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Portfolio Diversification under Local and Moderate Deviations from Power Laws

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  • Walden, Johan
  • Ibragimov, Rustam
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    Abstract

    This paper analyzes portfolio diversification for nonlinear transformations of heavy-tailed risks. It is shown that diversification of a portfolio of convex functions of heavy-tailed risks increases the portfolio’s riskiness if expectations of these risks are infinite. In contrast, for concave functions of heavy-tailed risks with finite expectations, the stylized fact that diversification is preferable continues to hold. The framework of transformations of heavy-tailed risks includes many models with Pareto-type distributions that exhibit local or moderate deviations from power tails in the form of additional slowly varying or exponential factors. The class of distributions under study is therefore extended beyond the stable class.

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    File URL: http://dash.harvard.edu/bitstream/handle/1/2640586/ibragimov_portfolio.pdf
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    Bibliographic Info

    Paper provided by Harvard University Department of Economics in its series Scholarly Articles with number 2640586.

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    Date of creation: 2008
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    Publication status: Published in Insurance: Mathematics and Economics
    Handle: RePEc:hrv:faseco:2640586

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Silverberg, G. & Verspagen, B., 2004. "The size distribution of innovations revisited: an application of extreme value statistics to citation and value measures of patent significance," Working Papers 04.17, Eindhoven Center for Innovation Studies.
    2. Rustam Ibragimov & Johan Walden, 2006. "The Limits of Diversification When Losses May Be Large," Harvard Institute of Economic Research Working Papers 2104, Harvard - Institute of Economic Research.
    3. Y. Malevergne & D. Sornette, 2003. "VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions," Papers physics/0301009, arXiv.org.
    4. Rustam Ibragimov & Johan Walden, 2006. "Portfolio Diversification Under Local, Moderate and Global Deviations From Power Laws," Harvard Institute of Economic Research Working Papers 2116, Harvard - Institute of Economic Research.
    5. Rustam Ibragimov, 2005. "Portfolio Diversification and Value at Risk Under Thick-Tailedness," Harvard Institute of Economic Research Working Papers 2086, Harvard - Institute of Economic Research.
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    Cited by:
    1. Moore, Kyle & Sun, Pengei & de Vries, Casper G. & Zhou, Chen, 2013. "The drivers of downside equity tail risk," MPRA Paper 45591, University Library of Munich, Germany.
    2. Tong, Bin & Wu, Chongfeng & Xu, Weidong, 2012. "Risk concentration of aggregated dependent risks: The second-order properties," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 139-149.
    3. Moore, Kyle & Sun, Pengfei & de Vries, Casper G. & Zhou, Chen, 2013. "The cross-section of tail risks in stock returns," MPRA Paper 45592, University Library of Munich, Germany.
    4. Embrechts, Paul & Puccetti, Giovanni, 2010. "Bounds for the sum of dependent risks having overlapping marginals," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 177-190, January.
    5. Rustam Ibragimov & Johan Walden, 2011. "Value at risk and efficiency under dependence and heavy-tailedness: models with common shocks," Annals of Finance, Springer, vol. 7(3), pages 285-318, August.
    6. Zhou, Chen, 2010. "Dependence structure of risk factors and diversification effects," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 531-540, June.
    7. Chen Zou, 2009. "Dependence structure of risk factors and diversification effects," DNB Working Papers 219, Netherlands Central Bank, Research Department.
    8. Ibragimov, Rustam, 2014. "On the robustness of location estimators in models of firm growth under heavy-tailedness," Journal of Econometrics, Elsevier, vol. 181(1), pages 25-33.

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