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Market share and risk taking: the role of collateral asset managers in the collapse of the arbitrage CDO market

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Abstract

Asset pricing theory predicts that if credit ratings do not reflect all relevant aspects of a CDO debt tranche’s risk profile (i.e., its total and systematic risk), then ratings-based tranche pricing by some naïve investors creates incentives for CDO arrangers to take excessive non-priced risk. CDO managers’ desire for repeat issuance makes them part of this risk taking strategy to exploit naïve investors. The implication is that the credit quality of CDOs run by large market share managers has a higher tendency to deteriorate in bad times. This paper finds empirical evidence for large market share manager’s conflicts of interest.

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Notes

  1. Furthermore, the findings in Sect. 6.3 below indicate that large managers’ risk taking incentives do not come from higher incentive compensation levels. Focusing on CLOs, Benmelech et al. (2012, pp. 94–95) also argue that “CLO managers’ compensation is only weakly tied to deal performance” and “that CLO management is primarily a volume business”.

  2. For example, most CDO management agreements contain a clause that deals with the termination of the management mandate. Usually a two-thirds majority of the equity holders is necessary to change the current manager and appoint a replacement manager. There is much anecdotal evidence suggesting that CDO manager incentives are systematically biased towards the interests of deal arrangers/equity investors. See the following two pieces from Bloomberg News: Shenn J, How Wing Chau Helped Neo Default in Merrill CDOs Under SEC View (May 9, 2010) and Ivry B, and Shenn J, How Lou Lucido Helped AIG Lose $35 Billion With CDOs Made by Goldman Sachs (March 31, 2010).

  3. Note that the analyzed default rates are effectively ‘cumulative’ default rates. That is, almost all of the ABS/MBS collateral tranches that defaulted during 2007–2008 are still in default (not liquidated) in 2010. Hence, deals with more collateral defaults in 2007–2008 will also have higher default rates in June 2010. In unreported robustness checks, I confirm that all results remain unchanged for default rates measured as of February 2009.

  4. The paper also contributes to recent literature investigating the form of default risk ratings are actually measuring—total or systematic risk. For corporate bond ratings, Hilscher and Wilson (2012) and Iannotta and Pennacchi (2012) find that ratings are not primarily or exclusively a measure of firm-specific raw default probabilities, but are also (partially) informative about the tendency of a bond issuer’s default risk to worsen in bad times. For CDO ratings, however, this paper actually finds no association with systematic risk. Finally, the paper is related to recent literature (e.g., Downing et al. 2009; Keys et al. 2010; Piskorski et al. 2010) on agency problems associated with the securitization process.

  5. According to data from the Securities Industry and Financial Markets Association (SIFMA 2012), CDO issuance activity drastically increased in the years prior to the subprime crisis with total quarterly issuance exploding from $48.0 billion in the first quarter of 2005 to $178.6 billion in the second quarter of 2007. On average, 87 % of this growth came from arbitrage CDOs, or, more precisely, from ABS-CDOs that accounted for around 70 % of arbitrage CDO issuance. ABS-CDOs are second-layer securitizations that do not contain plain vanilla bonds or loans in their collateral pools, but assets which are itself structured like tranches from ABS or MBS.

  6. There is much anecdotal and limited empirical evidence suggesting that some managers follow excessively risky investment strategies. For example, in a case study of managed CBOs (collateralized bond obligations), Fu and Gus (2003) explain that “much of the portfolio under-performance can be attributed to industry concentration […] and an “aggressive” investment philosophy. […] In addition to making bad credit choices, some managers have purchased discounted securities or engaged in risky trading strategies to avoid triggering O/C tests that would otherwise have required diverting money from junior to the most senior noteholders.” Several other examples of excessive manager risk taking are cited in Garrison (2005, pp. 5–6).

  7. The Basel Committee on Banking Supervision writes (BIS 2008, p. 67): “Credit ratings, which focus only on contractual payment obligations, are not designed to capture differences in sensitivity to systematic risk.”

