Alessi, L. ; Antunes, A. ; Babecky, J. ; Baltussen, S. ; Behn, M. ; Bonfim, D. Comparing Different Early Warning Systems: Results From a Horse Race Competition Among Members of the Macro-prudential Research Network. 2015 :
Alessi, L. ; Detken, K. Identifying excessive credit growth and leverage. 2018 J. Financ. Stab.. 35 215-225
Alessi, L. ; Detken, K. Quasi real time early warning indicators for costly asset price boom/bust cycles: a role for global liquidity. 2011 Eur. J. Polit. Econ.. 27 520-533
- Apel, M. ; Grimaldi, M.B. ; Hull, I. How much information do monetary policy committees disclose?. 2019 :
Paper not yet in RePEc: Add citation now
Büyükkarabacak, B. ; Valev, N.T. The role of household and business credit in banking crises. 2010 J. Bank. Financ.. 34 1247-1256
Babecký, J. ; Havránek, T. ; MatÄ›ju, J. ; Rusnák, M. ; Å mÃdková, K. ; VaÅ¡ÃÄek, B. Banking, debt and currency crises in developed countries: stylized facts and early warning indicators. 2014 J. Financ. Stab.. 15 1-17
Barrell, R. ; Davis, E.P. ; Karim, D. ; Liadze, L. How idiosyncratic are banking crises in OECD countries?. 2011 Inst. Econ. Rev.. 216 R53-R58
- Barron, A.R. Universal approximation bounds for superpositions of a sigmoidal function. 1993 IEEE Trans. Inf. Theory. 39 930-945
Paper not yet in RePEc: Add citation now
- Basel Committee on Banking Supervision (BCBS), Basel III: a Global Regulatory Framework for More Resilient Banks and Banking Systems — Revised Version. 2011 Bank for International Settlements:
Paper not yet in RePEc: Add citation now
Behn, M. ; Detken, C. ; Peltonen, T. ; Schuedel, W. Setting Countercyclical Capital Buffers Based on Early Warning Models: Would It Work?. 2013 :
Berg, A. ; Pattillo, C. Are currency crises predictable? A test. 1999 IMF Staff Papers. 46 1-
Beutel, J. ; List, S. ; von Schweinitz, G. Does machine learning help us predict banking crises?. 2019 J. Financ. Stab.. 45 -
Binner, J.M. ; Elger, T. ; Nilsson, B. ; Tepper, J.A. Predictable non-linearities in U.S. Inflation. 2006 Econ. Lett.. 93 323-328
- Binner, J.M. ; Elger, T. ; Nilsson, B. ; Tepper, J.A. Tools for non-linear time series forecasting in economics – an empirical comparison of regime switching vector autoregressive models and recurrent neural networks. 2004 Adv. Econometrics. 19 71-91
Paper not yet in RePEc: Add citation now
Bluwstein, K. ; Buckmann, M. ; Joseph, A. ; Kang, M. ; Kapadia, S. ; Simsek, Ö. Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach. 2020 Bank of England Staff Working Paper No. 848. -
Bordo, M.D. ; Meissner, C.M. Does inequality lead to a financial crisis?. 2012 J. Int. Money Finance. 31 2147-2161
Borio, C. The financial cycle and macroeconomics: What have we learnt?. 2014 J. Bank. Financ.. 45 182-198
Borio, C. ; Drehmann, M. Assessing the Risk of Banking Crises – Revisited. 2009 BIS Quarterly Review:
Borio, C. ; Lowe, P. Assessing the Risk of Banking Crises. 2002 BIS Quarterly Review:
Borovkova, S. ; Tsiamas, I. An ensemble of LSTM neural networks for high-frequency stock market classification. 2019 J. Forecast.. 38 600-619
Bussiere, M. ; Fratzscher, M. Towards a new early warning system of financial crises. 2006 J. Int. Money Finance. 25 953-973
Caggiano, G. ; Calice, P. ; Leonida, L. Early warning systems and systemic banking crises in low income countries: a multinomial logit approach. 2014 J. Bank. Financ.. 47 258-269
