Finance Project

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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The analysis of credit risk in a portfolio requires measures of dependency across assets. Individual spreads in the pricing world, probabilities of default (PDs) and loss-given-default in the risk universe, management world, are important but insufficient to determine the price/risk of multiname products and their entire distribution of losses.

Because the diversification effects are related to dependency, neither the price of a portfolio can be defined as a linear combination of the price of its underlying components, nor its loss distribution can be the sum of the distributions of individual losses.
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