Nilmawati, Nilmawati and Satoto, Shinta Heru (2015) Developing Financial Distress Prediction Model For Companies Going Public: Accounting, Macroeconomic, Market, And Industry Approaches. EUROPEAN JOURNAL OF ECONOMICS AND MANAGEMENT, 2 (1). pp. 21-37. ISSN 2056-7375 (Online) 2015
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Abstract
This research is to construct a model for an accurate prediction of financial
distress by finding and including other variables outside the
data/information derived the accounting reports. The population of this
research is composed of all the non-financial companies listed on the
Indonesia Stock Exchange. As for the samples, they are the companies
experiencing financial distress which is indicated by their negative profits
in two consecutive years; and the control group is composed of the
companies in the same industry group with the total asset of almost the
same as that of the companies experiencing financial distress; only that
these companies do not experience financial distress.The model to
construct the financial distress prediction is the Binary Logistic
Regression. The results show that the variables of the group of financial
ratios, namely liquidity, profitability, leverage, activity, and cash flow, can
be used as the variables for the financial distress prediction. However, the
variables of the group of market and macroeconomic ratios cannot be
employed to predict. Meanwhile, the variable of the group of industry
treated as a moderating dummy variable does not indicate to have any
moderating influence on the variables of financial ratio that previously
proved to have significant influence on the possibility of the financial
distress of a company.
| Item Type: | Article |
|---|---|
| Subjek: | H Social Sciences > HG Finance |
| Divisions: | x. Faculty of Law, Arts and Social Sciences > School of Social Sciences |
| Depositing User: | SE, MSi Nilmawati Nilmawati |
| Date Deposited: | 24 Nov 2017 02:44 |
| Last Modified: | 24 Nov 2017 02:44 |
| URI: | http://eprints.upnyk.ac.id/id/eprint/13834 |
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