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


  • 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)


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.

Suggested Citation

  • Hagströmer, Björn & Anderson, Richard G. & Binner, Jane & Elger, Thomas & Nilsson, Birger, 2007. "Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK," Working Papers 2008:1, Lund University, Department of Economics.
  • Handle: RePEc:hhs:lunewp:2008_001

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    References listed on IDEAS

    1. J. Tobin, 1958. "Liquidity Preference as Behavior Towards Risk," Review of Economic Studies, Oxford University Press, vol. 25(2), pages 65-86.
    2. Gourieroux, C. & Monfort, A., 2005. "The econometrics of efficient portfolios," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 1-41, January.
    3. Arditti, Fred D, 1969. "A Utility Function Depending on the First Three Moments: Reply," Journal of Finance, American Finance Association, vol. 24(4), pages 720-720, September.
    4. 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 915-919, September.
    5. Paul A. Samuelson, 1970. "The Fundamental Approximation Theorem of Portfolio Analysis in terms of Means, Variances and Higher Moments," Review of Economic Studies, Oxford University Press, vol. 37(4), pages 537-542.
    6. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    7. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    8. 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 308-317, June.
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    Cited by:

    1. de Farias Neto, Joao Jose, 2008. "S-shaped utility, subprime crash and the black swan," MPRA Paper 12122, University Library of Munich, Germany.
    2. David Johnstone & Dennis Lindley, 2013. "Mean-Variance and Expected Utility: The Borch Paradox," Papers 1306.2728,
    3. 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.

    More about this item


    portfolio choice; utility maximization; full-scale optimization; S-shaped utility; bilinear utility;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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