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Predicting sovereign debt crises using artificial neural networks: A comparative approach

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  • Fioramanti, Marco

Abstract

Recent episodes of financial crisis have revived interest in developing models able to signal their occurrence in timely manner. The literature has developed both parametric and non-parametric models, the so-called Early Warning Systems, to predict these crises. Using data related to sovereign debt crises which occurred in developing countries from 1980 to 2004, this paper shows that further progress can be achieved by applying a less developed non-parametric method based on artificial neural networks (ANN). Thanks to the high flexibility of neural networks and their ability to approximate non-linear relationship, an ANN-based early warning system can, under certain conditions, outperform more consolidated methods.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Financial Stability.

Volume (Year): 4 (2008)
Issue (Month): 2 (June)
Pages: 149-164

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Handle: RePEc:eee:finsta:v:4:y:2008:i:2:p:149-164

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Web page: http://www.elsevier.com/locate/jfstabil

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References

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  1. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
  2. Jeffrey A. Frankel & Andrew K. Rose, 1996. "Currency crashes in emerging markets: an empirical treatment," International Finance Discussion Papers 534, Board of Governors of the Federal Reserve System (U.S.).
  3. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
  4. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
  5. Ciarlone, Alessio & Trebeschi, Giorgio, 2005. "Designing an early warning system for debt crises," Emerging Markets Review, Elsevier, vol. 6(4), pages 376-395, December.
  6. Graciela L. Kaminsky, 2003. "Varieties of Currency Crises," NBER Working Papers 10193, National Bureau of Economic Research, Inc.
  7. Abdul Abiad, 2003. "Early Warning Systems," IMF Working Papers 03/32, International Monetary Fund.
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Citations

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Cited by:
  1. Sarlin, Peter & Peltonen, Tuomas A., 2011. "Mapping the state of financial stability," Working Paper Series 1382, European Central Bank.
  2. Sebastián Nieto Parra, 2008. "Who Saw Sovereign Debt Crises Coming?," OECD Development Centre Working Papers 274, OECD Publishing.
  3. Makram El-Shagi & Gregor von Schweinitz, 2012. "Qual VAR Revisited: Good Forecast, Bad Story," IWH Discussion Papers 12, Halle Institute for Economic Research.
  4. Bandiera, Luca & Cuaresma, Jesus Crespo & Vincelette, Gallina A., 2010. "Unpleasant surprises : sovereign default determinants and prospects," Policy Research Working Paper Series 5401, The World Bank.
  5. Eleftherios Giovanis, 2012. "Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA," Economic Analysis and Policy (EAP), Queensland University of Technology (QUT), School of Economics and Finance, vol. 42(1), pages 79-96, March.
  6. Elgin, Ceyhun & Uras, Burak R., 2013. "Public debt, sovereign default risk and shadow economy," Journal of Financial Stability, Elsevier, vol. 9(4), pages 628-640.
  7. Mioara CHIRITA & Daniela SARPE, 2011. "Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 44-48.
  8. Petr Hájek & Michal Střižík & Pavel Praks & Petr Kadeřábek, 2009. "Possibilities of Financial Crises Forecasting with Latent Semantic Indexing," Politická ekonomie, University of Economics, Prague, vol. 2009(6), pages 754-768.
  9. Ayşe Özmen & Gerhard-Wilhelm Weber & Zehra Çavuşoğlu & Özlem Defterli, 2013. "The new robust conic GPLM method with an application to finance: prediction of credit default," Journal of Global Optimization, Springer, vol. 56(2), pages 233-249, June.
  10. Eleftherios Giovanis, 2010. "Application of logit model and self-organizing maps (SOMs) for the prediction of financial crisis periods in US economy," Journal of Financial Economic Policy, Emerald Group Publishing, vol. 2(2), pages 98-125, June.
  11. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.

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