  8. Obviously, a tranche’s sensitivity to movements in collateral asset correlation depends on its position in the deals’ capital structure. In particular, while equity tranche investments are typically long correlation positions (tranche premium decreases as correlation increases), senior tranche investments are short correlation (tranche premium increases as correlation increases). The argument that the standard approach used by agencies to model asset correlation, the one-factor Gaussian copula, is fundamentally flawed can be supported by the well known ‘correlation smile’ phenomenon (see Cifuentes and Katsaros 2007).

  9. Deal ratings are constructed by weighting the corresponding (average) tranche ratings by their principal amounts. Tranche ratings were converted to a point scale where AAA corresponds to 1 and then each rating notch gets one point more (i.e., AA+/Aa1 = 2, …, B−/B3 = 16). Hence, higher numbers reflect more default risk.

  10. Home equity loan securities are residential mortgage-backed securities whose cash flows are backed by a pool of home equity loans. Home equity loans, in turn, are second lien mortgages in which borrowers use the equity in their homes as collateral.

  11. Because lagged market shares cannot be computed for deals issued in the first year (2000) of the sample, the number of deals included in the regressions below is reduced to 550.

  12. The correlation coefficients are: −0.816 between Fraction AAA and Deal rating, 0.517 between Equity share and Deal rating, and −0.297 between Equity share and Fraction AAA.

  13. I control for the possibility that large managers are more likely to receive inflated ratings through ratings shopping (i.e., get more than one rating and then only disclose the highest one). In particular, I include dummies for the number of ratings and the identity of raters rating a deal into the regressions of Table 3. The results for Mshare remain unchanged. Also, the deal rating (rounded to the closest integer) is converted in a series of dummies in order to capture non-linearities, without affecting the results.

  14. I do not consider fixed rate tranches for two reasons. The first is small sample size. Whereas for 2873 floating rate tranches all required information (float formula, ratings, tranche controls) is available, there are only 296 fixed rate tranches (thereof 39 AAA) with full information in the sample. Second, yield spreads for fixed rate CDO tranches are hard to obtain due to missing weighted average life estimates (an approximation for the expected maturity of the security) in the data. When I regress the fixed coupon of the tranches on Mshare and controls, I find a positive and weakly significant (p value: 0.09) coefficient for the log of one plus Mshare.

  15. See, e.g., Goldberg (2013) or Ju et al. (2013) for a general discussion of capital structure arbitrage (or debt-equity arbitrage).

  16. It appears to be a widespread believe also among academics that mortgage-related CDOs were mispriced prior to the subprime crisis. For example, Jarrow (2011, p. 16) states that “… it is reasonable to conclude that the CDO bonds issued were overvalued.” In a similar vein, Partnoy and Skeel (2007, p. 1046) argue: “There are only two possibilities: either CDOs are being used to arbitrage a substantial price discrepancy in the fixed income markets or CDOs are being used to convert existing fixed income instruments that are priced accurately into new fixed income instruments that are overvalued. … The second possibility seems more likely”.

  17. See especially Chapters 8–10 of the FCIC report (FCIC 2011) for an excellent discussion of the structures and players behind the mortgage CDO market in the years leading up to the subprime crisis. Mählmann (2013) provides an analysis of potential conflicts of interest associated with the introduction of synthetic CDOs.

  18. However, if hedge funds are the ones with the desire to short, and they work with different investment banks to structure different deals, underwriter fixed effects are an imperfect control for the incentives of these hedge fund deal originators.

