Multidimensional Distance-To-Collapse Point And Sovereign Default Prediction

Authors:
Roberto Savona;Marika Vezzoli
Affiliations:
University of Brescia, Department of Business Studies, Brescia, Italy;University of Brescia, Department of Quantitative Methods, Brescia, Italy
Venue:
International Journal of Intelligent Systems in Accounting and Finance Management
Year:
2012

Citing 3
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Abstract

By focusing on sovereign defaults, this paper introduces a multidimensional distance-to-collapse point based on a two-step procedure. The first step is nonparametric and provides an early warning system that signals a potential crisis whenever preselected leading indicators exceed specific thresholds. The second is parametric and incorporates the first-step country default predictors within a probit specification. Such a two-step procedure generalizes the distance-to-default à la Merton within a multidimensional setting, wherein we care about the distance of each indicator from its threshold. Empirical evidence about debt crises of emerging markets over the period 1975–2002 proves that our methodology predicts 80% of the total defaults and non-defaults in and out of sample. Copyright © 2012 John Wiley & Sons, Ltd.