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arXiv 2312.01034q-fin.RMq-fin.MF
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单调均值-偏差风险度量

Monotonic mean-deviation risk measures

Xia Han, Ruodu Wang, Qinyu Wu

AI总结:

本文通过风险加权函数刻画单调均值-偏差风险度量,建立公理化基础,给出凸与相干情形的刻画及对偶表示,并分析模型不确定性下的最坏情形值和估计量的渐近性质,最终应用于投资组合选择。

摘要:

均值-偏差模型以及现有的相干风险度量理论在文献中已得到充分研究。本文通过将风险加权函数应用于偏差部分,从一般均值-偏差模型中刻画了单调均值-偏差(风险)度量。其形式是偏差相关泛函与期望的组合,此类度量属于一致风险度量类。单调均值-偏差度量通过偏好关系获得了公理化基础。通过进一步假设风险加权函数的凸性和线性,得到了凸风险度量和相干风险度量的刻画,从而产生了许多新的凸和非凸一致风险度量的显式例子。此外,我们专门研究单调均值-偏差度量的凸情形,并得到其对偶表示。在两种常用的模型不确定性设定下,分析了单调均值-偏差度量的最坏情形值。进一步,我们建立了单调均值-偏差度量的自然估计量的渐近一致性和正态性。最后,利用金融数据将单调均值-偏差度量应用于投资组合选择问题。

英文摘要:

Mean-deviation models, along with the existing theory of coherent risk measures, are well studied in the literature. In this paper, we characterize monotonic mean-deviation (risk) measures from a general mean-deviation model by applying a risk-weighting function to the deviation part. The form is a combination of the deviation-related functional and the expectation, and such measures belong to the class of consistent risk measures. The monotonic mean-deviation measures admit an axiomatic foundation via preference relations. By further assuming the convexity and linearity of the risk-weighting function, the characterizations for convex and coherent risk measures are obtained, giving rise to many new explicit examples of convex and nonconvex consistent risk measures. Further, we specialize in the convex case of the monotonic mean-deviation measure and obtain its dual representation. The worst-case values of the monotonic mean-deviation measures are analyzed under two popular settings of model uncertainty. Further, we establish asymptotic consistency and normality of the natural estimators of the monotonic mean-deviation measures.Finally, the monotonic mean-deviation measures are applied to a problem of portfolio selection using financial data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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