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Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?

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  • Eric Jondeau

    (HEC Lausanne and FAME)

  • Michael Rockinger

    (HEC Lausanne and FAME)

Abstract

We evaluate how departure from normality may affect the conditional allocation of wealth. The expected utility function is approximated by a forth-order Taylor expansion that allows for non-normal returns. Market returns are characterized by a joint model that captures the time dependency and the shape of the distribution. We show that under large departure from normality, the mean-variance criterion can lead to portfolio weights that differ signifficantly from those obtained using the optimal strategy accounting for non-normality. In addition, the opportunity cost for a risk-adverse investor to use the sub- optimal mean-variance criterion can be very large.

Suggested Citation

  • Eric Jondeau & Michael Rockinger, 2005. "Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?," FAME Research Paper Series rp132, International Center for Financial Asset Management and Engineering.
    • Handle: RePEc:fam:rpseri:rp132
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    Cited by:

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    2. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    3. Hsu, Ching-Chi & Chien, FengSheng, 2022. "The study of co-movement risk in the context of the Belt and Road Initiative," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1130-1152.
    4. Juliane Proelss & Denis Schweizer, 2014. "Polynomial goal programming and the implicit higher moment preferences of US institutional investors in hedge funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(1), pages 1-28, February.
    5. Markus Haas, 2007. "Do investors dislike kurtosis?," Economics Bulletin, AccessEcon, vol. 7(2), pages 1-9.
    6. Francesco Paolo Natale, 2008. "Optimisation in the presence of tail-dependence and tail risk: A heuristic approach for strategic asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 8(6), pages 374-400, February.
    7. Wang, Chou-Wen & Liu, Kai & Li, Bin & Tan, Ken Seng, 2022. "Portfolio optimization under multivariate affine generalized hyperbolic distributions," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 49-66.
    8. Karol Szafranek, 2015. "Financialisation of the commodity markets. Conclusions from the VARX DCC GARCH," EcoMod2015 8554, EcoMod.
    9. John R. Birge & Luis Chavez-Bedoya, 2016. "Portfolio optimization under a generalized hyperbolic skewed t distribution and exponential utility," Quantitative Finance, Taylor & Francis Journals, vol. 16(7), pages 1019-1036, July.
    10. repec:ebl:ecbull:v:7:y:2007:i:2:p:1-9 is not listed on IDEAS
    11. Carnero M. Angeles & Eratalay M. Hakan, 2014. "Estimating VAR-MGARCH models in multiple steps," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-27, May.
    12. Allen, David & Lizieri, Colin & Satchell, Stephen, 2020. "A comparison of non-Gaussian VaR estimation and portfolio construction techniques," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 356-368.
    13. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364.
    14. Rihab Bedoui & Houda BenMabrouk, 2017. "CAPM with various utility functions: Theoretical developments and application to international data," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343230-134, January.
    15. Li, Xiao-Ming & Zou, Li-Ping, 2008. "How do policy and information shocks impact co-movements of China's T-bond and stock markets?," Journal of Banking & Finance, Elsevier, vol. 32(3), pages 347-359, March.
    16. Maria Grazia Zoia & Gianmarco Vacca & Laura Barbieri, 2020. "Modeling Multivariate Financial Series and Computing Risk Measures via Gram–Charlier-Like Expansions," Risks, MDPI, vol. 8(4), pages 1-21, November.

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    More about this item

    Keywords

    Volatility; Skewness; Kurtosis; GARCH model; Multivariate skewed Student-t distribution; Stock returns; Asset allocation; Emerging markets;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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