Robustness of Distance-to-Default

25 Pages Posted: 17 Aug 2013

See all articles by Cathrine Jessen

Cathrine Jessen

Copenhagen Business School - Department of Finance

David Lando

Copenhagen Business School

Date Written: August 16, 2013

Abstract

Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.

Keywords: Default risk, default prediction, distance-to-default, stochastic volatility

JEL Classification: G12, G32, G33

Suggested Citation

Jessen, Cathrine and Lando, David, Robustness of Distance-to-Default (August 16, 2013). 26th Australasian Finance and Banking Conference 2013. Available at SSRN: https://ssrn.com/abstract=2311228 or http://dx.doi.org/10.2139/ssrn.2311228

Cathrine Jessen (Contact Author)

Copenhagen Business School - Department of Finance ( email )

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark

David Lando

Copenhagen Business School ( email )

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark
+45 3815 3600 (Fax)

Register to save articles to
your library

Register

Paper statistics

Downloads
295
Abstract Views
1,220
rank
103,384
PlumX Metrics