Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal densities

被引:0
作者
Ruodu Wang
Liang Peng
Jingping Yang
机构
[1] Georgia Institute of Technology,School of Mathematics
[2] University of Waterloo,Department of Statistics and Actuarial Science
[3] Peking University,LMEQF and LMAM, Department of Financial Mathematics, Center for Statistical Science
来源
Finance and Stochastics | 2013年 / 17卷
关键词
Complete mixability; Monotone density; Sum of dependent risks; Value-at-Risk; 60E05; 60E15; G10;
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学科分类号
摘要
In quantitative risk management, it is important and challenging to find sharp bounds for the distribution of the sum of dependent risks with given marginal distributions, but an unspecified dependence structure. These bounds are directly related to the problem of obtaining the worst Value-at-Risk of the total risk. Using the idea of complete mixability, we provide a new lower bound for any given marginal distributions and give a necessary and sufficient condition for the sharpness of this new bound. For the sum of dependent risks with an identical distribution, which has either a monotone density or a tail-monotone density, the explicit values of the worst Value-at-Risk and bounds on the distribution of the total risk are obtained. Some examples are given to illustrate the new results.
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页码:395 / 417
页数:22
相关论文
共 25 条
  • [1] Denuit M.(1999)Stochastic bounds on sums of dependent risks Insur. Math. Econ. 25 85-104
  • [2] Genest C.(2003)Using copulae to bound the value-at-risk for functions of dependent risks Finance Stoch. 7 145-167
  • [3] Marceau É.(2006)Extreme VaR scenarios in higher dimensions Extremes 9 177-192
  • [4] Embrechts P.(2006)Bounds for functions of dependent risks Finance Stoch. 10 341-352
  • [5] Höing A.(2006)Bounds for functions of multivariate risks J. Multivar. Anal. 97 526-547
  • [6] Juri A.(1981)On a class of extremal problems in statistics Math. Operforsch. Stat., Ser. Optim. 12 123-135
  • [7] Embrechts P.(2009)Worst VaR scenarios with given marginals and measures of association Insur. Math. Econ. 44 146-158
  • [8] Höing A.(2006)Choosing joint distributions so that the variance of the sum is small J. Multivar. Anal. 97 1757-1765
  • [9] Embrechts P.(2012)Bounds for joint portfolios of dependent risks J. Comput. Appl. Math. 236 1833-1840
  • [10] Puccetti G.(1982)Random variables with maximum sums Adv. Appl. Probab. 14 623-632