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Mahdi Rasekhi

Mahdi Rasekhi

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Mathematical Sciences and Statistics
Address:
Phone: 0813-33339843 داخلی 391

Research

Title
The Odd Log-Logistic Weibull-G Family of Distributions with Regression and Financial Risk Models
Type
JournalPaper
Keywords
Odd log-logistic-G family; Weibull-G family; Regression model; Value at risk; Simulation; Maximum likelihood; Financial risk modeling
Year
2022
Journal Journal of the Operations Research Society of China
DOI
Researchers Mahdi Rasekhi

Abstract

A new generalization of the Weibull-G family is proposed with two extra shape parameters. The mathematical properties are derived in great detail. Using the Weibull and normal distributions as baseline distributions, two models are introduced. The first model is a location-scale regression model based on a new extension of the Weibull distribution. The second model is a new two-step financial risk model to forecast the daily value at risk. The flexibility and applicability of the proposed models are investigated by means of five real data sets on the lifetime and financial returns. Empirical findings of the study show that proposed models work well and produce better results than other well-known models for financial risk modeling and censored lifetime data analysis.