EconPapers)
JEL-codes: C52 G13 (search for similar items in EconPapers)
Date: 2019-10
New Economics Papers: this item is included in nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:19014

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