A new losses (revenues) probability model with entropy analysis, applications and case studies for value-at-risk modeling and mean of order-P analysis-Reference-Cited by-同舟云学术

A new losses (revenues) probability model with entropy analysis, applications and case studies for value-at-risk modeling and mean of order-P analysis

Published:2024 Issue:3 Volume:9 Page:7169-7211
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Elbatal Ibrahim¹,Diab L. S.¹,Ghorbal Anis Ben¹,Yousof Haitham M.²,Elgarhy Mohammed³⁴,Ali Emadeldin I. A.⁵⁶

Affiliation:

1. Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia

2. Department of Statistics, Mathematics and Insurance, Benha University, Benha, Egypt

3. Department of Basic Sciences, Higher Institute of Administrative Sciences, Belbeis, AlSharkia, Egypt

4. Mathematics and Computer Science Department, Faculty of Science, Beni-Suef University, Beni-Suef 62521, Egypt

5. Department of Economics, College of Economics and Administrative Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia

6. Department of Mathematics, Statistics, and Insurance, Faculty of Business, Ain Shams University, Egypt

Abstract

<abstract><p>This study introduces the Inverse Burr-X Burr-XII (IBXBXII) distribution as a novel approach for handling asymmetric-bimodal claims and revenues. It explores the distribution's statistical properties and evaluates its performance in three contexts. The analysis includes assessing entropy, highlighting the distribution's significance in various fields, and comparing it to rival distributions using practical examples. The IBXBXII model is then applied to analyze risk indicators in actuarial data, focusing on bimodal insurance claims and income. Simulation analysis shows its preference for right-skewed data, making it suitable for mathematical modeling and actuarial risk assessments. The study emphasizes the IBXBXII model's versatility and effectiveness, suggesting it as a flexible framework for actuarial data analysis, particularly in cases of large samples and right-skewed data.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

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