Caggiano, G. ; Calice, P. ; Leonida, L. ; Kapetanios, G. Comparing logit-based early warning systems: Does the duration of systemic banking crises matter?. 2016 J. Empir. Finance. 37 104-116
- Caprio, G. ; Klingebiel, K. Bank insolvencies: Bad luck, Bad policy, or Bad Banking?. 1997 Annual World, Bank Conference on Development Economics. -
Paper not yet in RePEc: Add citation now
Casabianca, E.J. ; Catalano, M. ; Forni, L. ; Giarda, E. ; Passeri, S. An early warning system for banking crises: from regression-based analysis to machine learning techniques. 2019 Marco Fanno Working Papers 235. -
- Cho, K. ; van Merrienboer, B. ; Gulcehre, C. ; Bahdanau, D. ; Bougares, F. ; Schwenk, H. ; Bengio, Y. Learning phrase representations using RNN encoder-decoder for statistical machine translation. 2014 Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). 1724-1734
Paper not yet in RePEc: Add citation now
Cook, T.R. ; Smalter Hall, A. Macroeconomic indicator forecasting with deep neural networks, Federal reserve Bank of Kansas City. 2017 Research Working Paper 17-11, September. -
- DÃaz-MartÃnez, Z. ; Sánchez-Arellano, A. ; Segovia-Vargas, M. Predicción de crisis financieras mediante conjuntos imprecisos (rough sets) y árboles de decisión. 2011 Innovar. 21 83-100
Paper not yet in RePEc: Add citation now
Davis, E.P. ; Karim, D. Comparing early warning systems for banking crises. 2008 J. Financ. Stab.. 4 89-120
Davis, E.P. ; Liadze, I. Should Multivariate Early Warning Systems for Banking Crises Pool Across Regions?. 2011 Rev. World Econ.. 147 693-716
- DeGroot, M.H. ; Fienberg, S.E. The comparison and evaluation of forecasters. 1983 Statistician. 32 12-22
Paper not yet in RePEc: Add citation now
- DeLong, E. ; DeLong, D. ; Clarke-Pearson, D. Comparing the areas under two or more correlated receiver operating characteristics curves: a nonparametric approach. 1988 Biometrics. 44 837-845
Paper not yet in RePEc: Add citation now
Demirgüc-Kunt, A. ; Detragiache, E. Monitoring banking sector fragility: a multivariate logit approach. 2000 World Bank Econ. Rev.. 14 287-307
Demirgüc-Kunt, A. ; Detragiache, E. The determinants of banking crises in developed countries. 1998 IMF Staff Pap.. 45 81-109
Detken, K. ; Weeken, O. ; Alessi, L. ; Bonfim, D. ; Boucinha, M. ; Castro, C. Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options. 2014 ERSB Occasional Paper Series No. 5 / June 2014. -
Domaç, I. ; Martinez Peria, M.S. Banking crises and exchange rate regimes: is there a link?. 2003 J. Int. Econ.. 61 41-72
Drehmann, M. ; Borio, C. ; Gambacorta, L. ; Jiménez, G. ; Trucharte, C. Countercyclical capital buffers: exploring options. 2010 BIS Working Papers 317. -
Drehmann, M. ; Juselius, M. Evaluating early warning indicators of banking crises: satisfying policy requirements. 2014 Int. J. Forecast.. 30 759-780
Duttagupta, R. ; Cashin, P. Anatomy of banking crises in developing and emerging market countries. 2011 J. Int. Money Finance. 30 354-376
Filardo, A. ; Lombardi, M. ; Raczko, M. Measuring financial cycle time. 2018 BIS Working Papers 755. -
Fioramanti, M. Predicting sovereign debt crises using artificial neural networks: a comparative approach. 2008 J. Financ. Stab.. 4 149-164
- Fischer, T. ; Krauss, C. Deep learning with long-short term memory networks for financial marker predictions. 2018 Eur. J. Oper. Res.. 270 654-669
Paper not yet in RePEc: Add citation now
