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Fast Filtering with Large Option Panels: Implications for Asset Pricing

Published online by Cambridge University Press:  13 June 2023

Arnaud Dufays ,
Kris Jacobs Open the ORCID record for Kris Jacobs [Opens in a new window] ,
Yuguo Liu  and
Jeroen Rombouts
Arnaud Dufays
Affiliation:
EDHEC Business School arnaud.dufays@edhec.edu
Kris Jacobs*
Affiliation:
University of Houston Bauer College of Business
Yuguo Liu
Affiliation:
Morgan Stanley yuguo.liu@morganstanley.com
Jeroen Rombouts
Affiliation:
ESSEC Business School rombouts@essec.edu
*
kjacobs@bauer.uh.edu (corresponding author)
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Abstract

The cross section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle Markov Chain Monte Carlo framework with a novel filtering approach and illustrate our method by estimating index option pricing models. Estimates of variance risk premiums, variance mean reversion, and higher moments differ from the literature. We show that these differences are due to the composition of the option sample. Restricting the option sample’s maturity dimension has the strongest impact on parameter inference and option fit in these models.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 32
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

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Footnotes

We are very grateful to the Canadian Derivatives Institute (CDI) for financial support. We thank Torben Andersen, Peter Christoffersen, Francois Cocquemas, Toby Daglish, Christian Dorion, Hitesh Doshi, Jin Duan, Bjorn Eraker, Andras Fulop, Rene Garcia, Mohammad Ghaderi, Christian Gourieroux, Bruce Grundy, Jinji Hao, Junye Li, Scott Murray, Federico Nardari, Chay Ornthanalai, Manuela Pedio, Nick Polson, Olivier Scaillet, David Schreindorfer, Gustavo Schwenkler, Sang Seo, Viktor Todorov, Thijs Van Der Heijden, Bas Werker, James Yae, Morad Zekhnini, and participants in seminars at Georgia State, George Washington, West Virginia, the Universities of Melbourne and Wellington, UNSW, the SFS Cavalcade, the ESSEC: 2018 Workshop on Bayesian Methods in Finance, and the Vienna: 2021 Workshop on the Econometrics of Option Markets for helpful discussions and comments. All errors are our own.

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