References

  • Adelino M (2009) Do investors rely only on ratings? The case of mortgage-backed securities. Working paper, MIT

  • Ashcraft A, Goldsmith-Pinkham P, Vickery J (2010) MBS ratings and the mortgage credit boom. Working paper, Federal Reserve Bank of New York

  • Ashcraft A, Goldsmith-Pinkham P, Hull P, Vickery J (2011) Credit ratings and security prices in the subprime MBS market. Am Econ Rev 101:115–119

    Article  Google Scholar 

  • Benmelech E, Dlugosz J (2009) The credit rating crisis. NBER Macro Annu 24:161–207

    Article  Google Scholar 

  • Benmelech E, Dlugosz J, Ivashina V (2012) Securitization without adverse selection: the case of CLOs. J Financ Econ 100:91–113

    Article  Google Scholar 

  • Bhansali V, Gingrich R, Lonstaff FA (2008) Systemic credit risk: What is the market telling us? Financ Anal J 64:16–24

    Article  Google Scholar 

  • BIS (2008) The Joint Forum—credit risk transfer: developments from 2005 to 2007. Bank for International Settlements, Basel

    Google Scholar 

  • Bolton P, Freixas X, Shapiro JD (2012) The credit ratings game. J Finance 67:85–111

    Article  Google Scholar 

  • Boot AWA, Thakor A (1993) Security design. J Finance 48:1349–1378

    Article  Google Scholar 

  • Brennan MJ, Hein J, Poon S-H (2009) Tranching and rating. Eur Financ Manag 15:891–922

    Article  Google Scholar 

  • Cifuentes A (2008) Turmoil in U.S. credit markets: the role of the credit rating agencies. Testimony of Arturo Cifuentes, Managing Director Structured Finance Department, R. W. Pressprich & Co. New York, NY. Before the Senate Committee on Banking, Housing and Urban Affairs, April 22, 2008

  • Cifuentes A, Katsaros G (2007) The one-factor Gaussian copula applied to CDOs: just say no (or, if you see a correlation smile, she is laughing at your “results”). J Struct Finance Fall 2007:60–71

    Article  Google Scholar 

  • Collin-Dufresne P, Goldstein RS, Yang F (2012) On the relative pricing of long-maturity index options and collateralized debt obligations. J Finance 67:1983–2014

    Article  Google Scholar 

  • Cordell L, Huang Y, Williams M (2011) Collateral damage: sizing and assessing the subprime CDO crisis. Working paper, Federal Reserve Bank of Philadelphia

  • Coval J, Jurek J, Stafford E (2009a) Economic catastrophe bonds. Am Econ Rev 99:628–666

    Article  Google Scholar 

  • Coval J, Jurek J, Stafford E (2009b) The economics of structured finance. J Econ Perspect 23:3–25

    Article  Google Scholar 

  • Dang TV, Gorton G, Holmström B (2009) Opacity and the optimality of debt for liquidity provision. Working paper, Yale

  • Downing C, Jaffee D, Wallace N (2009) Is the market for mortgage-backed securities a market for lemons? Rev Financ Stud 22:2461–2494

    Article  Google Scholar 

  • Financial Crisis Inquiry Commission (FCIC) (2011) The financial crisis inquiry report. Financial Crisis Inquiry Commission. http://fcic.law.stanford.edu/

  • Fu Y, Gus H (2003) U.S. high-yield CDOs: analyzing the performance of a beleaguered CDO category. Moody’s Investors Service, Special Report, Jan 2003

  • Garrison K (2005) Manager incentives in collateralized debt obligations. Working paper, MIT

  • Goldberg RS (2013) A methodology for computing and comparing implied equity and corporate-debt Sharpe ratios. Rev Quant Finance Account. doi:10.1007/s11156-013-0424-2

    Google Scholar 

  • Gorton G, Pennacchi G (1990) Financial intermediaries and liquidity creation. J Finance 45:49–72

    Article  Google Scholar 

  • Griffin JM, Tang DY (2011) Did credit ratings make unbiased assumptions on CDOs? Am Econ Rev 101:125–130

    Article  Google Scholar 

  • Griffin JM, Tang DY (2012) Did subjectivity play a role in CDO credit ratings? J Finance 67:1293–1328

