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Financial Perspectives on Corporate Bankruptcy

Financial Perspectives on Corporate Bankruptcy

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Financial Perspectives on Corporate Bankruptcy

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  1. Financial Perspectives on Corporate Bankruptcy Professor Larry Weiss McDonough School of Business Georgetown University October 30, 2007 San Francisco

  2. Council Member Biography • Born and raised in Montreal Canada, Professor Weiss began his career as a Canadian Chartered Accountant working for KPMG. He received his undergraduate degree in Accounting and his MBA in General Management from McGill University. Larry earned his Doctorate in Accounting and Control from Harvard Business School. • Professor Weiss has served on the faculties of McGill University, Babson College, Tulane University, INSEAD, MIT's Sloan School of Management, HEC Lausanne, and is now at Georgetown University’s McDonough School of Business. He has also taught at Rochester-Bern, KREMS, CEIBS, The Helsinki University of Technology, the EPFL, the London Business School, and IMD. He won the teacher of the year award at MIT and was nominated for best professor at both Tulane University and INSEAD. • Professor Weiss' research focuses on the reorganization of financially distressed firms. He is a recognized expert on US corporate bankruptcy, and has testified before the US Congress on bankruptcy reform. He has over 40 publications, including: The Journal of Financial Economics; The Journal of Applied Corporate Finance; Financial Management, The Journal of Legal Economics; The American Bankruptcy Law Journal; Bankruptcy Developments Law Journal; Regulation; several trade journals and newspapers (including The New York Times and the Financial Times); numerous cases (published at Harvard and INSEAD); and a book published by Cambridge University Press. His work has been cited over 250 times and he has won the All Star Paper award from the Journal of Financial Economics.

  3. Topics • Predicting corporate bankruptcy using financial information • The financial impact of corporate bankruptcy • The rules of the game and their effect • How the rules are changing

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  7. Table of Contents • Predicting Corporate Bankruptcy Using Financial Information • Prior Research • State of the Art Techniques • Corporate Bankruptcy • The Rules of the Game • The Impact of the Rules • How the Rules are Changing

  8. Bankruptcy Prediction • Why should you care? • To predict whether a company will meet its future obligations has obvious benefits to a variety of groups and individuals: • Banks • Insurance companies • Fund managers • Investors • Customers • Creditors

  9. Prior Research • Based on financial ratios: • Beaver (1966) • Altman (1977) • Ohlson (1980) • Zmijewski (1984) • Palepu (1986) • Begley, Ming & Watts (1996) • Hillegeist, Keating, Cram & Lundstedt (2004) • Weiss & Capkun (2006) • Merton-like models • Merton (1974) • Crosbie (1999) – KMV CreditManager

  10. How Does it Really Work? • By using either regression (Altman Z score), logistic regression, option pricing approach (KMV) or any other method a model provides a probability that a certain company will default or declare bankruptcy. • It is up to you to decide whether to invest/lend and at what price/rate (or whether to accept the market price).

  11. Altman’s Z-score • The original Z-score equation was devised by Altman in 1968 and further developed in 1977. The original equation is: • Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 0.999 X5 • X1 = Working capital/Total assets • X2 = Retained earnings/Total assets • X3 = Earnings before interest and tax/Total assets • X4 = Market capitalization/Book value of debt • X5 = Sales/Total assets

  12. Altman’s Z-score • Altman identified two benchmarks. Companies scoring over 3.0 are unlikely to fail and should be considered safe, while companies scoring under 1.8 are very likely to fail. The value of 3 has since been revised down to 2.7. Z-scores between 1.8 and 2.7 are in the grey area.

  13. Bankruptcy Prediction • The problem with the current design of prediction models is that their success is defined as the percentage of firms predicted correctly. • The evaluation should be based on whether using the model will increase profits. To do this you must include: • Type I Error = the loss given default or bankruptcy of a company in which you invest or lend funds to • Type II Error = the profit you lost from not investing or lending to a company that didn’t go bankrupt.

  14. Type I and Type II Error Costs • If you do not include the cost of errors in bankruptcy prediction modeling, you can get a misleading impression on the true precision (profitability) of the model. • For example • % correct profit • Model I 96.24% 60.04% • Model II 92.72% 64.12% • Which Model Would You Want to Use?

