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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
Tue Mar 12 2019
Journal Name
Lubricants
Absorption Wavebands for Discriminating Oxidation Time of Engine Oil as Detected by FT-IR Spectroscopy
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Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.

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Catalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne

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Publication Date
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In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con

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Publication Date
Tue Apr 21 2026
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Bioactivity of Gutta flow II versus Modified Gutta Percha based Silicon Endodontic Sealers by Nanobioactive Fillers
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Sat Sep 01 2018
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