A User-Friendly Algorithm for Detecting the Influence of Background Risks on a Model

Nadezhda Gribkova and Ričardas Zitikis
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Nadezhda Gribkova: Faculty of Mathematics and Mechanics, St. Petersburg State University, St. Petersburg 199034, Russia
Ričardas Zitikis: School of Mathematical and Statistical Sciences, Western University, London, ON N6A 5B7, Canada

Risks, 2018, vol. 6, issue 3, 1-11

Abstract: Background, or systematic, risks are integral parts of many systems and models in insurance and finance. These risks can, for example, be economic in nature, or they can carry more technical connotations, such as errors or intrusions, which could be intentional or unintentional. A most natural question arises from the practical point of view: is the given system really affected by these risks? In this paper we offer an algorithm for answering this question, given input-output data and appropriately constructed statistics, which rely on the order statistics of inputs and the concomitants of outputs. Even though the idea is rooted in complex statistical and probabilistic considerations, the algorithm is easy to implement and use in practice, as illustrated using simulated data.

Keywords: background risk; systematic risk; transfer function; information processing; order statistic; concomitant (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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