Bayesian Option Pricing Using Asymmetric GARCH Models

Posted: 14 Apr 2005

See all articles by Luc Bauwens

Luc Bauwens

Université catholique de Louvain

Michel Lubrano

Ecole des Hautes Etudes en Sciences Sociales (EHESS)

Abstract

This paper shows how one can compute option prices from a Bayesian inference viewpoint, using a GARCH model for the dynamics of the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The predictive distribution of this function provides a natural metric, provided it is neutralised with respect to risk, for gauging the predictive option price or other option evaluations. The proposed method is compared to the Black and Scholes evaluation, in which a marginal mean volatility is plugged, but which does not provide a natural metric. The methods are illustrated using symmetric, asymmetric and smooth transition GARCH models with data on a stock index in Brussels.

Keywords: Bayesian inference, GARCH, Option pricing, simulation

JEL Classification: C11, C15, C22, G13

Suggested Citation

Bauwens, Luc and Lubrano, Michel, Bayesian Option Pricing Using Asymmetric GARCH Models. Available at SSRN: https://ssrn.com/abstract=691921

Luc Bauwens (Contact Author)

Université catholique de Louvain ( email )

CORE
34 Voie du Roman Pays
B-1348 Louvain-la-Neuve, b-1348
Belgium
32 10 474321 (Phone)
32 10 474301 (Fax)

Michel Lubrano

Ecole des Hautes Etudes en Sciences Sociales (EHESS) ( email )

Greqam, Vieille Charité
2 rue de la Charité
13002 Marseille
France

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