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Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices

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Abstract

In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Implicit posterior densities for the parameters of the volatility model, for the latent volatilities and for the market price of volatility risk are produced. The method involves augmenting the data generating process associated with a panel of option prices with the probability density function describing the dynamics of the underlying bivariate spot price and volatility process. Posterior results are produced via a hybrid Markov Chain Monte Carlo sampling algorithm. Candidate draws which assume a given dynamic process for the volatility are re-weighted according to the information in both the option and spot price data. The method is illustrated using the Heston (1993) stochastic volatility model, based on data simulated to mimic the features of recent S&P500 spot and option price data. The way in which alternative option pricing models can be ranked, via Bayes Factors and via fit, predictive and hedging performance, is demonstrated.

Suggested Citation

  • C.S. Forbes & G.M. Martin & J. Wright, 2002. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices," Monash Econometrics and Business Statistics Working Papers 2/02, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2002-2
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2002/wp2-02.pdf
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    References listed on IDEAS

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    Cited by:

    1. Silvia Centanni, 2011. "Computing option values by pricing kernel with a stochatic volatility model," Working Papers 05/2011, University of Verona, Department of Economics.
    2. Cappuccio Nunzio & Lubian Diego & Raggi Davide, 2004. "MCMC Bayesian Estimation of a Skew-GED Stochastic Volatility Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-31, May.
    3. Nunzio Cappuccio & Diego Lubian & Davide Raggi, 2006. "Investigating asymmetry in US stock market indexes: evidence from a stochastic volatility model," Applied Financial Economics, Taylor & Francis Journals, vol. 16(6), pages 479-490.

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    More about this item

    Keywords

    Option Pricing; Stochastic Volatility; Volatility Risk; Bayesian Implicit Inference; Markov Chain Monte Carlo;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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