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Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach · Study

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PreprintPredicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach

Marco Fioramanti2006

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Preprintgreen2006

Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach

Marco Fioramanti

25 citations·0/0 files stored·SSRN Electronic Journal

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Global Financial Crisis and Policies Forecasting Techniques and Applications Financial Distress and Bankruptcy Prediction

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References

1996Currency crashes in emerging markets: An empirical treatment 1998Leading Indicators of Currency Crises 1999Balance Sheets, the Transfer Problem, and Financial Crises 1999Leading Indicators of Currency Crises 2007Debt Defaults and Lessons from a Decade of Crises 2003Predicting Sovereign Debt Crises 2001Crises and Liquidity 2004Assessing Early Warning Systems

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2011Mapping the State of Financial Stability 2015Toward Robust Early-Warning Models: A Horse Race, Ensembles and Model Uncertainty

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2012MULTIDIMENSIONAL DISTANCE‐TO‐COLLAPSE POINT AND SOVEREIGN DEFAULT PREDICTIONarticle · 9 shared references 2008Predicting sovereign debt crises using artificial neural networks: A comparative approacharticle · 8 shared references 2015Toward Robust Early-Warning Models: A Horse Race, Ensembles and Model Uncertaintypreprint · 7 shared references 2007Dating currency crises with ad hoc and extreme value‐based thresholds: East Asia 1970–2002 [Dating currency crises]article · 7 shared references 2019Early Warning Systems for Currency Crises with Real-Time Dataarticle · 7 shared references 2015Toward Robust Early-Warning Models: A Horse Race, Ensembles and Model Uncertaintypreprint · 7 shared references

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Year2006

Typepreprint

Published2006-01-01

VenueSSRN Electronic Journal

ISSN-L1556-5068

Languageen

Citations25

Files0 public / 0

ShelfGlobal Financial Crisis and Policies

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doi10.2139/ssrn.935107

openalex_workW2060027745

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