May 15, 2024
Morad Alizadeh

Morad Alizadeh

Academic Rank: Assistant professor
Address:
Degree: Ph.D in Statistics
Phone: 0
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title The OddLog-Logistic Weibull-G Family of Distributions with Regression and Financial Risk Models
Type Article
Keywords
Odd log-logistic-G family · Weibull-G family · Regression model · Value at risk · Simulation · Maximum likelihood · Financial risk modeling
Journal Journal of the Operations Research Society of China
DOI 10.1007/s40305-021-00349-6
Researchers Mahdi Rasekhi (First researcher) , Emrah Altun (Second researcher) , Morad Alizadeh (Third researcher) , Haitham Yousof (Fourth researcher)

Abstract

A new generalization of the Weibull-G family is proposed with two extra shape param- eters. 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 inves- tigated 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.