Researcher from Central Michigan University Reports on Findings in Risk Management (Transmuted Distortion Functions for Measuring Risks): Insurance - Risk Management - Insurance News | InsuranceNewsNet

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October 16, 2024 Newswires
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Researcher from Central Michigan University Reports on Findings in Risk Management (Transmuted Distortion Functions for Measuring Risks): Insurance – Risk Management

Insurance Daily News

2024 OCT 16 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A new study on risk management is now available. According to news originating from Mount Pleasant, Michigan, by NewsRx correspondents, research stated, “This paper introduces a new family of distortion functions for measuring risks, developed using transmutation techniques.”

The news journalists obtained a quote from the research from Central Michigan University: “We identify the parameter spaces where the proposed distortions exhibit concavity. Considering that the choice of distortion parameters can be influenced by political factors or users’ risk aversion levels, we generate plots of the distortion functions to examine how these parameters impact the tasks and users’ attitudes toward risk.”

According to the news reporters, the research concluded: “The coherent properties of the resulting risk measures are explored, outlining the conditions under which the transmuted Kumaraswamy and transmuted truncated normal distortions ensure coherence. Numerical analyses demonstrate the effects of parameter variations on the derived risk measures, highlighting the effectiveness of the proposed distortion functions in accurately assessing risk.”

For more information on this research see: Transmuted Distortion Functions for Measuring Risks. Risks, 2024,12(10). (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks12100153.

Our news editors report that additional information may be obtained by contacting Muna Alkasasbeh, Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, United States. Additional authors for this research include Carl Lee, Felix Famoye.

(Our reports deliver fact-based news of research and discoveries from around the world.)

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