Optimal clustering in Bayesian capital asset pricing model

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Quaderni di Dipartimento - EPMQ ; No. 197

Classification and Topics

• Classification: Wirtschaft
• Subject: Capital Asset Pricing Model ; Markov Chain Monte Carlo ; outlier identification ; product partition models ; score function

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): De Giuli, Maria Elena ; Tarantola, Claudia ; Uberti, Pierpaolo
• Event: Veröffentlichung
• (who): Università degli Studi di Pavia, Dipartimento di Economia Politica e Metodi Quantitativi (EPMQ)
• (where): Pavia
• (when): 2007

Further information

• Handle: http://hdl.handle.net/10419/87140
• Last update: 10.03.2025, 11:42 AM CET