Please use this identifier to cite or link to this item: http://archive.nnl.gov.np:8080/handle/123456789/160
Title: Financial ratios and corporate failure
Authors: Fago, Ghanendra
Keywords: finance and accounting
Issue Date: 25-Mar-2019
Abstract: The prediction of corporate failure has become a major area of finance and accounting since 1960s. Prior to 1960s, Ramser and Foster (1931); Fitzpatrick (1932); Smith and Winakar (1935); and Marwin (1942) used financial ratios to compare failed and non-failed firms. Beaver (1966) used univariate analysis of financial ratios to determine financial ratios as predictors of corporate failure. Altman (1968) used multivariate discriminant analysis for prediction of corporate failure. Ohlson (1980) used logistic analysis for prediction of corporate failure. The better known discriminant studies are Deakin (1972); Altman at el., (1977); Blum (1974); Gupta (1983); and Yadav (1986). Similarly, Edmister (1972); Meyer and Pifer (1980) used linear regression and Zavgren (1985); Nam and Jinn (2000); Charitou et al., (2004); and Ugurlu and Aksoy (2006) using logistic regression analysis for prediction of corporate failure. These studies developed corporate failure prediction models to provide early warning signal of corporate failure to the stakeholders, so that they can adopt corporate strategies to reduce risk of bankruptcy (Danilov, 2014). However, there is no unanimous in a financial ratio or a set of financial ratios as predictors of corporate failure abroad. Little attempts have been made to assess usefulness of financial ratios as predictors of corporate failure in the context developing country Nepal. The main objective of this study is to examine financial ratios and their usefulness in prediction of corporate failure of Nepal. The specific objectives are: (i) to compare financial ratios of failed and non-failed companies; (ii) to determine ratio or set of ratios that can predict corporate failure; (iii) to find out how many years in advance, corporate failure can be predicted; (iv) to develop models of financial ratios for prediction of corporate failure; and (v) to assess the consensus of financial executives and practitioners on financial ratios as predictors of corporate failure. This study has used descriptive, correlation, causal comparative research designs to deal with various issues raised in this study. For this purpose, a list of listed companies and public enterprises including liquidated, closed down, under liquidation, delisted from NEPSE) have been collected from the Office of Auditors 146 General of Nepal (OAG/N), Corporation Coordination Division of Ministry of Finance (MOF), Security Board of Nepal (SEBON), Nepal Stock Exchange Ltd (NEPSE) and the Office of the Company Registrar (OCR). In this study, a company is defined as a failed company, if its total liabilities are greater than total assets or liquidated or under liquidation process or closed down operations. A company is regarded as a non-failed company, if it is not failed company. On the basis of these criteria, twenty failed companies have been selected. These twenty one failed companies have been paired with twenty non-failed companies. Both failed and non-failed companies have been selected from the list of thirty three privately owned listed companies and liquidated or delisted companies; thirty seven public enterprises, and thirty privatized and dissolved public enterprises. The main source of secondary data of this study is the financial statements from fiscal years 1988 through 2009 that have been used to assess financial ratios and their usefulness for prediction of corporate failure. The major source of primary data is structured questionnaire. A structured questionnaire was designed to find consensus among financial executives and practitioners on financial ratios and corporate failure in the context of Nepal. In this study, opinions of one hundred sixty eight (168) financial executive and practitioners have been used to assess the consensus on the issue.
URI: http://103.69.125.248:8080/xmlui/handle/123456789/160
Appears in Collections:300 Social sciences

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