- Fouliard, J. ; Howell, M. ; Rey, H. Answering the queen: online machine learning and financial crises. 2019 Presentation at the BIS Annual Conference. -
Paper not yet in RePEc: Add citation now
- Fricke, D. Financial Crisis Prediction: A Model Comparison. 2017 :
Paper not yet in RePEc: Add citation now
- Gers, F.A. ; Eck, D. ; Schmidhuber, J. Applying LSTM to time series predictable through time-window approaches. 2001 International Conference on Artificial Neural Networks ICANN 2001. 669-676
Paper not yet in RePEc: Add citation now
- Gers, F.A. ; Schraudolph, N.N. ; Schmidhuber, J. Learning precise timing with LSTM recurrent networks. 2002 J. Mach. Learn. Res.. 3 115-143
Paper not yet in RePEc: Add citation now
Gogas, P. ; Papadimitriou, T. ; Matthaiou, Yield curve and recession forecasting in a machine learning framework. 2014 Comput. Econ.. 45 635-645
- Hansen, L.K. ; Larsen, J. ; Fog, T. Early stop criterion from the bootstrap ensemble. 1997 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing. 4 3205-3208
Paper not yet in RePEc: Add citation now
Hardy, D.C. ; Pazarbasioglu, C. Determinants and leading indicators of banking crises: further evidence. 1999 IMF Staff Paper. 46 1-
- Hochreiter, S. ; Schmidhuber, J. Long short-term memory. 1997 Neural Comput.. 9 1735-1780
Paper not yet in RePEc: Add citation now
Holopainen, M. ; Sarlin, P. Toward robust early-warning models: a horse race, ensembles and model uncertainty. 2017 Quant. Finance. 17 1933-1963
- Hornik, K. Approximation capabilities of multilayer feedforward networks. 1991 Neural Netw.. 4 251-257
Paper not yet in RePEc: Add citation now
- Jordà , Ò. ; Schularick, M. ; Taylor, A.M. Leveraged bubbles. 2015 J. Monet. Econ.. 76 S1-S20
Paper not yet in RePEc: Add citation now
Jordà , Ò. ; Schularick, M. ; Taylor, A.M. Macrofinancial history and the New business cycle facts. 2017 En : . University of Chicago Press: Chicago
Joy, M. ; Rusnák, M. ; Å mÃdková, K. ; VaÅ¡ÃÄek, B. Banking and currency crises: differential diagnostics for developed countries. 2017 Int. J. Financ. Econ.. 22 44-67
Kaminsky, G. ; Reinhart, C. The twin crises: the causes of banking and balance-of-payments problems. 1999 Am. Econ. Rev.. 89 473-500
Kauko, K. External deficits and non-performing loans in the recent financial crisis. 2012 Econ. Lett.. 115 196-199
Kauko, K. How to foresee banking crises? A survey of the empirical literature. 2014 Econ. Syst.. 38 289-308
- Kauko, K. ; Tölö, E. Banking crisis prediction with differenced relative credit. 2020 Appl. Econ. Q.. -
Paper not yet in RePEc: Add citation now
- Kauko, K. ; Tölö, E. On the long-run calibration of the credit-to-GDP gap as a banking crisis predictor. 2020 Finnish Economic Papers. -
Paper not yet in RePEc: Add citation now
Knoll, K. ; Schularick, M. ; Steger, T. No price like home: global house prices 1870-2012. 2016 Am. Econ. Rev.. 107 331-353
- Kuan, C.-H. ; White, H. Artificial neural networks: an econometric perspective. 2007 Econom. Rev.. 13 1-91
Paper not yet in RePEc: Add citation now
Laeven, L. ; Valencia, F. Systemic Banking crises database: an update. 2012 Working Paper No.12/163. -
Lang, J.H. ; Cosimo, I. ; Fahr, S. ; Ruzicka, J. Anticipating the bust: a new cyclical systemic risk inidicator to assess the likelihood and severity of financial crises. 2019 ECB Occasional Paper Series No. 219. -
- Lo Duca, M. ; Peltonen, T. Assessing systemic risks and predicting systemic events. 2013 J. Bank. Financ.. 37 2183-2195
