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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
Mon Nov 27 2023
Journal Name
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Publication Date
Sun Apr 02 2017
Journal Name
International Workshop In Physics Applications
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Mon Mar 18 2019
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Publication Date
Thu Jan 17 2019
Journal Name
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: The terrestrial snail Eobania vermiculata (O. F. Müller, 1774) were collected from three station in Baghdad Al- Karkh, Iraq between the period from June 2016 to July 2017. Then we studied the life cycle from the egg to maturity. We studied and photographed the external morphology of it’s shell to identified the species. This species was recorded for the first time in Baghdad.

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Publication Date
Thu Apr 01 2021
Journal Name
Journal Of Alloys And Compounds
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