What makes dependence modeling challenging? Pitfalls and ways to circumvent them

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2013-01-01 DOI:10.1524/strm.2013.2001

Jan-Frederik Mai, M. Scherer

引用次数: 0

Abstract

Abstract We present a list of challenges one faces when given the task of modeling dependence between stochastic objects, with a special focus on financial applications. Our aim is to draw the readers' attention to common (and not so common) pitfalls and fallacies, and we particularly address readers who are new to dependence modeling. The presented list of challenges is clearly not complete, but it gives a flavor of how difficult and subtle the task of dependence modeling can be. Moreover, the readers shall get some intuition about what challenges are structural and cannot be overcome, and what challenges allow for a better solution than common practice might suggest.

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是什么使依赖性建模具有挑战性?陷阱和规避它们的方法

摘要我们提出了当给定随机对象之间的依赖建模任务时所面临的挑战列表，特别关注金融应用。我们的目标是吸引读者注意常见的(和不那么常见的)陷阱和谬误，我们特别针对那些不熟悉依赖建模的读者。所提出的挑战列表显然不完整，但它让我们了解到依赖性建模的任务是多么困难和微妙。此外，读者应该对哪些挑战是结构性的、无法克服的，以及哪些挑战可以提供比一般实践可能建议的更好的解决方案有一些直觉。

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.