Robustness of Distance-to-Default

Cathrine Jessen, David Lando

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publication26th Australasian Finance & Banking Conference 2013
EditorsFariborz Moshirian
Number of pages25
Place of PublicationSydney
PublisherUNSW Australia Business School
Publication date2013
ISBN (Print)9780987312754
Publication statusPublished - 2013
EventThe 26th Australasian Finance and Banking Conference 2013 - Shangri-la Hotel, Sydney, Australia
Duration: 17 Dec 201319 Dec 2013
Conference number: 26


ConferenceThe 26th Australasian Finance and Banking Conference 2013
LocationShangri-la Hotel
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