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A Stochastic Volatility Model With Realized Measures for Option Pricing |
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| Authors: | Giacomo Bormetti Roberto Casarin Fulvio Corsi Giulia Livieri |
| Affiliation: | 1. Department of Mathematics, University of Bologna, Piazza di Porta S. Donato, 5, 40126, Bologna, Italy (giacomo.bormetti@unibo.it);2. Department of Economics, Ca’ Foscari University of Venice, Fondamenta S. Giobbe, 873, Venezia, Italy (r.casarin@unive.it);3. Department of Economics and Management, University of Pisa, Via Cosimo Ridolfi, 10, 56124, Pisa, Italy;4. Department of Economics, City University London, Northampton Square, EC1V 0HB, London, UK (fulvio.corsi@unipi.it);5. Scuola Normale Superiore, Piazza dei Cavalieri, 7, 56126, Pisa, Italy (giulia.livieri@sns.it) |
| Abstract: | AbstractBased on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized measures to the latent conditional variance. A semi-analytical option pricing framework is developed for this class of models. In addition, we provide analytical filtering and smoothing recursions for the basic specification of the model, and an effective MCMC algorithm for its richer variants. The empirical analysis shows the effectiveness of filtering and smoothing realized measures in inflating the latent volatility persistence—the crucial parameter in pricing Standard and Poor’s 500 Index options. |
| Keywords: | Bayesian inference High-frequency data Monte Carlo Markov chain Option pricing Realized volatility |