A Bayesian Beta Markov Random Field calibration of the term structure of implied risk neutral densities

Roberto Casarin, Fabrizio Leisen, German Molina and Enrique Ter Horst
Additional contact information
Fabrizio Leisen: Department of Economics, University of Kent
German Molina: Idalion Capital US LP
Enrique Ter Horst: CESA & IESA

No 2014:22, Working Papers from Department of Economics, University of Venice "Ca' Foscari"

Abstract: We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible time dependence between densities with the same maturity and for dependence across maturities at the same point in time. The assumptions on the prior distribution allow us to compound the needs of model flexibility, parameter parsimony and information pooling across densities.

Keywords: Bayesian inference; Beta random fields; Exchange Metropolis Hastings; Markov chain Monte Carlo; Risk neutral measure. (search for similar items in EconPapers)
JEL-codes: C11 C15 C33 C51 C58 G13 G17 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2014
New Economics Papers: this item is included in nep-ecm and nep-ore
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Related works:
Working Paper: A Bayesian Beta Markov Random Field Calibration of the Term Structure of Implied Risk Neutral Densities (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:ven:wpaper:2014:22

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