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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 Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
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Ibn Al-haitham Journal For Pure And Applied Science
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Wed Dec 04 2013
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Proceedings Of Nuclei Of Seyfert Galaxies And Qsos - Central Engine & Conditions Of Star Formation — Pos(seyfert 2012)
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Publication Date
Wed Jan 01 2020
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Biochemical Cellular Archives
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Unsteady Magnetohydrodynamics oscillating flow of third order fluid with central free stream velocity
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
Gas Sensing of (SnO2)1-x(ZnO)x Composite Associating with Electrical Properties
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Semiconductor-based gas sensors were prepared, that use n-type tin oxide (SnO2) and  tin oxide: zinc oxide composite (SnO2)1-x(ZnO)x at different x ratios using pulse laser deposition at room temperature. The prepared thin films were examined to reach the optimum conditions for gas sensing applications, namely X-ray diffraction, Hall effect measurements, and direct current conductivity. It was found that the optimum crystallinity and maximum electron density, corresponding to the minimum charge carrier mobility, appeared at 10% ZnO ratio. This ratio appeared has the optimum NO2 gas sensitivity for 5% gas concentration at 300 °C working temperat

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Mon Aug 01 2016
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Wed Jan 01 2014
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Research Journal Of Pharmaceutical, Biological And Chemical Sciences
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Publication Date
Tue Jan 08 2013
Journal Name
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Publication Date
Thu Jan 01 2026
Journal Name
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