Optimal Portfolio Diversification: Empirical Bayes Versus Classical Approach

Hui, Tak-Kee; Kwan, Edmond K.; Lee, Patrick Chang Boon

doi:10.1038/sj/jors/0441109

Cited by 2 publications

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“…Their results raise a statistically interesting question which is whether the Stein type estimator dominating x * (m, S) exists. Hui et al (1993) and Board and Sutcliffe (1994) supported their results by empirical studies.…”

Section: Introductionsupporting

confidence: 72%

Finite Sample Properties of Estimators for the Optimal Portfolio Weight

Mori

2004

JJSS

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This paper considers the problem of estimating the optimal portfolio weight to the mean-variance model in finance when parameters are unknown. For this purpose, we consider the following two classes of estimators. One is the class of proportional type estimators and the other is the class of Stein type estimators. First, we derive an unbiased estimator of the optimal portfolio weight, which belongs to the class of proportional type estimators. Second, we obtain dominance results within each class. From this, we showed that the unbiased proportional estimator and the maximum likelihood estimator are inadmissible.

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Section: Introductionsupporting

confidence: 72%

Finite Sample Properties of Estimators for the Optimal Portfolio Weight

Mori

2004

JJSS

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“…The means, variances and correlations of asset returns are usually estimated by their historical values, or their transformations. But the performance of portfolio models with inputs estimated in this way has been disappointing due to large estimation errors (Benati, 2015;Dhingra, 1983;Hui, et al, 1993;Levy and Simaan, 2016;Maillet, et al, 2015). In recent years a new approach to estimating portfolio inputs has been developed which recognises that asset returns are not generated by a single economic regime (Levy and Kaplanski, 2015;Bae, et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes?

2017

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Estimation errors in the inputs are the main problem when applying portfolio analysis. Markov regime switching models are used to reduce these errors, but they do not always improve outof-sample portfolio performance. We investigate the levels of transaction costs and risk aversion below which the use of two regimes is superior to one regime for an investor with a CRRA utility function, allowing for skewed and kurtic returns. Our results suggest that, due to differences in risk and transactions costs, most retail investors should use one regime models, while investment banks should use two regime models.

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Optimal Portfolio Diversification: Empirical Bayes Versus Classical Approach

Cited by 2 publications

References 0 publications

Finite Sample Properties of Estimators for the Optimal Portfolio Weight

Finite Sample Properties of Estimators for the Optimal Portfolio Weight

Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes?

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