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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 Mar 11 2019
Journal Name
Baghdad Science Journal
The Qualitative and Quantitative Composition of Epiphytic Algae on Ceratophyllum demersum L. in Tigris River within Wassit Province, Iraq
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 The present research was performed to study the qualitative and quantitative composition of epiphytic algae on the aquatic host plant Ceratophyllum demersum L. Four sites in Tigris River, at Wassit Governorate were covered, during the seasons of Autumn 2017, winter 2018, Spring 2018, and Summer 2018. The study also included measuring the physiochemical parameters (temperature of air and water, pH , water level, EC, salinity, TDS, TSS, dissolved oxygen,  BOD5, alkalinity, total hardness, calcium, magnesium, total nitrogen, total phosphourus). The total number of species of epiphytic algae was145 species, 98 species belonging to Bacillariophyceae, followed by 27species of class Cyanophyceae, 19 species of class Chloroph

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A Comparative Study to Reveal Earnings Management in Emerging Markets: Evidence from Tunisia and Iraq
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Purpose: The purpose of the study is to compare and evaluate Earnings Management in Tunisia and Iraq.   Theoretical framework: Earnings Management is an important topic that has been studied by a significant number of researchers, as well as those who are interested in the accounting profession. Earnings Management has gotten a lot of attention from academics, professionals, and other interested parties in recent years (e.g. Kliestik et al., 2020; Rahman et al., 2021; Gamra &Ellouze, 2021)   Design/methodology/approach: The sample includes ten banks listed on the Bourse of Tunisia and Iraq Stock Exchanges for the year 2017. We have used a model of Kothari et al., (2005) as a tool to measure Earnings Management in both mark

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Sun Jun 01 2014
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Estimate the Best production function of the General Company for Iraqi Cement for the period (1996-2010)
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