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  • 标题:Estimation Risk Modeling in Optimal Portfolio Selection: An Empirical Study from Emerging Markets
  • 本地全文:下载
  • 作者:Sarayut Nathaphan ; Pornchai Chunhachinda
  • 期刊名称:Economics Research International
  • 印刷版ISSN:2090-2123
  • 电子版ISSN:2090-2131
  • 出版年度:2010
  • 卷号:2010
  • DOI:10.1155/2010/340181
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Efficient portfolio is a portfolio that yields maximum expected return given a level of risk or has a minimum level of risk given a level of expected return. However, the optimal portfolios do not seem to be as efficient as intended. Especially during financial crisis period, optimal portfolio is not an optimal investment as it does not yield maximum return given a specific level of risk, and vice versa. One possible explanation for an unimpressive performance of the seemingly efficient portfolio is incorrectness in parameter estimates called “estimation risk in parameter estimates”. Six different estimating strategies are employed to explore ex-post-portfolio performance when estimation risk is incorporated. These strategies are traditional Mean-Variance (EV), Adjusted Beta (AB) approach, Resampled Efficient Frontier (REF), Capital Asset Pricing Model (CAPM), Single Index Model (SIM), and Single Index Model incorporating shrinkage Bayesian factor namely, Bayesian Single Index Model (BSIM). Among the six alternative strategies, shrinkage estimators incorporating the single index model outperform other traditional portfolio selection strategies. Allowing for asset mispricing and applying Bayesian shrinkage adjusted factor to each asset's alpha, a single factor namely, excess market return is adequate in alleviating estimation uncertainty.
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