The Front Men of Wall Street: The Role of CDO Collateral Managers in the CDO Boom and Bust
Pages: 1893-1936 | Published: 7/2017 | DOI: 10.1111/jofi.12520 | Cited by: 17
SERGEY CHERNENKO
I study the incentives of the collateral managers who selected securities for ABS CDOs—securitizations that figured prominently in the financial crisis. Specialized managers without other businesses that could suffer negative reputational consequences invested in low‐quality securities underwritten by the CDO's arranger. These securities performed significantly worse than observationally similar securities. Managers investing in these securities were rewarded with additional collateral management assignments. Diversified managers who did assemble CDOs suffered negative reputational consequences during the crisis: institutional investors withdrew from their mutual funds. Overall, the results are consistent with a quid pro quo between collateral managers and CDO underwriters.
Pages: 1983-2044 | Published: 7/2017 | DOI: 10.1111/jofi.12525 | Cited by: 87
DARRELL DUFFIE, PIOTR DWORCZAK, HAOXIANG ZHU
We characterize the role of benchmarks in price transparency of over‐the‐counter markets. A benchmark can raise social surplus by increasing the volume of beneficial trade, facilitating more efficient matching between dealers and customers, and reducing search costs. Although the market transparency promoted by benchmarks reduces dealers' profit margins, dealers may nonetheless introduce a benchmark to encourage greater market participation by investors. Low‐cost dealers may also introduce a benchmark to increase their market share relative to high‐cost dealers. We construct a revelation mechanism that maximizes welfare subject to search frictions, and show conditions under which it coincides with announcing the benchmark.
What Drives the Cross‐Section of Credit Spreads?: A Variance Decomposition Approach
Pages: 2045-2072 | Published: 6/2017 | DOI: 10.1111/jofi.12524 | Cited by: 76
YOSHIO NOZAWA
I decompose the variation of credit spreads for corporate bonds into changing expected returns and changing expectation of credit losses. Using a log‐linearized pricing identity and a vector autoregression applied to microlevel data from 1973 to 2011, I find that expected returns contribute to the cross‐sectional variance of credit spreads nearly as much as expected credit loss does. However, most of the time‐series variation in credit spreads for the market portfolio corresponds to risk premiums.