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Sampling Errors and Portfolio Efficient Analysis

Author

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  • Kroll, Yoram
  • Levy, Haim

Abstract

Studies which deal with portfolio efficiency analysis can be divided into two main categories: (a) those concerned with the development of normative decision rules; and (b) those that discuss the application of the normative rules to empirical data. Most of the research on portfolio efficiency analysis uses some set of empirical data, without considering the possible errors which may arise when a sample rather than the entire population is examined. The prevailing neglect of the sampling errors is a clear reflection of the complexity of the issue.

Suggested Citation

  • Kroll, Yoram & Levy, Haim, 1980. "Sampling Errors and Portfolio Efficient Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(3), pages 655-688, September.
    • Handle: RePEc:cup:jfinqa:v:15:y:1980:i:03:p:655-688_00
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    Citations

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    Cited by:

    1. Annaert, Jan & Osselaer, Sofieke Van & Verstraete, Bert, 2009. "Performance evaluation of portfolio insurance strategies using stochastic dominance criteria," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 272-280, February.
    2. Post, G.T., 2003. "Statistical Inference on Stochastic Dominance Efficiency. Do Omitted Risk Factors Explain the Size and Book-to-Market Effects?," ERIM Report Series Research in Management ERS-2003-017-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Smimou, K. & Bector, C.R. & Jacoby, G., 2008. "Portfolio selection subject to experts' judgments," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1036-1054, December.
    4. Roger P. Bey & Richard C. Burgess & Richard B. Kearns, 1984. "Moving Stochastic Dominance: An Alternative Method For Testing Market Efficiency," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 7(3), pages 185-196, September.
    5. Oliver Linton & Thierry Post & Yoon‐Jae Whang, 2014. "Testing for the stochastic dominance efficiency of a given portfolio," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 59-74, June.
    6. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    7. William E. Stein & Roger C. Pfaffenberger & Dan W. French, 1987. "Sampling Error In First Order Stochastic Dominance," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 10(3), pages 259-268, September.
    8. Smimou, K. & Bector, C.R. & Jacoby, G., 2007. "A subjective assessment of approximate probabilities with a portfolio application," Research in International Business and Finance, Elsevier, vol. 21(2), pages 134-160, June.
    9. Post, Thierry, 2005. "A Stochastic Dominance Approach to Spanning. With an Application to the January Effect/Una aproximación mediante la metodología del dominio estocástico al fenómeno del SPANNING. Una aplicación al efec," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 7-25, Abril.
    10. Marat Molyboga & Seungho Baek & John F. O. Bilson, 2017. "Assessing hedge fund performance with institutional constraints: evidence from CTA funds," Journal of Asset Management, Palgrave Macmillan, vol. 18(7), pages 547-565, December.
    11. Gourieroux, C. & Monfort, A., 2005. "The econometrics of efficient portfolios," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 1-41, January.
    12. Moshe Ben-Horim, 1990. "Stochastic Dominance And Truncated Sample Data," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 13(2), pages 105-116, June.
    13. Wang, Ming-Hui & Ke, Mei-Chu & Liang Liao, Tung & Chiang, Yi-Chein & Hsu, Chuan-Hao, 2020. "Alternative estimation method of earnings growth rate for PEGR strategy," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    14. Thierry Post & Iňaki Rodríguez Longarela, 2021. "Risk Arbitrage Opportunities for Stock Index Options," Operations Research, INFORMS, vol. 69(1), pages 100-113, January.
    15. Post, G.T., 2001. "Testing for Stochastic Dominance with Diversification Possibilities," ERIM Report Series Research in Management ERS-2001-38-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Timo Kuosmanen, 2004. "Efficient Diversification According to Stochastic Dominance Criteria," Management Science, INFORMS, vol. 50(10), pages 1390-1406, October.
    17. Post, G.T., 2001. "Spanning and Intersection: a stochastic dominance approach," ERIM Report Series Research in Management ERS-2001-63-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. J. Annaert & S. Van Osselaer & B. Verstraete, 2007. "Performance evaluation of portfolio insurance strategies using stochastic dominance criteria," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/473, Ghent University, Faculty of Economics and Business Administration.
    19. Post, G.T., 2002. "A Stochastic Dominance Approach to Spanning," ERIM Report Series Research in Management ERS-2002-01-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Thierry Post & Valerio Potì, 2017. "Portfolio Analysis Using Stochastic Dominance, Relative Entropy, and Empirical Likelihood," Management Science, INFORMS, vol. 63(1), pages 153-165, January.

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