Shrinkage Bayesian portfolio incorporating factor model in optimal portfolio selection: an empirical study.
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Issued Date
2008
Resource Type
Language
eng
Rights
Mahidol University
Suggested Citation
Sarayut Nathapana, Varumpa Temaismithi, Pornchai Chunhachinda, Charlie Charoenwongc (2008). Shrinkage Bayesian portfolio incorporating factor model in optimal portfolio selection: an empirical study.. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/40193
Title
Shrinkage Bayesian portfolio incorporating factor model in optimal portfolio selection: an empirical study.
Other Contributor(s)
Abstract
Parameter estimation based on shrinkage estimation under empirical Bayesian analysis has been proven by previous studies to outperform the maximum likelihood estimator (MLE). This study extends previous works by incorporating both the single index and the three-factor models in an empirical Bayesian approach to estimate grand mean. Six alternative strategies are employed to explore ex post portfolio performance when estimation risk is incorporated. These strategies are:
naïve (equal weighted), passive (value weighted), mean-variance, Bayes-Stein, Bayes-CAPM, and Bayes-3-Factors portfolios. Among the six alternative strategies, the traditional, naïve, and passive portfolio
strategies are outperformed by the shrinkage estimators because sample or historical averages seem to contain little useful information in the context of portfolio selection. However, shrinkage estimators incorporating the single index model have shown a noticeable improvement over optimized
portfolios based on historical estimates. The result suggests that it is not necessary to include more explanatory factors in a shrinkage Bayesian incorporating factor model. Therefore, the shrinkage Bayesian portfolio,
incorporating single index model or Bayes-CAPM seems to be an appropriate portfolio selection strategy.
Description
Midwest Finance Research Conference. Texas, USA. February 26 - March 2, 2008