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A New Class of Bayesian Semiparametric Models with Applications to Option Pricing


Marcin T. Kacperczyk


New York University (NYU) - Leonard N. Stern School of Business; National Bureau of Economic Research (NBER); New York University (NYU) - Department of Finance

Paul Damien


University of Texas at Austin - McCombs School of Business

Stephen G. Walker


University of Bath - School of Mathematical Sciences

April 13, 2011

NYU Stern School of Business Working Paper
McCombs Research Paper Series No. IROM-08-05

Abstract:     
This paper develops a new family of Bayesian semiparametric models. A particular member of this family is used to model option prices with the aim of improving out-of-sample predictions. A detailed empirical analysis is made for European index call and put options to illustrate the ideas.

Number of Pages in PDF File: 41

Keywords: Bayesian semiparametric model, option pricing

JEL Classification: G13, G12

working papers series


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Date posted: August 8, 2003 ; Last revised: June 15, 2011

Suggested Citation

Kacperczyk, Marcin T., Damien, Paul and Walker, Stephen G., A New Class of Bayesian Semiparametric Models with Applications to Option Pricing (April 13, 2011). NYU Stern School of Business Working Paper; McCombs Research Paper Series No. IROM-08-05. Available at SSRN: http://ssrn.com/abstract=416583 or http://dx.doi.org/10.2139/ssrn.416583

Contact Information

Marcin T. Kacperczyk (Contact Author)
New York University (NYU) - Leonard N. Stern School of Business ( email )
44 West 4th Street
New York, NY NY 10012
United States
National Bureau of Economic Research (NBER) ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
New York University (NYU) - Department of Finance
Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States
Paul Damien
University of Texas at Austin - McCombs School of Business ( email )
Austin, TX 78712
United States
Stephen G. Walker
University of Bath - School of Mathematical Sciences ( email )
Bath, BA2 7AY
United Kingdom
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