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Structural Versus Reduced Form Models: A New Information Based Perspective

by Robert A. Jarrow of Cornell University, and
Philip Protter of Cornell University

May 2004

Abstract: This paper compares structural versus reduced form credit risk models from an information based perspective. We show that the difference between these two model types can be characterized in terms of the information assumed known by the modeler. Structural models assume that the modeler has the same information set as the firm's manager--complete knowledge of all the firm's assets and liabilities. In most situations, this knowledge leads to a predictable default time. In contrast, reduced form models assume that the modeler has the same information set as the market--incomplete knowledge of the firm's condition. In most cases, this imperfect knowledge leads to an inaccessible default time. As such, we argue that the key distinction between structural and reduced form models is not whether the default time is predictable or inaccessible, but whether the information set is observed by the market or not. Consequently, for pricing and hedging, reduced form models are the preferred methodology.

Published in: Journal of Investment Management, Vol. 2, No. 2, (May 2004), pp. 1-10.

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