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This paper analyzes the risk properties of typical asset-backed securities (ABS), like CDOs or MBS, relying on a model with both macroeconomic and idiosyncratic components. The examined properties include expected loss, loss given default, and macro factor dependencies. Using a two-dimensional loss decomposition as a new metric, the risk properties of individual ABS tranches can directly be compared to those of corporate bonds, within and across rating classes. By applying Monte Carlo Simulation, we find that the risk properties of ABS differ significantly and systematically from those of straight bonds with the same rating. In particular, loss given default, the sensitivities to macroeconomic risk, and model risk differ greatly between instruments. Our findings have implications for understanding the credit crisis and for policy making. On an economic level, our analysis suggests a new explanation for the observed rating inflation in structured finance markets during the pre-crisis period 2004-2007. On a policy level, our findings call for a termination of the 'one-size-fits-all' approach to the rating methodology for fixed income instruments, requiring an own rating methodology for structured finance instruments. JEL Classification: G21, G28
This paper analyzes the risk properties of typical asset-backed securities (ABS), like CDOs or MBS, relying on a model with both macroeconomic and idiosyncratic components. The examined properties include expected loss, loss given default, and macro factor dependencies. Using a two-dimensional loss decomposition as a new metric, the risk properties of individual ABS tranches can directly be compared to those of corporate bonds, within and across rating classes. By applying Monte Carlo Simulation, we find that the risk properties of ABS differ significantly and systematically from those of straight bonds with the same rating. In particular, loss given default, the sensitivities to macroeconomic risk, and model risk differ greatly between instruments. Our findings have implications for understanding the credit crisis and for policy making. On an economic level, our analysis suggests a new explanation for the observed rating inflation in structured finance markets during the pre-crisis period 2004-2007. On a policy level, our findings call for a termination of the 'one-size-fits-all' approach to the rating methodology for fixed income instruments, requiring an own rating methodology for structured finance instruments. JEL Classification: G21, G28 Keywords: credit risk, risk transfer, systematic risk
Risk transfer with CDOs
(2008)
Modern bank management comprises both classical lending business and transfer of asset risk to capital markets through securitization. Sound knowledge of the risks involved in securitization transactions is a prerequisite for solid risk management. This paper aims to resolve a part of the opaqueness surrounding credit-risk allocation to tranches that represent claims of different seniority on a reference portfolio. In particular, this paper analyzes the allocation of credit risk to different tranches of a CDO transaction when the underlying asset returns are driven by a common macro factor and an idiosyncratic component. Junior and senior tranches are found to be nearly orthogonal, motivating a search for the where about of systematic risk in CDO transactions. We propose a metric for capturing the allocation of systematic risk to tranches. First, in contrast to a widely-held claim, we show that (extreme) tail risk in standard CDO transactions is held by all tranches. While junior tranches take on all types of systematic risk, senior tranches take on almost no non-tail risk. This is in stark contrast to an untranched bond portfolio of the same rating quality, which on average suffers substantial losses for all realizations of the macro factor. Second, given tranching, a shock to the risk of the underlying asset portfolio (e.g. a rise in asset correlation or in mean portfolio loss) has the strongest impact, in relative terms, on the exposure of senior tranche CDO-investors. Our findings can be used to explain major stylized facts observed in credit markets.