SYSTEMIC CREDIT RISK:WHAT IS THE MARKET TELLING US?Vineer Bhansali∗Robert Gingrich∗Francis A. Longstaff∗∗Abstract. The ongoing subprime crisis raises many concerns about the possibilityof much broader credit shocks in the economy. We use a simple linear version of theLongstaff and Rajan (2007) model to extract the information about macroeconomiccredit risk embedded in the prices of tranches on the most-liquid credit indexes. Threetypes of credit risk appear to be priced by the market: idiosyncratic risks at the level ofindividual firms, sectorwide risk at the level of correlated firms within the same industrygroup, and economywide or systemic risk. We apply the model to the recent behavior oftranches in the U.S. and European credit derivatives markets and show that the currentcredit crisis has more than twice the systemic risk of the May 2005 auto-downgradecredit crisis.Current version: March 2008.∗PIMCO, 840 Newport Center Drive, Newport Beach, CA 92660.∗∗UCLA AndersonSchool and NBER, 110 Westwood Plaza, Los Angeles, CA 90095-1481.The dramatic meltdown in the subprime market during the past year has raised manyred flags among market participants about their potential exposure to broader systemiccredit shocks. These heightened concerns have resulted in dramatic declines in marketliquidity, restricted access to credit, flights to quality, sharply increased market volatility,and larger risk premia in many financial markets. As a result, the prices of the mostcredit-sensitive securities in the market may actually play the role of the “canary in thecoal mine” in providing information about how market participants collectively assessthe risk of systemic or macroeconomic credit shocks.In this paper, we use the prices of indexed credit derivatives to extract marketexpectations about the nature and magnitude of the credit risks facing financial mar-kets. Since their inception in 2002, indexed credit derivatives markets have explodedin size and participation. Broad indexes are now traded for U.S. (CDX) and European(ITRAXX) credit markets with usually very deep liquidity, and to a lesser degree forJapanese and U.K. credit markets. As of the end of 2007, the investment grade indexwas in its ninth generation, and its European counterpart was in its eight generation.What has been even more striking than the success of the indexes, however, is the launchand success of tranches on the indexes. Tranches can be best thought of as call spreadson the credit losses of a portfolio. Investors can use tranches to control their exposureto particular loss thresholds.To extract the information from these credit derivatives, we first develop a simplelinearized version of the collateralized debt obligation (CDO) pricing model of Longstaffand Rajan (2007). Longstaff and Rajan propose a three-jump model that is calibratedto the traded spreads of tranches and indexes directly. Their model allows for thepossibility that credit spreads might be a composite of several different types of creditrisk. Specifically, they find that the credit loss distribution embedded in index trancheprices includes a component for the risk of idiosyncratic or firm-specific defaults, acomponent for the risk of broader sectorwide or industrywide defaults, and a componentfor the risk of a massive economywide default scenario. We then fit the linearized versionof the model to the market prices of the credit indexes and tranches. Their results arealso consistent with the CDO modeling framework of Duffie and Gˆarleanu (2001).The results have many important implications. Using current data for both invest-ment-grade and high-yield indexes as well as for longer tenors, we likewise find thatthe market anticipates three different types of credit risks: idiosyncratic credit events,broader sectorwide credit events, and economywide credit events. What is particularlystriking, however, is that the nature of systemic credit risk appears to have changeddramatically over time. In particular, systemic credit risk was only a small percentageof total credit risk during the auto-downgrade credit crisis of May 2005. In the recentsubprime crisis, however, systemic credit risk has ballooned and now approximates thesize of the idiosyncratic component of credit spreads.1These results argue that the current credit crisis differs in fundamental ways fromprevious credit events. An important implication of this is that credit risk premia infinancial markets may remain at high levels going forward, leading to a significantlyhigher cost of debt capital for many firms and sectors. Furthermore, this shifting trendin the nature of credit risk implies that traditional risk management strategies such asportfolio diversification may be less effective in controlling credit risk exposure.Another key implication is that some of credit modeling tools that are widely usedin practice may severely underestimate the actual risk exposure of credit portfolios. Forexample, during the May 2005 auto-downgrade crisis, many investors held positions inwhich the 0-3% equity tranche was hedged with the 3-7% tranche based on the industry-standard Gaussian copula model. These trades performed completely differently thanexpected. The reason for this risk-management failure can ultimately be traced to a lackof liquidity and understanding by participants of the source of macro risks embedded inthe tranches. Specifically, the behavior of index tranches to idiosyncratic and systemicrisks varies significantly across their attachment and detachment points. Thus, while theGaussian copula model can be applied to individual tranches, one correlation number isnot sufficient to capture the risks of all tranches. At best, the implied base correlation ofthe copula model reflects the average correlation of the underlying equities, and hence,the correlation for the most junior or equity tranche (see Bhansali (2007)). Due to thelack of data on correlation during systemic defaults, it is difficult to extrapolate thetails to the higher senior part of the capital structure. Thus, using the copula model asa risk-management tool is fraught with dangers.This paper is organized as follows. Section 1 presents the linearized CDO pricingmodel. Section 2 discusses the data and the methodology. Section 3 presents the resultsand discusses their implications for financial markets. Section 4 summarizes the resultsand makes concluding remarks.1. The Linearized Three-Jump