Reports Summarize Mathematics Research from Benha University (A New Reciprocal Weibull Extension for Modeling Extreme Values with Risk Analysis Under Insurance Data): Mathematics

2023 MAR 02 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on mathematics is the subject of a new report. According to news reporting originating from Benha University by NewsRx correspondents, research stated, “Probability-based distributions might be able to explain risk exposure well. Usually, one number, or at the very least, a limited number of numbers called the key risk indicators (KRIs), are used to describe the level of risk exposure.”

Financial supporters for this research include King Saud University.

Our news reporters obtained a quote from the research from Benha University: “These risk exposure values, which are undeniably the outcome of a specific model, are frequently referred to as essential critical risk indicators. Five key risk indicators, including value-at-risk, tail variance, tail-value-at-risk, and tail mean-variance, were also used for describing the risk exposure under the reinsurance revenues data. These measurements were created for the proposed model; hence, this paper presents a novel distribution for this purpose. Relevant statistical properties are derived, including the generating function, ordinary moments, and incomplete moments. Special attention is devoted to the applicability of the new model under extreme data sets. Three applications to real data show the usefulness and adaptability of the proposed model. The new model proved its superiority against many well-known related models.”

According to the news editors, the research concluded: “Five key risk indicators are employed for analyzing the risk level under the reinsurance revenues dataset. An application is provided along with its relevant numerical analysis and panels. Some useful results are identified and highlighted.”

For more information on this research see: A New Reciprocal Weibull Extension for Modeling Extreme Values with Risk Analysis Under Insurance Data. Mathematics, 2023,11(4). (Mathematics - http://www.mdpi.com/journal/mathematics). The publisher for Mathematics is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/math11040966.

Our news journalists report that more information may be obtained by contacting Haitham M. Yousof, Department of Statistics, Mathematics and Insurance, Benha University, Benha 13518, Egypt. Additional authors for this research include Yusra Tashkandy, Walid Emam, M. Masoom Ali, Mohamed Ibrahim.

ORCID is an identifier for authors and includes bibliographic information. The following is ORCID information for the authors of this research: Haitham M. Yousof (http://orcid.org/0000-0003-4589-4944), Yusra Tashkandy (http://orcid.org/0000-0003-2878-4460), Walid Emam (http://orcid.org/0000-0002-6810-6640), Mohamed Ibrahim (http://orcid.org/0000-0003-4893-9669).

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