بخشی از مقاله (انگلیسی)
The prediction of corporate bankruptcy is a phenomenon of interest to investors, creditors, borrowing firms, and governments alike. Many quantitative methods and distinct variable selection techniques have been employed to develop empirical models for predicting corporate bankruptcy. For the present study the lasso and ridge approaches were undertaken, since they deal well with multicolinearity and display the ideal properties to minimize the numerical instability that may occur due to overfitting. The models were employed to a dataset of 2032 non-bankrupt firms and 401 bankrupt firms belonging to the hospitality industry, over the period 2010-2012. The results showed that the lasso and ridge models tend to favor the category of the dependent variable that appears with heavier weight in the training set, when compared to the stepwise methods implemented in SPSS.
There are several undesirable consequences of business failures. Its economic and social cost can be significant. So, it is quite natural that this issue has occupied a significant part of researcher’s agenda. In spite of recent growing interest on non-financial attributes in explaining business failures, traditionally investigation on this issue has been focused on financial attributes. In most of the works statistical or artificial intelligence techniques were applied to the accountancy data of the companies, aiming at obtaining prediction models that would indicate whether the company would or would not reach a bankruptcy situation in the future (Beaver, 1966; Altman, 1968; Martin, 1977; Tam and Kiang, 1992). In a study on corporate bankruptcy prediction, one of the aspects we immediately need to clarify is the concept of bankruptcy we shall use. In specialized literature the term has been used in different ways by different authors: legal bankruptcy, insolvency, inability to do payments or continued losses. As we lack a general theory on corporate bankruptcy, there is also no unique definition for this concept. This is an important limitation, since the sample’s selection, both in terms of firms that have and have not “bankrupt”, depends on the definition of corporate bankruptcy used.