The Early Warning of Financial Failure for Iraqi Banks Based on Robust Adaptive Lasso Logistic Regression




Lasso, Robust Regression, Financial Failure, Logistic Regression


 It is well known that there are many mathematical financial failure models that have been proposed
in the financial literature for specific stock markets. Some researchers are not aware these mathematical models
were constructed to be fitted for that market data, not for other markets. Iraq stock market exchange is one of these
markets in which the researchers used imported models such as Kida, Sherrod, Altman, and others to predict
financial failure. Therefore, the development of a financial failure warning model for banks has become very
crucial for the Iraqi bank sector in the stock market exchange. Unfortunately, there is no clear information about
the financial failure of Iraqi banks as a response variable, and the financial indicators contain outliers. The
objective of this paper is to propose an algorithm to know the performance of efficient and inefficient banks based
on their indicators during specific time periods. The output of this algorithm will be considered as response
variables. Then, a weighted adaptive lasso logistic regression algorithm that has a high breakdown point is used to
tackle outliers’ problem. Thirteen banks have been chosen as the most traded during the period (2010-2017), and
for each bank (27) financial indicators were collected. Our proposed model is compared with adaptive lasso
logistic regression by using Deviance, Misclassification, Area Under Curve, Mean Square Errors, and Mean
Absolute Errors. Consequently, the results showed that the weighted Adaptive Lasso Logistic Regression model is
more robust and relevant than others to be a financial model to warn of the failure of the banks in Iraq's stock


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Author Biographies

Aqeel Jaafar Abbas Alshareefi, Ministry of Planning

Name: Aqeel Jaafar Abbas Alshareefi
Birthday: 27-4-1988 / Iraq-Kirkuk
Live in: Babel-Alhashimiya City
Marital Status: Married, and I have three children
Current Job: Government Employee in Iraqi Ministry of Planning
Career Title: Senior Statistician
Academic Achievement: Master's degree student in Statistics In University of Al-Qadisiyah
for contact:
WhatsApp, Telegram & Viber: +964-780-638-1359

Hassan Uraibi, Faculty of Administration and Economics, Al-Qadisiyah University, Diwaniyah, IRAQ

Dept. of Statistics




How to Cite

A. J. A. Alshareefi and H. S. U. alshamari, “The Early Warning of Financial Failure for Iraqi Banks Based on Robust Adaptive Lasso Logistic Regression”, Iraqi Journal For Computer Science and Mathematics, vol. 5, no. 1, pp. 112–124, Jan. 2024.
DOI: 10.52866/ijcsm.2024.05.01.008
Published: 2024-01-28