Financial Ratios as Predictors of Failure: Evidence from ... - ERIM

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Altman and Brenner, 1981). According to the classic Capital Asset Pricing Model (CAPM) 8 , investors would expect higher returns for bearing more risk. The first and most well-know empirical tests can be traced back to over 30 years ago. For example, Black et al (1972) provided empirical tests and additional insights based on the original CAPM model. They confirmed that the beta factor (firm-specific risk) is important in determining security returns using cross-sectional tests. More recently, Chava and Purnanandam (2008) uncovered the risk-return relation by extending their sample period, and suggested that expected returns are positively correlated with bankruptcy. Consequently, there should be a positive relation between return on equity and default risk. 3.2 Multi factors in predicting PD and the methodologies 3.2.1 Multiple Discriminant Analysis Many scholars have incorporated various factors in terms of financial ratios into their predicting model in order to discriminate default and non-default companies. Beaver (1966) and Altman (1968) pioneered the studies. By using univariate analysis, Beaver pairwisely compared failed and non-failed companies and found that ratios like cash flow/total assets, net income/total assets, total debt/total assets, and cash flow/total debt 9 in particular were important indicators of failure. Later, based on his research, Altman (1968) developed the classic Multiple Discriminant Analysis (MDA) and Z-score model. Being more advanced than univariate analysis, MDA examines the entire variable profile simultaneously instead of sequentially testing individual variables. The five accounting 8 E(R)=Rf+β*(Rm- Rf), E(R) is the expected return of the capital asset, Rf is the risk-free rate of interest, β is the sensitivity of the asset returns to market returns, Rm is the expected return of the market, (Rm- Rf) is the difference between expected return on market and risk-free rate, or also known as risk premium. Since most investors are diversified, the expected return on a security should be positively related to its beta. The model was introduced by Treynor (1962), Sharpe (1964), Lintner (1965), and Mossin (1966). 9 Cash flow/total debt has predictive power up to five years before bankruptcy. 9
atios he employed in the research were working capital/total assets, retained earnings/total assets, earning before interest and taxes/total assets, market value equity/book value of total debt, and sales/total assets. The model proved very accurate when tested on a sample of US manufacturing firms, and the predictive value of the model for the first two years prior to bankruptcy was quite high (correct prediction: 95% for year one and 72% for year two). Following his previous research, Altman et al (1977) constructed a second-generation model, called ZETA. ZETA model was effective in classifying bankrupt companies up to five years prior to failure on a sample of corporations consisting of manufacturers and retailers. Many other scholars have also applied multidimensional models in their studies (see for example, Deakin (1972) and Sinkey (1975)). 3.2.2 Logistic Regression Later, new econometric methodology of logit and probit analysis has been introduced into this field. There is no fundamental difference between logit and probit models, except that the conditional probability p approaches zero or one at a slower rate in logit than in probit. In practice many researchers choose logit model because of its comparative mathematical simplicity (Gujarati, 2003). Comparing to quantitative explanatory variables in normal regression, dependent variables in logistic regression are normally qualitative (or dummy). Martin (1977) first intended to build an early warning model for predicting future bank failure based on current period’s balance sheet and income statement by using logistic regression. Ohlson (1980) tested the 1970-1976 industrial sample data, and found that the predictive power of the default risk model (two years before default) based on financial ratios seemed to be robust. Meanwhile, he found four basic factors being significant with probability of failure (within one year), namely firm 10
Page 1 and 2: 17 Nov 2008 Financial Ratios as Pre
Page 3 and 4: Abstract This paper presents some e
Page 5 and 6: 1. Introduction One year after the
Page 7 and 8: However he did not find substantial
Page 9: interest in predicting bankruptcy b
Page 13 and 14: there are specific statistical requ
Page 15 and 16: “returns”, “values” and “
Page 17 and 18: Table 2 Explanatory Variables Varia
Page 19 and 20: which results in high standard erro
Page 21 and 22: Table 7 Variables in the Equation (
Page 23 and 24: Summary. -2 log likelihood (-2LL) i
Page 25 and 26: predicted to be default, it is call
Page 27 and 28: estimation procedure. However it is
Page 29 and 30: Ohlson (1980)). In the second sampl
Page 31 and 32: Reference Altman, E. I., 1968, “F
Page 33 and 34: Hong Kong Society of Accountants, 1
Page 35 and 36: MDA Appendix One Table 1 Literature
Page 37 and 38: Appendix Two Table 4 Descriptive St
Page 39 and 40: Appendix Four Table 9 Coefficients
Page 41 and 42: Appendix Six Table 10 Coefficients
Page 43 and 44: Appendix Eight Table 12 Classificat

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