    Article  Google Scholar 

  • Hamerle A, Liebig T, Schropp HJ (2009) Systematic risk of CDOs and CDO arbitrage. Deutsche Bundesbank Discussion paper no. 13, Frankfurt

  • He J, Qian J, Strahan PE (2012) Are all ratings created equal? The impact of issuer size on the pricing of mortgage-backed securities. J Finance 67:2097–2137

    Article  Google Scholar 

  • Hilscher J, Wilson M (2012) Credit ratings and credit risk. Working paper, Brandeis University

  • Iannotta G, Pennacchi G (2012) Bank regulation, credit ratings, and systematic risk. Working paper, Universitá Bocconi/University of Illinois

  • Jarrow RA (2011) The role of ABS, CDS and CDOs in the credit crisis and the economy. Working paper, Cornell University

  • Ju H-S, Chen R-R, Yeh S-K, Yang T-H (2013) Evaluation of conducting capital structure arbitrage using the multi-period extended Geske–Johnson model. Rev Quant Finance Account. doi:10.1007/s11156-013-0400-x

    Google Scholar 

  • Keys BJ, Mukherjee T, Seru A, Vig V (2010) Did securitization lead to lax screening? Evidence from subprime loans. Q J Econ 125:307–362

    Article  Google Scholar 

  • Li H, Zhao F (2012) Economic catastrophe bonds: inefficient market or inadequate model? Working paper, University of Michigan/University of Texas at Dallas

  • Magnetar (2010) Magnetar investor letter. April 19, 2010. http://www.propublica.org/documents/item/magnetar-letter-to-investors-about-propublica-article

  • Mählmann T (2010) Securitizations and the subprime crisis: the collapse of the market for ABS–CDOs. Die Betriebswirtschaft 70:405–423

    Google Scholar 

  • Mählmann T (2012) Did investors outsource their risk analysis to rating agencies? Evidence from ABS–CDOs. J Bank Finance 36:1478–1491

    Article  Google Scholar 

  • Mählmann T (2013) Hedge funds, CDOs and the financial crisis: an empirical investigation of the ‘Magnetar trade’. J Bank Finance 37:537–548

    Article  Google Scholar 

  • Mathis J, McAndrews J, Rochet J-C (2009) Rating the raters: Are reputation concerns powerful enough to discipline rating agencies? J Monet Econ 56:657–674

    Article  Google Scholar 

  • Papke LE, Wooldridge JM (1996) Econometric methods for fractional response variables with an application to 401(k) plan participation rates. J Appl Econom 11:619–632

    Article  Google Scholar 

  • Partnoy F, Skeel DA (2007) The promise and perils of credit derivatives. Univ Cincinnati Law Rev 75:1019–1051

    Google Scholar 

  • Piskorski T, Seru A, Vig V (2010) Securitization and distressed loan renegotiation: evidence from the subprime mortgage crisis. J Financ Econ 97:369–397

    Article  Google Scholar 

  • SIFMA (2012) Global CDO issuance 2000–2011. Securities Industry and Financial Markets Association, London

    Google Scholar 

  • Skreta V, Veldkamp L (2009) Rating shopping and asset complexity: a theory of ratings inflation. J Monet Econ 56:678–695

    Article  Google Scholar 

  • Story L (2010) SEC cites asset firm in a fraud. The New York Times, New York

    Google Scholar 

  • Wojtowicz M (2014) CDOs and the financial crisis: credit ratings and fair premia. J Bank Finance 39:1–13

    Article  Google Scholar 

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  1. Chair of Banking and Finance, Catholic University of Eichstaett-Ingolstadt, Auf der Schanz 49, 85049, Ingolstadt, Germany

    Thomas Mählmann

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Mählmann, T. Market share and risk taking: the role of collateral asset managers in the collapse of the arbitrage CDO market. Rev Quant Finan Acc 47, 273–303 (2016). https://doi.org/10.1007/s11156-015-0501-9

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