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Fitting and Forecasting Sovereign Defaults Using Multiple Risk Signals

  • Roberto Savona

    ()

    (Department of Business Studies, University Of Brescia)

  • Marika Vezzoli

    (Department of Quantitative Methods, University Of Brescia)

In this paper we face the fitting versus forecasting paradox with the objective of realizing an optimal Early Warning System to better describe and predict past and future sovereign defaults. We do this by proposing a new Regression Tree-based model that signals a potential crisis whenever preselected indicators exceed specific thresholds. Using data on 66 emerging markets over the period 1975-2002, our model provides an accurate description of past data, although not the best description relative to existing competing models (Logit, Stepwise logit, Noise-to-Signal Ratio and Regression Trees), and produces the best forecasts accomodating to different risk aversion targets. By modulating in- and out-of sample model accuracy, our methodology leads to unambiguous empirical results, since we find that illiquidity (short-term debt to reserves ratio), insolvency (reserve growth) and contagion risks act as the main determinants/predictors of past/future debt crises.

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File URL: http://www.unive.it/media/allegato/DIP/Economia/Working_papers/Working_papers_2012/WP_DSE_savona_vezzoli_26_12.pdf
File Function: First version, 2012
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Paper provided by Department of Economics, University of Venice "Ca' Foscari" in its series Working Papers with number 2012_26.

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Length: 59
Date of creation: 2012
Date of revision:
Handle: RePEc:ven:wpaper:2012_26
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