渐近稳定动态风险评估

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2013-03-28 DOI:10.1515/strm-2012-1146

Karl-Theodor Eisele, M. Kupper

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引用次数: 0

摘要

摘要本文研究了渐近稳定风险评估(或等价的风险度量)的性质，即不能通过在遥远的未来增加巨大的现金流而使不可接受的头寸变为可接受的头寸。在附加的连续性假设下，这些风险评估正是那些在有限时间间隔上支持的测试概率方面具有鲁棒表示的风险评估。对于时间一致的风险评估，我们给出了它们的发电机保证渐近稳定的条件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Asymptotically stable dynamic risk assessments

Abstract In this paper we study asymptotically stable risk assessments (or equivalently risk measures) which have the property that an unacceptable position cannot become acceptable by adding a huge cash-flow far in the future. Under an additional continuity assumption, these risk assessments are exactly those which have a robust representation in terms of test probabilities that are supported on a finite time interval. For time-consistent risk assessments we give conditions on their generators which guarantee asymptotic stability.

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来源期刊

Statistics & Risk Modeling STATISTICS & PROBABILITY-

CiteScore

1.80

自引率

6.70%

发文量

期刊介绍： Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.