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ACCOUNTING DATA, BANKRUPTCY, AND RISK

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Introduction Earnings is not the only accounting number available to investors in the capital market CAPM an asset’s market value is a function of its expected future cash flows, the risk of its future cash flows ( ), the market price of a risk, and the risk-free rate of return The risk-free rate and the market price of a risk are determined in the capital market A firm’s accounting data are likely to be more useful in estimating the firm’s securities expected cash flows and risk

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Accounting Data and Bankruptcy The nature of bankruptcy Corporate bankruptcies are “proceedings which are undertaken under bankruptcy laws when a corporation is unable to pay or reach agreement with its creditors outside of court” Ceteris paribus, the firm’s expected future cash flows and market value fall as the probability of bankruptcy increases Estimates of the value of stocks, bonds, and other claims on the firm depend on the probability that the firm will go bankrupt

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Accounting Data and Bankruptcy (Cont’d) The role of accounting data in predicting bankruptcy Most bankruptcy prediction models use accounting data. Often expressed in ratio form Reason: bond indentures and lending agreements often use accounting ratios to restrict managers’ actions Breach of the accounting ratio covenant places the firm in default and can lead to bankruptcy

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Accounting Data and Bankruptcy (Cont’d) Multivariate approaches to predicting bankruptcy Discriminant analysis Involves many variables Only the set of variables that “best” distinguishes between the failed and nonfailed groups is used to estimate z scores. Altman (1968): 22 variables are considered as candidates for the discriminant function The combination finally chosen consists of 5 variables (working capital/total assets, retained earnings/total assets, earning before interest and taxes/total assets, market value of equity/book value of total debt, sales/total assets)

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Accounting Data and Bankruptcy (Cont’d) Multivariate approaches to predicting bankruptcy (Cont’d) Discriminant analysis (Cont’d) Use holdout sample: to evaluate the discriminant function’s predictive ability

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Accounting Data and Bankruptcy (Cont’d) Multivariate approaches to predicting bankruptcy (Cont’d) Altman’s finding and those of other studies suggest that accounting data are useful in predicting bankruptcy. However, they do not provide evidence that accounting-based models outpredict the market Westerfield (1970) and Aharony, Jones, and Swary (1980) find that he bankrupt firm’s stock begin earning negative abnormal returns five years before bankruptcy

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Accounting Data and Bankruptcy (Cont’d) Multivariate approaches to predicting bankruptcy (Cont’d) Extensions Altman, Haldeman & Narayanan (1977) Estimate the relative costs of the two types of errors. Ohlson (1980) Earlier studies assume (often incorrectly) that the financial statements for the bankruptcy year are disclosed prior to the bankruptcy filling Requires the sample proportions of bankrupt and nonbankrupt firms be the same as the population proportions.

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Accounting Data and Bankruptcy (Cont’d) Multivariate approaches to predicting bankruptcy (Cont’d) A problem common to all studies is ad hoc selection of independent variables

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Accounting Data and Stock Risk - the measure of risk is estimated from the market model Assume that is stationarity over time, but it could vary from period to period. Trade-off: if is stationary, the longer the estimation period the better the estimate. But, the longer the estimation period, the more likely changes. Bogue (1972) and Gonedes (1973): 60 months is the optimal period for their sample

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Accounting Data and Stock Risk (Cont’d) It is possible that additional information can be used to obtain a “better” estimate of than that obtain form market model Accounting data can be used to provide estimates of for unlisted securities It is possible that better estimates can be obtained for listed securities by using accounting data in combination with the market model estimate of

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Accounting Data and Stock Risk (Cont’d) Accounting data and estimates Accounting earnings are surrogate for cash flows Financial leverage Operating leverage

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Accounting Data and Stock Risk (Cont’d) Accounting data and estimates (Cont’d) Ball & Brown (1968) “Accounting betas” are associated with market model estimates Beaver, Kettler & Scholes (1970) Variables: dividend payout, asset growth, leverage, liquidity, asset size, earnings variability, accounting beta Significant correlation: payout, leverage, earnings variability, accounting beta

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Accounting Data and Stock Risk (Cont’d) Accounting data and estimates (Cont’d) Beaver, Kettler & Scholes (1970), Bildersee (1975), Rosenberg & Maranthe (1975), Eskew (1979): models based on accounting variables forecast future levels of market risk more accurately than do models relying solely on prior market model estimates of Elgers (1980): accounting variables do not produce more accurate estimates of

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Accounting Data and Bond Risk Bond ratings and risk If bond ratings are measuring risk, ratings should be cross-sectionally correlated with Percival (1973) and Rozeff (1976): corporate bond ’s are systematically negatively related to ratings Urwitz (1975) finds that the correlation for ratings and is significantly higher than is the correlation for ratings and variance

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Accounting Data and Bond Risk (Cont’d) Evidence that rating agencies use accounting data Wakeman (1981): Explanations Accounting-based reasons accounted for more than two-thirds of the changes not involving new financing S&P’s assesses 5 areas in determining a bond’s rating: indenture provision, asset protection, financial resources (liquidity), future earning power, and management Timing of ratings changes Ratings changes are most common in May and June, both of which shortly follow the availability of most annual reports Empirical studies Kaplan & Urwitz (1979) find that total asset, long-term debt to total assets, and stock’s beta are statistically associated with ratings.

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Accounting Data and Bond Risk (Cont’d) Bonds ratings and market efficiency Weinstein (1977) and Wakeman (1981): find no bond price effect at the time of rating change.

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