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Pricing Australian S&P200 Options: A Bayesian Approach Based on Generalized Distributional Forms

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Author Info

  • David B. Flynn
  • Simone D. Grose

    ()

  • Gael M. Martin

    ()

  • Vance L. Martin

Abstract

A new class of option price models is developed and applied to options on the Australian S&P200 Index. The class of models generalizes the traditional Black-Scholes framework by accommodating time-varying conditional volatility, skewness and excess kurtosis in the underlying returns process. An important property of the more general pricing models is that the computational requirements are practically the same as those associated with the Black-Scholes model, with both methods being based on one-dimensional integrals. Bayesian inferential methods are used to evaluate a range of models nested in the general framework, using observed market option prices. The evaluation is based on posterior distributions estimated for the parameters of the alternative models, as well as posterior model probabilities, out-of-sample predictive performance and implied volatility smiles. The empirical results provide strong evidence that time-varying volatility, leptokurtosis and skewness are priced in Australian stock market options.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2003/wp6-03.pdf
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Bibliographic Info

Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 6/03.

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Length: 30 pages
Date of creation: Feb 2003
Date of revision:
Handle: RePEc:msh:ebswps:2003-6

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Related research

Keywords: Bayesian Option Pricing; Leptokurtosis; Skewness; Time-Varying Volatility; Option Price Prediction; Implied Volatility Smiles;

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Cited by:
  1. Stamey, James & Gerlach, Richard, 2007. "Bayesian sample size determination for case-control studies with misclassification," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2982-2992, March.
  2. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 4(1), pages 74-96, December.

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