USING KIDA MODEL IN PREDICTING FINANCIAL FAILURE IN EGYPTIAN FIRMS

Abstract

Understanding the financial failure of firms is a vital accounting research endeavour. Because of the critical importance of financial failure to managers' decision-making, investors, shareholders, and others, many studies examined several developed models for predicting financial failure using Linear multiple discriminant approaches (LMDA), logistic regression, artificial intelligence approaches and data mining techniques (neural network (NN), genetic algorithm (GA), expert systems (ESs), and support vector machines (SVMs). In Egypt, there doesn't seem to be much similar work. This study aims to close this knowledge gap, especially after many financial consequences, including financial failure, have been experienced by a number of Egyptian-listed firms in recent years despite government and professional initiatives to reduce financial failure in Egypt. The current study uses the Kida model for predicting financial failure in Egyptian firms. According to the findings, the Kida model is deemed adequate for predicting Egyptian firms' financial failure, which was negative for most study years/firms.