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Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK

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Author Info

  • Hagströmer, Björn

    ()
    (School of Business, Stockholm University)

  • Anderson, Richard G.

    ()
    (Federal Reserve Bank of St. Louis)

  • Binner, Jane

    ()
    (Sheffield University)

  • Elger, Thomas

    (Department of Economics, Lund University)

  • Nilsson, Birger

    ()
    (Department of Economics, Lund University)

Abstract

In the Full-Scale Optimization approach the complete empirical financial return probability distribution is considered; and the utility maximizing solution is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory; under which Full-Scale Optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality; the findings indicate much broader usefulness of Full-Scale Optimization than has earlier been shown. The results hold in and out of sample; and the performance improvements are given in terms of utility as well as certainty equivalents.

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Bibliographic Info

Paper provided by Lund University, Department of Economics in its series Working Papers with number 2008:1.

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Length: 32 pages
Date of creation: 24 Oct 2007
Date of revision:
Publication status: Published in The Manchester School, 2008, pages 134-156.
Handle: RePEc:hhs:lunewp:2008_001

Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/en
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Keywords: portfolio choice; utility maximization; full-scale optimization; S-shaped utility; bilinear utility;

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References

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  1. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
  2. Arditti, Fred D, 1969. "A Utility Function Depending on the First Three Moments: Reply," Journal of Finance, American Finance Association, vol. 24(4), pages 720, September.
  3. Samuelson, Paul A, 1970. "The Fundamental Approximation Theorem of Portfolio Analysis in terms of Means, Variances, and Higher Moments," Review of Economic Studies, Wiley Blackwell, vol. 37(4), pages 537-42, October.
  4. Gourieroux, C. & Monfort, A., 2005. "The econometrics of efficient portfolios," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 1-41, January.
  5. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-17, June.
  6. Scott, Robert C & Horvath, Philip A, 1980. " On the Direction of Preference for Moments of Higher Order Than the Variance," Journal of Finance, American Finance Association, vol. 35(4), pages 915-19, September.
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Cited by:
  1. David Johnstone & Dennis Lindley, 2013. "Mean-Variance and Expected Utility: The Borch Paradox," Papers 1306.2728, arXiv.org.
  2. George Yungchih Wang, 2012. "Evaluating an Investment Project in an Incomplete Market," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 055-073, June.
  3. de Farias Neto, Joao Jose, 2008. "S-shaped utility, subprime crash and the black swan," MPRA Paper 12122, University Library of Munich, Germany.

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