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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In recent years, the market for collateral debt obligations (CDOs) and, in particular, the development of the synthetic CDO market and correlation trading has resulted in significant developments in valuation and risk management for such products. The market has been dominated by developments around the static Gaussian copula model, the introduction of base correlation as an alternative to the compound correlation, and extensions to better capture the observed correlation smile/skew, only recently more dynamic models that incorporate credit spreads or other major modeling parameters have been introduced by practitioners and academics.

All valuation approaches are based on risk-neutral pricing principles and little focus has been given to replication-based arguments that would also lead to developments for practical hedging and risk management. Currently, risk management often focuses on static risk measures that address the likelihood of a CDO investor receiving full notional and actual interest in a timely manner (ratings perspective), or on mark-to-market (MtM) sensitivities and “the greeks” frequently employed by correlation investors and traders.
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