Finance Project

The collateral debt obligations (CDO) modeling framework with static spread term structures and employing copula functions is taking hold in the accounting of synthetic CDO trading profit and loss (P&L). This has been spurred by tranches on standardized credit indexes (e.g., CDX.NA.IG, CDX.NA.HY, ITRAXX Eur, etc.) that have provided a calibration target for pricing models. There are ongoing discussions on different ways of fitting prices across the capital structure (e.g., “compound correlation,” versus “base correlation”).

Less understood are hedging strategies and their cost and effectiveness, and the basic risk-reward profiles of popular CDO trading strategies and the associated capitalization needs for banks. The two main reasons for this state of affairs are:
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Univariate pricing is a key component to the pricing of structured credit vehicles. To date, credit is still very much an incomplete market. In addition, it is usually difficult to use a simple diffusion setup to model its dynamic, as default risk is usually perceived as an unexpected event, i.e., a jump. An incomplete market and the presence of jumps make the credit space a difficult market, where it is not always easy to derive prices from the cost of related replicating (hedging) strategies/portfolios.

Due to these characteristics, market participants have been trying hard to make the most of two alternatives:
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