Option prices under Bayesian learning: implied volatility dynamics and predictive densities

Guidolin, Massimo and Timmermann, Allan (2001) Option prices under Bayesian learning: implied volatility dynamics and predictive densities. Financial Markets Group Discussion Papers (397). Financial Markets Group, The London School of Economics and Political Science, London, UK.

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Abstract

This paper shows that many of the empirical biases of the Black and Scholes option pricing model can be explained by Bayesian learning effects. In the context of an equilibrium model where dividend news evolve on a binomial lattice with unknown but recursively updated probabilities we derive closed-form pricing formulas for European options. Learning is found to generate asymmetric skews in the implied volatility surface and systematic patterns in the term structure of option prices. Data on S&P 500 index option prices is used to back out the parameters of the underlying learning process and to predict the evolution in the cross-section of option prices. The proposed model leads to lower out-of-sample forecast errors and smaller hedging errors than a variety of alternative option pricing models, including Black-Scholes and a GARCH model.

Item Type:	Monograph (Discussion Paper)
Official URL:	https://www.fmg.ac.uk/
Additional Information:	© 2001 The Authors
Divisions:	Financial Markets Group
Subjects:	H Social Sciences > HC Economic History and Conditions H Social Sciences > HG Finance
JEL classification:	G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search; Learning; Information and Knowledge; Communication; Belief
Date Deposited:	04 Jul 2023 09:06
Last Modified:	16 Sep 2023 00:02
URI:	http://eprints.lse.ac.uk/id/eprint/119091

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