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Tranching and Rating Brennan, Hein, and Poon Comments by Mark Flannery Financial Innovations and Crises, May 11-13, 2009.

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Presentation on theme: "Tranching and Rating Brennan, Hein, and Poon Comments by Mark Flannery Financial Innovations and Crises, May 11-13, 2009."— Presentation transcript:

1 Tranching and Rating Brennan, Hein, and Poon Comments by Mark Flannery Financial Innovations and Crises, May 11-13, 2009

2 Motivation Many CDOs Large majority were “arbitrage” issuances, inconsistent with arbitrage-free asset pricing. Why? Moreover, bond CDOs had many tranches. Why? E.g., could manufacture AAA tranches with only one subordinated tranche. 2

3 Hypothesis: Some Investors Mis-value Complex Securities Sophisticated investors properly price corporate bonds. Naïve investors price complex securities according to ratings. Selling securities to naïve investors should permit profits. Paper shows how those profits depend on multiple tranches. 3

4 Hypothesized Security Pricing Ratings-based investors consider – Possible cash flows – Physical probabilities (p i ) “True” security value depends on – (Possible cash flows)*(state prices) – “risk-neutral probabilities” (q i ) 4

5 Sources of CDO Mis-valuation 1) Bonds default in high-value states (if β > 0) 2) Bond’s cash flows have high variance relative to “reference” bond the rating agency has in mind. 5

6 Firm’s Asset Value Distribution Probabilities V max Physical probabilities 6

7 Positive Beta and State Prices Probabilities V max Physical probabilities Risk neutral probabilities 7

8 Mispricing Cash-flows’ Beta Bond Payoffs ($) F 8

9 Mispricing Cash-flows’ Beta Bond Payoffs ($) F Credit Risk Premium, physical probabilities “R f ” 9

10 Β > 0  Promise higher repayment F F’ 10

11 Asset Variance and Default Losses Probabilities PD=5% “A” rated Bond repayment, LOW variance. “A” rated Bond repayment, HIGH variance. 11

12 Bond Payoffs ($) F RfRf Reference Bond Risk Premium on a Reference Bond’s Volatility 12

13 F F’ Mispricing Asset Return Variance 13

14 Issues: #1 Model provides a hypothesis that is consistent with multiple tranches. Is it consistent with the data? Were the bonds selected for CDOs 1.Higher beta? 2.Higher asset volatility? 3.Correlated with one another? 14

15 Issue #2 Can other hypotheses generate same prediction re: multiple junior tranches? E.g. knowing investors purchased these tranches as a way to write out-of-the money puts. – Hence “earn alpha” – Hence earn asymmetric hedge fund fees 15

16 Issue #3 What to do about rating agencies? Credibility may be slightly damaged (!) Some evidence of poor “care” on CDO ratings, at least for subprime mortgage pools. Fairly extensive government/regulatory reliance on these private firms. Help set new standards, that reflect cross- security distinctions? 16

17 Issue #4 Returning to the model here: can it be applied to corporate debt structures? Higher beta or volatility assets support more complex debt structures? Or, with unbiased information asymmetries, does higher volatility generate a greater range of selected debt structures? 17


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