Calibrating Structural Models: A New Methodology Based on Stock and Credit Default Swap Data

Abstract

This paper presents a modified version of Leland and Toft’s (1996) structural credit risk model, together with a novel calibration methodology based on stock and CDS data: the firm asset value and volatility are consistently derived from equity prices; the default barrier is calibrated from CDS premia. It empirically shows that as long as the appropriate default barrier is selected, the model generates time series of stock market implied credit spreads which fit the times series of CDS spreads. Moreover, CDS implied default barriers prove to be consistent with stockholders’ rationality, with predictions made by structural models with endogenous default, and with historical recovery rates.

Keywords: Structural credit risk models, Calibration, Default barrier

JEL Classification: G12