Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87140 
Year of Publication: 
2007
Series/Report no.: 
Quaderni di Dipartimento - EPMQ No. 197
Publisher: 
Università degli Studi di Pavia, Dipartimento di Economia Politica e Metodi Quantitativi (EPMQ), Pavia
Abstract: 
We focus on robust Bayesian estimation of the systematic risk of an asset in presence of outlying points. We assume that the returns follow independent normal distributions with a product partition structure on the parameters of interest. A Bayesian decision theoretical approach is used to identify the partition that best separates standard and atypical data points. We apply a nonsmooth optimization algorithm to minimize the expected value of a given loss function. The methodology is illustrated with reference to the IPSA stock market index and the MIBTEL one.
Subjects: 
Capital Asset Pricing Model
Markov Chain Monte Carlo
outlier identification
product partition models
score function
Document Type: 
Working Paper

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