Bankruptcy prediction of listed companies on the Tehran Stock Exchange. Issue 5 (12th September 2016)

• Record Type: Journal Article
• Authors: Salehi, Mahdi; Davoudi Pour, Mojdeh
• Is Part Of: International journal of law and management. Volume 58:Issue 5(2016)
• Page Start: 545
• Page End: 561
• Publication Date: 2016-09-12
• Subjects: Bankruptcy -- Stock exchange -- Artificial neural network -- Forecasting; Labor laws and legislation -- Great Britain -- Periodicals; Trade regulation -- Great Britain -- Periodicals; Labor laws and legislation -- Great Britain -- Cases; Trade regulation -- Great Britain -- Cases; 346.0664
• DOI: 10.1108/IJLMA-05-2015-0023
• Languages: English
• ISSNs: 1754-243X

Abstract

Abstract : Purpose: Bankruptcy is the last phase of economic life of companies and has some impacts on all of the entity's stakeholders. Thus, the prediction of bankruptcy is very important. The inherent aim of preparing and developing financial accounting information is to provide a basis for economic decision-making, and any decision requires information acquisition, processing and data analysis as well as logical and correct interpretation of information. Developing models for predicting financial crisis and comparing the capabilities of existing models can help to alert management about ongoing activities and investors about economic decision for purchase shares or granting loan facilities to companies. So, the purpose of this study is the predict bankruptcy of listed companies on the Tehran Stock Exchange. Design/methodology/approach: From the statistical methods' perspective, the present research is classified as modeling and with respect to research methodology, it is a correlative-descriptive study in which the relationship between variables is analyzed based on the research objective. Predictive variables are the best ratios of cost of goods sold, non-operating revenues, net sales, predicted earnings per share (EPS) and real EPS. Findings: Prediction of corporate bankruptcy crisis is one of the vital research areas. Predictive models are means for estimating the company's future situation. Investors and creditors are highly willing to predict the bankruptcy crisis because the high costs associated with bankruptcy crisis will spoil the economy as a whole. On the other hand, this raises concerns among owners, and they are always seeking to find ways to preserve their capital through prediction of stocks continuing operations in the future. Having knowledge about bankruptcy or non-bankruptcy of automotive parts companies makes it possible to recognize weaknesses and strengths in the companies' current performance and to make investment decisions. Practical implications: Development of financial markets and, subsequently, creation of fierce competition has resulted in bankruptcy of many companies. Investors are always looking for predicting possible bankruptcy of a firm to prevent their investments risks because bankruptcy costs are high for investors, creditors, lenders and government agencies. Hence, they are seeking ways to estimate corporate bankruptcy. For this reason, over the past four decades, bankruptcy prediction has been enumerated as a key issue in companies and consequently because of its importance, many studies have been conducted to achieve the best model to predict bankruptcy. Originality/value: Bankruptcy forecast is an economically important issue in every organization and company. Financial and accounting researchers are trying to offer financial models using various combinations of financial ratios with better measuring ability for performance and dividends payments as well as company continued activities. Bankruptcy prediction models are among financial analysis techniques in which the purpose of financial analysis and bankruptcy forecasting is recognition of efficiency and management executive performances. Moreover, the analysis of stock value by shareholder is another application of such research results. Basically, shareholders are interested in knowing the future status of the companies that are going to buy. In this way, shareholders use this method of analysis to estimate future activity or inactivity of firms.