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Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange: Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange
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Abstract

The prevention of bankruptcy not only prolongs the economic life of the company and increases its financial performance, but also helps to improve the general economic well-being of the country. Therefore, forecasting the financial shortfall can affect various factors and affect different aspects of the company, including dividends. In this regard, this study examines the prediction of the financial deficit of companies that use the logistic regression method and its impact on the earnings per share of companies listed on the Iraqi Stock Exchange. The time period of the research is from 2015 to 2020, where 33 companies that were accepted in the Iraqi Stock Exchange were selected as a sample, and the research hypotheses were tested using normal least squares regression and logistic regression. The results of testing the first hypothesis of the research indicated that the results of the unidirectional logistic regression from Baytree indicated the confirmation of this hypothesis and it can be said with confidence that by combining accounting and market information, a suitable model can be used to predict the financial distress of accepted companies offered on the Iraqi Stock Exchange. The results of the second hypothesis of the research also showed that earnings per share is a predictor of financial deficit. Firms that predict fiscal deficit try to show lower earnings per share and try to be honest and by accurate prediction of earnings per share according to signal theory, they gain the trust of shareholders and creditors and assure that the company is trying to find a suitable solution for the current issue and other issues that may take place in the future.

Keywords: Predicting financial distress, logistic regression, earnings per share

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Publication Date
Wed Mar 15 2017
Journal Name
International Journal Of Poultry Science
Effect of Threonine Supplementation on Broiler Chicken Productivity Traits
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Publication Date
Sun Nov 01 2020
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Journal Of Engineering
Hydrated Lime Effects on Geotechnical Properties of Clayey Soil
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Publication Date
Sun May 01 2016
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Journal Of Engineering
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
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Publication Date
Tue Oct 31 2023
Journal Name
College Of Islamic Sciences
Legal adjustment of zakat on property prepared for sale
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Now that follows: Islamic law aims to make man happy in this world and the afterlife, starting with faith in God Almighty until the end of the legal obligations. This is

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Publication Date
Wed May 10 2023
Journal Name
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Publication Date
Thu Dec 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
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Publication Date
Fri Apr 01 2022
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On Cohomology Groups of Four-Dimensional Nilpotent Associative Algebras
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The study of cohomology groups is one of the most intensive and exciting researches that arises from algebraic topology. Particularly, the dimension of cohomology groups is a highly useful invariant which plays a rigorous role in the geometric classification of associative algebras. This work focuses on the applications of low dimensional cohomology groups. In this regards, the cohomology groups of degree zero and degree one of nilpotent associative algebras in dimension four are described in matrix form.

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Some Results of (α, β) Derivations on Prime Semirings
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Publication Date
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