A Bayesian Information Criterion for Portfolio Selection
32 Pages Posted: 17 Jun 2011
Date Written: May 8, 2011
The mean-variance theory of Markowitz (1952) indicates that large investment portfolios naturally provide better risk diversication than small ones. However, due to parameter estimation errors, one may find ambiguous results in practice. Hence, it is essential to identify relevant stocks to alleviate the impact of estimation error in portfolio selection. To this end, we propose a linkage condition to link the relevant and irrelevant stock returns via their conditional regression relationship. Subsequently, we obtain a BIC selection criterion that enables us to identify relevant stocks consistently. Numerical studies indicate that BIC outperforms commonly used portfolio strategies in the literature.
Keywords: Bayesian Information Criterion, Minimal Variance Portfolio, Portfolio Selection, Risk Diversification
JEL Classification: C12, C13
Suggested Citation: Suggested Citation