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Applying Portfolio Change and Conditional Performance Measures: The Case of Industry Rotation via the Dynamic Investment Model

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  • Grauer, Robert R
  • Hakansson, Nils H

Abstract

This paper applies portfolio change and conditional performance measures to assess the performance of the dynamic investment model in various industry-rotation settings spanning the 1934-95 period. The dynamic investment model employs the empirical probability assessment approach in raw form. In addition, it incorporates three adjustments for estimation error: James-Stein, Bayes-Stein, and CAPM-based corrections. The tests are unanimous in their conclusion that the excess returns attained by the (unadjusted) historic, the Bayes-Stein, and the James-Stein estimators are (sometimes highly) statistically significant over the 1966-95 and 1966-81 sub-periods. This lends support to the idea that the joint empirical probability assessment approach based on the recent past, with and without Stein-based corrections for estimation error, contains information that can be profitably exploited. The relationship of these findings to the extant literature on momentum and contrarian strategies is addressed. Copyright 2001 by Kluwer Academic Publishers

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  • Grauer, Robert R & Hakansson, Nils H, 2001. "Applying Portfolio Change and Conditional Performance Measures: The Case of Industry Rotation via the Dynamic Investment Model," Review of Quantitative Finance and Accounting, Springer, vol. 17(3), pages 237-265, November.
    • Handle: RePEc:kap:rqfnac:v:17:y:2001:i:3:p:237-65
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    Cited by:

    1. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    2. Luis Ferruz Agudo & Maria Vargas Magallon & Jose Sarto, 2006. "Evaluation of performance and conditional information: the case of Spanish mutual funds," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 803-817.
    3. Hagelin, Niclas & Pramborg, Bengt, 2004. "Dynamic investment strategies with and without emerging equity markets," Emerging Markets Review, Elsevier, vol. 5(2), pages 193-215, June.
    4. Stefano Gubellini, 2014. "Conditioning information and cross-sectional anomalies," Review of Quantitative Finance and Accounting, Springer, vol. 43(3), pages 529-569, October.
    5. Tristan Nguyen & Gerhard Wörtche, 2012. "Review of the performance and robustness of several investment strategies applied to an international equity portfolio," Journal of Asset Management, Palgrave Macmillan, vol. 13(1), pages 58-75, February.
    6. Ferruz Agudo, Luis & Vargas Magallón, María & Nievas López, J., 2008. "¿Utilizan los gestores españoles de fondos de inversión información privada en sus labores de gestión?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 26, pages 257-278, Septiembr.
    7. Glensk, Barbara & Madlener, Reinhard, 2011. "Dynamic Portfolio Selection Methods for Power Generation Assets," FCN Working Papers 16/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    8. Zhang, Xinyu & Chen, Ti & Wan, Alan T.K. & Zou, Guohua, 2009. "Robustness of Stein-type estimators under a non-scalar error covariance structure," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2376-2388, November.

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