AGGREGATION OF CORRELATED RISK PORTFOLIOS: MODELS AND ALGORITHMS
AGGREGATION OF CORRELATED RISK PORTFOLIOS: MODELS AND ALGORITHMS
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发表时间：
1999
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通讯作者：
Shaun S. Wang;K. S. Tan
中科院分区：
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作者：
Shaun S. Wang;K. S. Tan
本文提出了一套工具，建模和组合相关的风险。各种相关性结构的生成使用copula，共同的混合，组件和失真模型。这些相关性结构根据（i）联合累积分布函数或（ii）联合特征函数来指定，并通过使用蒙特卡罗模拟或快速傅里叶变换来提供有效的聚合方法。致谢作者感谢中国科学院风险理论委员会发起和支持本研究项目。特别感谢Phil Heckman和Glenn Meyers在监督该项目进展的同时提供了许多令人兴奋的评论。Phil Heckman、Stephen Mildenhall、Don Mango、Louise弗朗西斯和CAS编辑委员会在对本文的全面审查中提供了许多有价值的意见，这些意见使早期的报告草案得到了显著的改进。作者还感谢Ole Hesselager、Julia Wirch和Ken Seng Tan的评论。
This paper presents a set of tools for modeling and combining correlated risks. Various correlation structures are generated using copula, common mixture, component, and distortion models. These correlation structures are specified in terms of (i) the joint cumulative distribution function or (ii) the joint characteristic function and lend themselves to efficient methods of aggregation by using Monte Carlo simulation or fast Fourier transform. ACKNOWLEDGEMENT The author wishes to thank the CAS Committee on Theory of Risk for initiating and supporting this research project. A special thanks goes to Phil Heckman and Glenn Meyers for providing numerous stimulating comments while overseeing the progress of this project. Phil Heckman, Stephen Mildenhall, Don Mango, Louise Francis, and the CAS Editorial Committee, in their thorough review of this paper, have provided many valuable comments which led to significant improvement of an earlier draft report. The author also thanks Ole Hesselager, Julia Wirch, and Ken Seng Tan for comments.