Morningstar Advisor - December/January 2010 - 21

Recently, Morningstar’s valuation research team re-examined Distance to Default and another bankruptcy prediction model— the Z-Score—to assess their predictive power. Under the extreme conditions of the financial crisis, are these models proving their mettle? The Models The Z-Score, developed by Edward Altman, a professor of finance at New York University, is perhaps the most familiar model for predicting financial distress (Bemmann 2005). Altman identified five common accounting ratios that significantly predict default. The five pillars are combined in an equation that result in a company’s Z-Score (Altman 2002). Morningstar’s Distance to Default model is less intuitive than the Z-Score because it does not specifically address the cash accounting values that practitioners and professionals typically examine in a default or bankruptcy. The Distance to Default model considers a company’s equity as a call option on the firm’s assets with a strike price equal to the book value of its liabilities and a market price equal to the market value of the firm’s assets. Distance to Default describes the probability that this hypothetical call option will end up worthless—in effect, the potential that it will default if the value of the firm’s assets drops below the book value of the firm’s liabilities. Based on the current market value of a company’s assets, the historical volatility of those assets, and the current book value of a company’s liabilities, we can calculate Distance to Default. (For the complete methodology, see Warren Miller’s paper, “Comparing Models of Corporate Bankruptcy Prediction: Distance to Default vs. Z-Score.” It is available for free download from the White Paper Bank on MorningstarAdvisor.com.) In our study, we also included a simple, single-variable model based on the ratio of total liabilities to total assets (TLTA) to act as a benchmark for comparing the bankruptcy prediction models; even individual accounting ratios and measures of capital structure may predict bankruptcy potential to some degree. In this case, we would expect the probability of bankruptcy to increase as the TLTA ratio increases. Our comparison of the Z-Score and Distance to Default models is not a contest. Rather, it sheds light on the strengths and weaknesses of each and gives investors an understanding of what’s available to them in order to evaluate the creditworthiness of public and private companies. We are also cognizant of the fact that the Z-Score was intended to gauge the financial health of manufacturing companies (Altman 2002). Nonetheless, we included non-manufacturing companies in our study because, in practice, the Z-Score is commonly used to evaluate the financial health of all companies. Collecting and Refining the Data Using data from Bloomberg, we first compiled a master bankruptcy list of 502 companies that declared chapter 7 or 11 bankruptcy between March 1998 and June 2009. Next, we extracted the necessary data from Distance to Default values provided by the Center for Research in Security Prices at the University of Chicago’s Booth School of Business. We then calculated Z-Score and TLTA values with data from Morningstar’s Equity XML Output Interface. We transformed each of the three ratings into a percentile score using breakpoints based on all the data over a 10-year history. The higher the percentile, the more prone to default a company was rated. Finally, we matched our master bankruptcy list with the three percentile datasets. When compiling data for the models, we expunged each company-date pairing that did not include all relevant data points from that model’s dataset. Therefore, the company data we used overlapped within the three models, but they did not include identical company-date records. The Results z 5 1.2x1 1 1.4x2 1 3.3x3 1 0.6x4 1 1.0x5 x1 5 working capital total assets retained earnings total assets earnings before interest and taxes (EBIT) total assets market value of equity book value of total liabilities sales total assets x2 5 x3 5 x4 5 x5 5 Each factor is intuitively appealing to investors because it captures a different creditrelevant aspect of a company’s operations. Liquidity, cumulative profitability, asset productivity, market-based financial leverage, and capital turnover are addressed by the five ratios. The Z-Score presumes that each ratio is linearly related to a company’s probability of bankruptcy. The best way to compare the performance of credit-scoring models with non-identical sample sets is to measure their ability to differentiate between companies that are most likely to go bankrupt within a year from those that are least likely (Bemmann 2005). We tested each model’s ability to rank companies from least to most likely to declare bankruptcy as well as the rankings’ durability and stability. We also performed two tests of each model’s cardinal ability to predict bankruptcy. MorningstarAdvisor.com 21

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Morningstar Advisor - December/January 2010

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