Analyzing Bankruptcy Risk
This section discusses the analysis of bankruptcy risk by using information in the financial statements.
This section discusses the analysis of bankruptcy risk by using information in the financial statements.
The Bankruptcy Process
During the recession of 2008–2009, a staggering number of large, well-known firms filed for bankruptcy, including IndyMac Bancorp (July 2008), Lehman Brothers (September 2008), Washington Mutual (September 2008), Circuit City (November 2008), Tribune Group (December 2008), Saab Automobile (February 2009), Chrysler (April 2009), General Motors (June 2009), Eddie Bauer (June 2009), The Jolt Company (September 2009), and Simmons Bedding (November 2009). Subsequently, many more typically
During the recession of 2008–2009, a staggering number of large, well-known firms filed for bankruptcy, including IndyMac Bancorp (July 2008), Lehman Brothers (September 2008), Washington Mutual (September 2008), Circuit City (November 2008), Tribune Group (December 2008), Saab Automobile (February 2009), Chrysler (April 2009), General Motors (June 2009), Eddie Bauer (June 2009), The Jolt Company (September 2009), and Simmons Bedding (November 2009). Subsequently, many more typically
.After that period elapses, creditors, employees, and others can file their plans of reorganization. One such plan might include immediately selling the assets of the business and paying creditors the amounts due. The court decides which plan provides the fairest treatment for all parties concerned. While the firm is in bankruptcy, creditors cannot demand payment of their claims. The court oversees the execution of the reorganization. When the court determines that the firm has executed the plan of reorganization successfully and appears to be a viable entity, the firm is released from bankruptcy. In contrast to Chapter 11, a Chapter 7 filing entails an immediate sale, or liquidation, of the firm’s assets and a distribution of the proceeds to the various claimants in the order of priority.
Firms typically file for bankruptcy when they have insufficient cash to pay creditors’ claims coming due. If such firms did not file for bankruptcy, creditors could exercise their right to take possession of any collateral pledged to secure their lending and effectively begin liquidation of the firm. In an effort to keep assets intact and operating activities functioning and to allow time for the firm to reorganize, the firm files for bankruptcy. In recent years, some firms have filed for bankruptcy for reasons other than insufficient liquid resources to pay creditors. Some firms have filed for bankruptcy to avoid labor contracts or retirement obligations, because the firms considered them too costly. Other firms facing potentially costly litigation have filed for bankruptcy as a means of forcing the contending party to negotiate a settlement
Models of Bankruptcy Prediction
Empirical studies of bankruptcy attempt to distinguish the financial characteristics of firms that file for bankruptcy from those that do not. The objective is to develop a model that predicts which firms will likely file for bankruptcy within one or more years. These models use financial statement ratios and other data.
Univariate Bankruptcy Prediction Models
Early research on bankruptcy prediction in the mid-1960s used univariate analysis. Univariate models examine the relation between a particular financial statement ratio and bankruptcy. Multivariate models, discussed next, combine several financial statement ratios to determine whether the set of ratios together can improve bankruptcy prediction. Beaver10 studied 29 financial statement ratios for the five years preceding bankruptcy using a sample of 79 bankrupt and 79 nonbankrupt firms. The objective was to identify the ratios that best differentiated between these two groups of firms and to determine how many years prior to bankruptcy the differences in the ratios emerged. The six ratios with the best discriminating power (and the nature of the risk that each ratio measures) were as follows
1. Net Income plus Depreciation, Depletion, and Amortization/Total Liabilities (long-term solvency risk)11
2. Net Income/Total Assets (profitability
3. Total Debt/Total Assets (long-term solvency risk)
4. Net Working Capital/Total Assets (short-term liquidity risk)
5. Current Assets/Current Liabilities (short-term liquidity risk)
6. Cash, Marketable Securities, Accounts Receivable/Operating Expenses Excluding
Depreciation, Depletion, and Amortization (short-term liquidity risk)
Note that this list includes profitability, short-term liquidity risk, and long-term solvency risk ratios. Beaver’s best predictor was net income plus depreciation, depletion, and amortization divided by total liabilities. Exhibit 5.12 summarizes for each of the five years preceding bankruptcy the success of this ratio in correctly predicting firms that go bankrupt. The predictive accuracy increased as bankruptcy approached, but was close to 80% for as early as five years preceding bankruptcy.