  15. The Goal of a Bankruptcy/Default Prediction Model • To maximize the profit obtained by using a model (as opposed to the precision in the number of companies correctly classified). • Methodology: • Determine a probability of bankruptcy for each firm • Rank firms by probabilities from lowest to highest • Compute profit at each probability • Determine the cutoff that maximizes profit • Compare maximum profit with naive model profit

  16. Bankruptcy Prediction Computation • P(BI) XI Status A B Profit(Loss) Cumulative • 0.000 • 0.001 • • • • • • • • • 0.999 • 1.000

  17. Changes in Type I and Type II Errors • Type I and Type II errors will not be the same for all companies. • The ratio of Type I/Type II error costs will change with the probability of default. • Two Approaches to Choose a Cutoff • Approach I: Empirical estimation • Approach II: Model

  18. Improvements in Profitability by Including the Cost of Errors

  19. A World Without Bankruptcy • Race to Grab Assets • Excessive Monitoring Costs • Failure to Maximize Firm Value

  20. Managerial Incentives • Firm has Debt of 100, 2 possible mutually exclusive projects: • Project 1 Bad Good Expected • Firm payoff 101 105 103 • Debt payoff 100 100 100 • Equity payoff 1 5 3 • Project 2 Bad Good Expected • Firm payoff 50 150 100 • Debt payoff 50 100 75 • Equity payoff 0 50 25

  21. Direct Costs of Bankruptcy • Study Time period #Firms Mean • Workouts: • Gilson, John & Lang 1981-1988 18 0.65% • Prepacks: • Tashjian, Lease & McConnell 1986-1993 39 1.57% • Bankruptcy: • Stanley & Girth 1964 90 24.9% • Warner 1933-1955 11 4.0% • Ang, Chua & McConnell 1963-1978 55 7.5% • Weiss 1980-1986 31 2.8% • Does this seem large compared to tax shield of say 34%?

  22. Indirect Costs of Bankruptcy:Texaco v. Penzoil • Directors of Getty agree to sell 43% of their company to Penzoil • One week later, directors agree to sell 100% of Getty to Texaco • Texaco indemnifies Getty directors • Penzoil sues, Texas jury trial. • Jury award of $12 billion to Penzoil ($7.5 actual damages , $3 billion punitive, and $1.5 accrued interest) • Texaco equity down by $1 billion, debt down by $5 billion. • Penzoil up but by much less, Cutler & Summers estimate only 40% of Texaco’s drop in value was gained by Penzoil. • Texaco declares bankruptcy • How could you have made money on this situation?

  23. Texaco v. Penzoil – Financial Opportunity • Enter Carl Ichan • He purchased equity of Penzoil, debt & equity of Texaco • Did Carl make money? Yes! • How did Carl make money? Removed conflict of interest! • Settlement – Texaco paid Penzoil $3 billion. • Cutler and Summers estimate the direct costs at $525 million and the indirect costs at $1.2 billion. They would have been higher if not for Carl Ichan.

  24. US Corporate Bankruptcy - Overview • Chapter 7 – Liquidation • Chapter 11 – Reorganization • File where incorporated, main business, sub has filed • Debtor has 120 days to file plan, 60 more to get approval • Approval with majority in number, 2/3 by $ of those who vote

  25. Some Major Examples • Eastern Airlines • K-Mart

  26. Traditional (post 1980) Academic View for Major US Bankruptcy Cases • Debtor in Possession & Control • Low (34%) CEO turnover • Rampant violations to priority of claims • Both secured & unsecured • Though primarily between unsecured • Takeover opportunity through low ranked debt

  27. New Directions (post 1990) for Major US Corporate Bankruptcies Cases • Looking more like European bankruptcies • What this means to you: • Less opportunity for greenmail • Lower payouts to unsecured – maybe • Increased liquidations (more takeover targets)

  28. New Directions (post 1990) for Major US Corporate Bankruptcies Cases • Rare Violations to Absolute Priority of Claims • Secured creditors normally in charge • Majority of CEOs (75%) replaced (-1 to +3) • Looking more like pre US 1978 bankruptcies • What this means to you: • Less opportunity for greenmail • Lower payouts to unsecured – maybe • Increased liquidations (more takeover targets)