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Elements in the Design of an Early Warning System for Sovereign Default

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  • Ana-Maria Fuertes
  • Elena Kalotychou

Abstract

This paper utilizes two different classification techniques to explore issues in the development of an early warning system for sovereign default. Specifically, the paper develops K-means clustering and logit models to illustrate how the optimal choice of parameters, such as assignment rule of fitted observations to binary groups depend on the decision-makers' preferences. It proposes optimization approaches to tailor these parameters to the decision-maker's loss-function and degree of risk-aversion towards unpredicted defaults. The paper also investigates the potential benefits of combining the optimal forecasts from three methods: logit based on objective macroeconomic variables, logit based on judgmental bankers' credit ratings and non-parametric K-means clustering using both objective and judgmental variables. Unlike continuous-variable forecasts, combining forecasts of discrete-variables requires different techniques based on logit regression or voting rules. In this context, the benefit from combination is not as clear-cut, since the expected loss is not directly related to the error variance. We find that the forecast combining approach can also be chosen optimally to account for the decision-makers' loss-function and risk-aversion

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 231.

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Date of creation: 11 Aug 2004
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Handle: RePEc:sce:scecf4:231

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Related research

Keywords: Early warning systems; financial crises; classification techniques; forecast combination;

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References

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Cited by:
  1. Kalotychou, Elena & Staikouras, Sotiris K., 2006. "An empirical investigation of the loan concentration risk in Latin America," Journal of Multinational Financial Management, Elsevier, vol. 16(4), pages 363-384, October.
  2. Thangjam Rajeshwar Singh, 2011. "An ordered probit model of an early warning system for predicting financial crisis in India," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 185-201 Bank for International Settlements.

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