This can happen if for example a pending lawsuit was

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Z-score indicates the company is healthy, yet the company goes bankrupt. This can happen if, for example, a pending lawsuit was not recognized in the financial statements, or a sudden downturn in the industry forced the company to fail despite adequate recent performance. A Type II error occurs when a company's Z-score indicates the company is likely to go bankrupt, yet the company remains solvent. This can happen if the company is rebounding from a small downturn in business or has recently gone public and its ratios are weak because of the com- pany's age. Exhibit 4.10 shows both types of error. ~ EXHIBIT 4.10 Z-Score Prediction Errors Predicted Classification Bankrupt Non-Bankrupt r:::: I I Correct prediction I 0 Bankrupt Type I error :;;:; Q) ~ ::J .- .=~ (J) m I Non-Bankrupt I Type II error Correct prediction (3 Given the potential for both Type I and Type II errors, a Z-score must be viewed as only one piece of evidence for assessing bankruptcy risk. Altman twice revised the Z-score model to allow for different industries and firm-age, as well as for privately-held firms. These models are more accurate when applied to those types of companies. Altman and other researchers also developed the ZETA analysis, which adds new variables for the persistence of earnings, the interest coverage ratio (EBIT/interest payments). the current ratio, the company capitalization (MVEltotal capital), and the company size (natural logarithm of total assets)-see E. Altman, R. Haldeman, and P. Narayanan, "ZETA Analysis: A New Model to Identify Bankruptcy Risk of Corporations," Journal of Banking and Finance, June 1977. With the ZETA analysis, Altman et al. recommend adjustments to financial statement num- bers to reflect the true underlying economics. The ZETA model performs similarly with Z-score in short-term predictive accuracy, but it yields better long-term predictions (up to 70% prediction accuracy five years before bankruptcy). ~
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Module4 I CreditRiskAnalysisandInterpretation 4-30 3lJSINESS INSIGHT Predicting Bankruptcy for Private Companies dy's KMV RiskCalc™ uses extensive data from 1,600 credit defaults in the private sector. The el provides an example of how credit rating agencies assess the likelihood of default and bank- icy. Most notably, Moody's model differs in a two-pronged assessment of solvency: financial- ement-only mode and a credit-cycie-adjusted mode. The latter adjusts for a company's stage of credit cycle and is assessed on an industry-wide and country-wide basis that is updated monthly. financial-statement-only risk evaluation is quite similar in spirit to Altman's original Z-score model, lying slightly different variables to capture leverage, profitability, liquidity, size, and growth. (Source: 's, "RiskCalc Private Model: Moody's Default Model for Private Firms," Global Credit Research, 2004.) uired Compute and interpret the Altman Z-score for Lowe's Companies for the year ended January 28, 2011. On that date, the company's stock closed at $25.25 per share.
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