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On the out-of-sample importance of skewness and asymetric dependence for asset allocation

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  • Patton, Andrew J.

Abstract

Recent studies in the empirical finance literature have reported evidence of two types of asymmetries in the joint distribution of stock returns. The Þrst is skewness in the distribution of individual stock returns, while the second is an asymmetry in the dependence between stocks: stock returns appear to be more highly correlated during market downturns than during market upturns. In this paper we examine the economic and statistical significance of these asymmetries for asset allocation decisions in an out-of-sample setting. We consider the problem of a CRRA investor allocating wealth between the risk-free asset, a small-cap and a large-cap portfolio, using monthly data. We use models that can capture time-varying means and variances of stock returns, and also the presence of time-varying skewness and kurtosis. Further, we use copula theory to construct models of the time-varying dependence structure that allow for greater dependence during bear markets than bull markets. The importance of these two asymmetries for asset allocation is assessed by comparing the performance of a portfolio based on a normal distribution model with a portfolio based on a more ßexible distribution model. For a variety of performance measures and levels of risk aversion our results suggest that capturing skewness and asymmetric dependence leads to gains that are economically signiÞcant, and statistically significant in some cases.

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  • Patton, Andrew J., 2002. "On the out-of-sample importance of skewness and asymetric dependence for asset allocation," LSE Research Online Documents on Economics 24951, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:24951
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    1. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
    2. Kandel, Shmuel & Stambaugh, Robert F, 1996. "On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
    3. Patton, Andrew J, 2001. "Modelling Time-Varying Exchange Rate Dependence Using the Conditional Copula," University of California at San Diego, Economics Working Paper Series qt01q7j1s2, Department of Economics, UC San Diego.
    4. Yacine AÏT‐SAHALI & Michael W. Brandt, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, August.
    5. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(4), pages 465-487, December.
    6. Michael Rockinger & Eric Jondeau, 2001. "Conditional Dependency of Financial Series: An Application of Copulas," Working Papers hal-00601478, HAL.
    7. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
    8. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
    9. Peter Reinhard Hansen, 2001. "An Unbiased and Powerful Test for Superior Predictive Ability," Working Papers 2001-06, Brown University, Department of Economics.
    10. Lim, Kian-Guan, 1989. "A New Test of the Three-Moment Capital Asset Pricing Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(2), pages 205-216, June.
    11. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    12. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    13. West, Kenneth D. & Edison, Hali J. & Cho, Dongchul, 1993. "A utility-based comparison of some models of exchange rate volatility," Journal of International Economics, Elsevier, vol. 35(1-2), pages 23-45, August.
    14. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    15. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    16. Joshua Rosenberg, 1999. "Semiparametric Pricing of Multivariate Contingent Claims," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-028, New York University, Leonard N. Stern School of Business-.
    17. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    18. Michael W. Brandt, 1999. "Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach," Journal of Finance, American Finance Association, vol. 54(5), pages 1609-1645, October.
    19. Joshua V. Rosenberg, 2003. "Nonparametric pricing of multivariate contingent claims," Staff Reports 162, Federal Reserve Bank of New York.
    20. Miller, Douglas J. & Liu, Wei-han, 2002. "On the recovery of joint distributions from limited information," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 259-274, March.
    21. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 433-495.
    22. Weiss, Andrew A, 1996. "Estimating Time Series Models Using the Relevant Cost Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 539-560, Sept.-Oct.
    23. Campbell, Rachel & Koedijk, Kees & Kofman, Paul, 2002. "Increased Correlation in Bear markets: A Downside Risk Perspective," CEPR Discussion Papers 3172, C.E.P.R. Discussion Papers.
    24. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
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    More about this item

    Keywords

    stock returns; forecasting; Density forecasting; normality; asymmetry; copulas;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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