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De Giuli, Maria Elena
Tarantola, Claudia
Uberti, Pierpaolo
Year of Publication: 
Series/Report no.: 
Quaderni di Dipartimento, EPMQ, Università degli Studi di Pavia 197
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.
Capital Asset Pricing Model
Markov Chain Monte Carlo
outlier identification
product partition models
score function
Document Type: 
Working Paper

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