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Understanding portfolio efficiency with conditioning information

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  • Peñaranda, Francisco

Abstract

Contrary to the classic framework of passive strategies, if investors exploit return predictability through active strategies then there is a tension between the mean-variance frontiers that drive empirical work and the mean-variance preferences that are used in finance theory. We show that standard preferences choose portfolios on a frontier that has not been studied in the literature, develop new betas and Sharpe ratios to construct portfolio efficiency tests, and highlight some concerns with current empirical work. An empirical application to active strategies on stock portfolios sorted by size and book-to-market confirms the relevance of our theoretical results.

Suggested Citation

  • Peñaranda, Francisco, 2009. "Understanding portfolio efficiency with conditioning information," LSE Research Online Documents on Economics 24415, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:24415
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    File URL: http://eprints.lse.ac.uk/24415/
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Bansal, Ravi & Dahlquist, Magnus & Harvey, Campbell R., 2004. "Dynamic Trading Strategies and Portfolio Choice," SIFR Research Report Series 31, Institute for Financial Research.
    3. Dybvig, Philip H & Ross, Stephen A, 1985. "Differential Information and Performance Measurement Using a Security Market Line," Journal of Finance, American Finance Association, vol. 40(2), pages 383-399, June.
    4. Ferson, Wayne & Siegel, Andrew F. & Xu, Pisun (Tracy), 2006. "Mimicking Portfolios with Conditioning Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(3), pages 607-635, September.
    5. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
    6. Owen, Joel & Rabinovitch, Ramon, 1983. "On the Class of Elliptical Distributions and Their Applications to the Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 38(3), pages 745-752, June.
    7. Wayne E. Ferson & Andrew F. Siegel, 2001. "The Efficient Use of Conditioning Information in Portfolios," Journal of Finance, American Finance Association, vol. 56(3), pages 967-982, June.
    8. Hansen, Lars Peter & Richard, Scott F, 1987. "The Role of Conditioning Information in Deducing Testable," Econometrica, Econometric Society, vol. 55(3), pages 587-613, May.
    9. Dybvig, Philip H & Ross, Stephen A, 1985. "The Analytics of Performance Measurement Using a Security Market Line," Journal of Finance, American Finance Association, vol. 40(2), pages 401-416, June.
    10. Roll, Richard, 1977. "A critique of the asset pricing theory's tests Part I: On past and potential testability of the theory," Journal of Financial Economics, Elsevier, vol. 4(2), pages 129-176, March.
    11. Michael W. Brandt & Pedro Santa‐Clara, 2006. "Dynamic Portfolio Selection by Augmenting the Asset Space," Journal of Finance, American Finance Association, vol. 61(5), pages 2187-2217, October.
    12. Chamberlain, Gary, 1983. "A characterization of the distributions that imply mean--Variance utility functions," Journal of Economic Theory, Elsevier, vol. 29(1), pages 185-201, February.
    13. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
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    More about this item

    Keywords

    Beta-pricing; Dynamic portfolio strategies; Jensen’s alpha; Mean-variance frontiers; Sharpe ratios;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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