article

Multidimensional Distance-To-Collapse Point And Sovereign Default Prediction

Authors:

Roberto Savona,

Marika VezzoliAuthors Info & Claims

International Journal of Intelligent Systems in Accounting and Finance Management, Volume 19, Issue 4

Pages 205 - 228

https://doi.org/10.1002/isaf.1332

Published: 01 October 2012 Publication History

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.

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Cited By

Figini SSavona RVezzoli M(2018)Corporate Default Prediction Model AveragingInternational Journal of Intelligent Systems in Accounting and Finance Management10.5555/3074517.307452023:1-2(6-20)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/3074517.3074520
Lahmiri S(2017)A two-step system for direct bank telemarketing outcome classificationInternational Journal of Intelligent Systems in Accounting and Finance Management10.1002/isaf.140324:1(49-55)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1002/isaf.1403
Lahmiri S(2016)Features selection, data mining and finacial risk classificationInternational Journal of Intelligent Systems in Accounting and Finance Management10.1002/isaf.139523:4(265-275)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1002/isaf.1395

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cover image International Journal of Intelligent Systems in Accounting and Finance Management

International Journal of Intelligent Systems in Accounting and Finance Management Volume 19, Issue 4

October 2012

69 pages

ISSN:1055-615X

EISSN:2160-0074

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John Wiley and Sons Ltd.

United Kingdom

Publication History

Published: 01 October 2012

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Cited By

Figini SSavona RVezzoli M(2018)Corporate Default Prediction Model AveragingInternational Journal of Intelligent Systems in Accounting and Finance Management10.5555/3074517.307452023:1-2(6-20)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/3074517.3074520
Lahmiri S(2017)A two-step system for direct bank telemarketing outcome classificationInternational Journal of Intelligent Systems in Accounting and Finance Management10.1002/isaf.140324:1(49-55)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1002/isaf.1403
Lahmiri S(2016)Features selection, data mining and finacial risk classificationInternational Journal of Intelligent Systems in Accounting and Finance Management10.1002/isaf.139523:4(265-275)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1002/isaf.1395

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