Abstract

Research on the prediction of the failure of firms by using accounting information started in the second half of the 19th century and was intensified in the second half of the 20th century. Towards the end of the nineteenth century the practice arose of comparing current assets with current liabilities. Some researches in the 1930’s and 1940’s showed that net working capital/total capital assets, net profit/net worth, net worth/debt, net worth/fixed assets, net working capital/total assets, and the current ratio could be good predictors of failure. In the 1960’s Beaver found that the ability to predict failure is strongest for the cash-flow/total debt and net-income/total assets ratios. Starting from the late 1960’s the multiple ratio analyses prevailed upon the univariate analyses of firms’ failures. According to the Z-Score index obtained by a multiple discriminant analysis (MDA), the best predictors of failure are working capital/total assets, retained earnings/total assets, EBIT/total assets, market value of equity/book value of total debt, sales/total assets. In a second MDA generation model (ZETA model), retained earnings/total assets, appeared to be by far the most reliable predictor of failure. In 1980 Ohlson, applying a methodology of conditional logit analysis, found that three accounting ratios are statistically significant for purposes of assessing the probability of bankruptcy: total liabilities/total assets, net income/total assets, working capital/ total assets. In recent years Altman, Sabato and Wilson have developed a methodology for evaluating credit risk of small and medium sized enterprises (SMEs). The best predictors of failures turned out to be retained profit/total assets, quick assets/current assets, net cash/net worth, change in net worth, change in retained profit.

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