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Decomposing aggregate risk into marginal risks under partial information: A top-down method

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  • Shao, Hui

Abstract

This paper proposes a method to decompose a square-integrable random variable into any number of marginal random variables under partial information restrictions. An executable algorithm and a concrete example of the capital allocation problem are also provided.

Suggested Citation

  • Shao, Hui, 2017. "Decomposing aggregate risk into marginal risks under partial information: A top-down method," Statistics & Probability Letters, Elsevier, vol. 124(C), pages 97-100.
  • Handle: RePEc:eee:stapro:v:124:y:2017:i:c:p:97-100
    DOI: 10.1016/j.spl.2017.01.015
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    References listed on IDEAS

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    1. Ruodu Wang & Liang Peng & Jingping Yang, 2013. "Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal densities," Finance and Stochastics, Springer, vol. 17(2), pages 395-417, April.
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    6. Wang, Bin & Wang, Ruodu, 2011. "The complete mixability and convex minimization problems with monotone marginal densities," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1344-1360, November.
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