Paper not yet in RePEc: Add citation now
- Lundberg, S.M. ; Lee, S.-I. A unified approach to interpreting model predictions. 2017 Proceedings of the 31st International Conference on Neural Information Processing Systems. 4768-4777
Paper not yet in RePEc: Add citation now
- Manasse, P. ; Roubini, N. “Rules of thumb†for sovereign debt crises. 2009 J. Int. Econ.. 78 192-205
Paper not yet in RePEc: Add citation now
Manasse, P. ; Savona, R. ; Vezzoli, M. Rules of thumb for Banking crises in emerging markets. 2013 Universita’ di Bologna Working Papers No. 872. -
- Minami, S. Predicting equity price with corporate action events using RNN-LSTM. 2018 J. Math. Financ.. 8 58-63
Paper not yet in RePEc: Add citation now
- Niculescu-Mizin, A. ; Caruana, R. Predicting Good probabilities with supervised learning. 2005 ICML 05 Proceedings of the 34th International Conference on Machine Learning. 625-632
Paper not yet in RePEc: Add citation now
- Nik, P. ; Jusoh, M. ; Shaari, A.H. ; Sarmdi, T. . 2016 J. Econ. Cooperation Dev.. 37 25-40
Paper not yet in RePEc: Add citation now
Nyman, R. ; Ormerod, P. Predicting Economic Recessions Using Machine Learning Algorithms. 2017 :
- Olah, C. Understanding LSTM Networks. 2015 :
Paper not yet in RePEc: Add citation now
Qi, M. Predicting US recessions with leading indicators via neural network models. 2001 Int. J. Forecast.. 17 383-401
Reinhart, C.M. ; Rogoff, K.S. This Time Is Different: Eight Centuries of Financial Folly. 2009 Princeton University Press:
Ristolainen, K. Predicting banking crises with artificial neural networks: the role of Nonlinearity and heterogeneity. 2018 Scand. J. Econ.. 120 31-62
Roy, S. ; Kemme, D.M. Causes of banking crises: deregulation, credit booms and asset bubbles, then and now. 2012 Int. Rev. Econ. Financ.. 24 270-294
- Sarlin, P. Mapping financial stability. 2014 Ai Commun.. 27 285-297
Paper not yet in RePEc: Add citation now
Schularick, M. ; Taylor, A.M. Credit booms gone bust: monetary policy, leverage cycles and financial crises, 1870-2008. 2012 Am. Econ. Rev.. 102 1029-1061
- Shapley, L.S. A value for n-person games. 1953 Contributions to the Theory of Games. 2 307-317
Paper not yet in RePEc: Add citation now
- Siami-Namini, S. ; Tavakoli, N. ; Namin, A.S. A comparison of ARIMA and LSTM in forecasting time series. 2018 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). 1394-1401
Paper not yet in RePEc: Add citation now
Suss, J. ; Treitel, H. Predicting bank distress in the UK with machine learning. 2019 Bank of England Staff Working Paper No. 831. -
Tölö, E. ; Laakkonen, H. ; Kalatie, S. Evaluating Indicator for use in setting the countercyclical capital buffer. 2018 Int. J. Cent. Bank.. 14 51-111
von Hagen, J. ; Ho, T.-K. Money market pressure and the determinants of banking crises. 2007 J. Money Credit Bank.. 39 1037-1066
- Wu, Y. ; Schuster, M. ; Chen, Z. ; Le, Q.V. ; Norouzi, M. ; Macherey, W. ; Krikun, M. ; Cao, Y. ; Gao, Q. ; Macherey, K. ; Klingner, J. ; Shah, A. ; Johnson, M. ; Liu, X. ; Kaiser, Å. ; Gouws, S. ; Kato, Y. ; Kudo, T. ; Kazawa, H. ; Stevens, K. ; Kurian, G. ; Patil, N. ; Wang, W. ; Young, C. ; Smith, J. ; Riesa, J. ; Rudnick, A. ; Vinyals, O. ; Corrado, G. ; Hughes, M. ; Dean, J. Google’s Neural Machine Translation System: Bridging the Gap Between Human and Machine Translation. 2016 :
Paper not yet in RePEc: Add citation now