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Optimal Reinsurance Under Distortion Risk Measures and Expected Value Premium Principle for Reinsurer*
  • ISSN号:1009-6124
  • 期刊名称:《系统科学与复杂性学报:英文版》
  • 时间:0
  • 分类:O225[理学—运筹学与控制论;理学—数学] F842.3[经济管理—保险]
  • 作者机构:[1]Department of Finance, Beijing Technology and Business University , Beijing 100037, China., [2]Department of Financial Mathematics, Peking University, Beijing 100871, China., [3]Department of Financial Mathematics, School of Mathematical Sciences and Center of Statistical Science, Peking University, Beijing 100871, China.
  • 相关基金:Zheng's research was supported by the Program of National Natural Science Foundation of Youth of China under Grant No. 11201012 and PHR201007125; Yang's research was supported by the Key Program of National Natural Science Foundation of China under Grant No. 11131002 and the National Natural Science Foundation of China under Grant No. 11271033.
中文摘要:

这份报纸由在一个将军下面最小化保险公司风险讨论最佳的再保险策略风险措施:失真风险措施。作者假设再保险奖赏被期望的值奖赏原则决定,保险公司的保留的损失是起始的损失的一个增加的函数。保险公司的一个明确的答案最佳的再保险问题被获得。为一些特殊失真风险措施的最佳的策略例如 value-at-risk (VaR ) 和尾巴 value-at-risk (TVaR ) ,也被调查。

英文摘要:

This paper discusses optimal reinsurance strategy by minimizing insurer's risk under one general risk measure: Distortion risk measure. The authors assume that the reinsurance premium is determined by the expected value premium principle and the retained loss of the insurer is an increasing function of the initial loss. An explicit solution of the insurer's optimal reinsurance problem is obtained. The optimal strategies for some special distortion risk measures, such as value-at-risk (VaR) and tail value-at-risk (TVaR) are also investigated.

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期刊信息
  • 《系统科学与复杂性学报:英文版》
  • 主管单位:中国科学院
  • 主办单位:中国科学院系统科学研究所
  • 主编:
  • 地址:北京东黄城根北街16号
  • 邮编:100080
  • 邮箱:
  • 电话:010-62541831 62541834
  • 国际标准刊号:ISSN:1009-6124
  • 国内统一刊号:ISSN:11-4543/O1
  • 邮发代号:82-545
  • 获奖情况:
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国数学评论(网络版),德国数学文摘,荷兰文摘与引文数据库,美国工程索引,美国科学引文索引(扩展库),英国科学文摘数据库
  • 被引量:125