The error rates deserve particular attention, however. A Type I error is classifying a firm as nonbankrupt when it ultimately goes bankrupt. A Type II error occurs when afirm is classified as bankrupt and ultimately survives. A Type I error is more costly to an investor because of the likelihood of losing the full amount invested. A Type II error costs the investor the opportunity cost of earnings from funds invested. Note in Exhibit 5.12 that the Type I error rates are much higher than the Type II error rates in Beaver’s study. When the net income before depreciation, depletion, and amortization to total liabilities ratio is used to predict bankruptcy four years prior to bankruptcy, 47% of the predictions that firms would be nonbankrupt turned out to be incorrect, whereas only 3% of the predictions that firms would be bankrupt turned out to be incorrect. Because univariate analysis helps identify factors related to bankruptcy, it is a useful step in the initial development of predictors of bankruptcy risk. However, in the assessment of risk, univariate analysis does not provide a means of measuring the relative importance of individual financial statement ratios or of combining them. For example
Firms typically file for bankruptcy when they have insufficient cash to pay creditors’ claims coming due. If such firms did not file for bankruptcy, creditors could exercise their right to take possession of any collateral pledged to secure their lending and effectively begin liquidation of the firm. In an effort to keep assets intact and operating activities functioning and to allow time for the firm to reorganize, the firm files for bankruptcy. In recent years, some firms have filed for bankruptcy for reasons other than insufficient liquid resources to pay creditors. Some firms have filed for bankruptcy to avoid labor contracts or retirement obligations, because the firms considered them too costly. Other firms facing potentially costly litigation have filed for bankruptcy as a means of forcing the contending party to negotiate a settlement
Models of Bankruptcy Prediction
Empirical studies of bankruptcy attempt to distinguish the financial characteristics of firms that file for bankruptcy from those that do not. The objective is to develop a model that predicts which firms will likely file for bankruptcy within one or more years. These models use financial statement ratios and other data.
Univariate Bankruptcy Prediction Models
Early research on bankruptcy prediction in the mid-1960s used univariate analysis. Univariate models examine the relation between a particular financial statement ratio and bankruptcy. Multivariate models, discussed next, combine several financial statement ratios to determine whether the set of ratios together can improve bankruptcy prediction. Beaver10 studied 29 financial statement ratios for the five years preceding bankruptcy using a sample of 79 bankrupt and 79 nonbankrupt firms. The objective was to identify the ratios that best differentiated between these two groups of firms and to determine how many years prior to bankruptcy the differences in the ratios emerged. The six ratios with the best discriminating power (and the nature of the risk that each ratio measures) were as follows
1. Net Income plus Depreciation, Depletion, and Amortization/Total Liabilities (long-term solvency risk)11
2. Net Income/Total Assets (profitability
3. Total Debt/Total Assets (long-term solvency risk)
4. Net Working Capital/Total Assets (short-term liquidity risk)
5. Current Assets/Current Liabilities (short-term liquidity risk)
6. Cash, Marketable Securities, Accounts Receivable/Operating Expenses Excluding
Depreciation, Depletion, and Amortization (short-term liquidity risk)
Note that this list includes profitability, short-term liquidity risk, and long-term solvency risk ratios. Beaver’s best predictor was net income plus depreciation, depletion, and amortization divided by total liabilities. Exhibit 5.12 summarizes for each of the five years preceding bankruptcy the success of this ratio in correctly predicting firms that go bankrupt. The predictive accuracy increased as bankruptcy approached, but was close to 80% for as early as five years preceding bankruptcy.
The error rates deserve particular attention, however. A Type I error is classifying a firm as nonbankrupt when it ultimately goes bankrupt. A Type II error occurs when afirm is classified as bankrupt and ultimately survives. A Type I error is more costly to an investor because of the likelihood of losing the full amount invested. A Type II error costs the investor the opportunity cost of earnings from funds invested. Note in Exhibit 5.12 that the Type I error rates are much higher than the Type II error rates in Beaver’s study. When the net income before depreciation, depletion, and amortization to total liabilities ratio is used to predict bankruptcy four years prior to bankruptcy, 47% of the predictions that firms would be nonbankrupt turned out to be incorrect, whereas only 3% of the predictions that firms would be bankrupt turned out to be incorrect. Because univariate analysis helps identify factors related to bankruptcy, it is a useful step in the initial development of predictors of bankruptcy risk. However, in the assessment of risk, univariate analysis does not provide a means of measuring the relative importance of individual financial statement ratios or of combining them. For example
does a firm with a high current ratio and a high debt-to-assets ratio have more bankruptcy risk than a firm with a low current ratio and a low debt-to-assets ratio? The analyst also must subjectively judge the level of each financial ratio that signals a high probability of bankruptcy.
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