Improved algorithms for computing worst Value-at-Risk

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2015-05-09 DOI:10.1515/strm-2015-0028

M. Hofert, Amir Memartoluie, D. Saunders, T. Wirjanto

引用次数: 17

Abstract

Abstract Numerical challenges inherent in algorithms for computing worst Value-at-Risk in homogeneous portfolios are identified and solutions as well as words of warning concerning their implementation are provided. Furthermore, both conceptual and computational improvements to the Rearrangement Algorithm for approximating worst Value-at-Risk for portfolios with arbitrary marginal loss distributions are given. In particular, a novel Adaptive Rearrangement Algorithm is introduced and investigated. These algorithms are implemented using the R package qrmtools and may be of interest in any context in which it is required to find columnwise permutations of a matrix such that the minimal (maximal) row sum is maximized (minimized).

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计算最坏风险值的改进算法

摘要:本文识别了同质投资组合中计算最坏风险值的算法中固有的数值挑战，并给出了解决方案以及有关其实现的警告。此外，对具有任意边际损失分布的投资组合逼近最坏风险值的重排算法进行了概念上和计算上的改进。特别地，介绍并研究了一种新的自适应重排算法。这些算法是使用R包qrmtools实现的，在需要查找矩阵的列排列以使最小(最大)行和最大化(最小化)的任何上下文中，这些算法都可能很有用。

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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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.

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