Bayesian Option Pricing using Asymmetric Garch Models
Luc Bauwens () and
Michel Lubrano ()
G.R.E.Q.A.M. from Universite Aix-Marseille III
This paper shows how one can compute option prices from a Bayesian inference view point, using a GARCH model for the dynamics of the 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 the 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: PRICING; EXPECTATIONS; ECONOMETRIC MODELS (search for similar items in EconPapers)
JEL-codes: C11 C15 C22 G13 (search for similar items in EconPapers)
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Journal Article: Bayesian option pricing using asymmetric GARCH models (2002)
Working Paper: Bayesian option pricing using asymmetric GARCH models (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:fth:aixmeq:00a18
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