Robust Regression for Capital Asset Pricing Model Using Bayesian Approach

K. Autchariyapanitkul, K. Kunasri, S. Sriboonchitta

Abstract

This study investigate the performance of a portfolio based on capitalasset pricing model using a Bayesian statistics approach. We use a hierarchicalmodel robustly to estimate the systematic risk of an asset. We assume that thereturns follow independent normal distributions. MCMC sampling is applied tocalculate all the parameters in the model. Finally, the Bayesian method gives usthe probability of every possible asset returns, given the market returns and alsothe posterior predictions is a clue that the model could be improved.