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Building a Credit Risk Valuation Framework for Loan Instruments

by Scott Aguais of Algorithmics LLP,
Larry Forest  of Algorithmics LLP, and
Dan Rosen of Algorithmics LLP

December 2000

Abstract: We present a general option-valuation framework for loans that provides valuation information at loan origination and supports mark-to-market analysis, portfolio credit risk and asset and liability management for the entire portfolio. We describe, in detail, the main structures found in commercial loans and the practical assumptions required to model the state-contingent cash flows resulting from these structures. The characteristics of the credit risk model necessary to capture the main features of the problem are described. Finally, we discuss the families of credit models appropriate for pricing, the data required for their calibration and reasonable criteria for choosing the sophistication of the model. We propose a multi-state, ratings-based credit model with three credit drivers: the credit state of the obligor, the level of risk-free rates and the spreads. Though we focus primarily on large corporate and middle-market loans, the approach is applicable more generally to bonds and credit derivatives.

Published in: Algo Research Quarterly, Vol. 3, No. 3, (December 2000), pp. 21-46.

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