Credit risk with asymmetric information and a switching default threshold

TL;DR

This paper extends structural credit risk models by introducing a dynamic, random default threshold influenced by management decisions, and analyzes how different information levels affect default probability estimation and credit spreads.

Contribution

It develops a generalized model with a stochastic default threshold and derives explicit formulas for default probabilities under various information scenarios.

Findings

Information level significantly influences default probability estimates.

Dynamic thresholds impact credit spread calculations.

Explicit formulas enable better risk assessment.

Abstract

We investigate the impact of available information on the estimation of the default probability within a generalized structural model for credit risk. The traditional structural model where default is triggered when the value of the firm's asset falls below a constant threshold is extended by relaxing the assumption of a constant default threshold. The default threshold at which the firm is liquidated is modeled as a random variable whose value is chosen by the management of the firm and dynamically adjusted to account for changes in the economy or the appointment of a new firm management. Investors on the market have no access to the value of the threshold and only anticipate the distribution of the threshold. We distinguish different information levels on the firm's assets and derive explicit formulas for the conditional default probability given these information levels. Numerical results indicate that the information level has a considerable impact on the estimation of the default probability and the associated credit yield spread.