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7444
Application of Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA
Abstract:
In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.
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References:

[1] A. Demirguc-kunt and E. Detragiache, "The Determinants of Banking Crises in Developing and Developed Countries", IMF Staff Papers, Vol. 45, No. 1, pp. 81-109, 1998
[2] B. Eichengreen and A.K. Rose, "Staying Afloat When the Wind Shifts: External Factors and Emerging-Market Banking Crises", NBER Working Papers 6370, National Bureau of Economic Research, Cambridge, MA, 1998
[3] J. Frankel and A.K. Rose, "Currency Crashes in emerging Markets: An Empirical Treatment", International Finance Discussion Papers 534, Board of Governors of the Federal Reserve System, Washington. D.C, 1996
[4] R. Glick and A.K. Rose, "Contagion and trade: Why currency crises are regional?", NBER Working Papers 6806, National Bureau of Economic Research, Cambridge, MA, 1998
[5] R. Glick and A.K. Rose, "Money and Credit, Competitiveness and Currency Crises in Asia and Latin America", Center for Pacific Basin Money and economic Studies, Federal Reserve Bank of San Francisco papers BP99-01,1999
[6] L.G. Kaminsky and C.M. Reinhart, "The Twin Crises: The Causes of Banking and Balance of Payments Problems", Federal Reserve Board Discussion Papers 544. Board of Governors of the Federal Reserve System.Washington. D.C., 1996
[7] L.G. Kaminsky and C.M. Reinhart, "Leading Indicators of Currency Crises", IMF Staff Papers, Vol. 45, No. 1, pp. 1-48, 1998
[8] L. Salchenberger, E. Cinar N. and Lash, "Neural networks: A new tool for predicting thrift failures", Decision Sciences, Vol. 23, pp. 899-916, 1992
[9] P.K. Coats and F.L. Fant, "Recognizing financial distress patterns using a neural network tool", Financial Management, Vol. 22, pp. 142-155, 1993
[10] G. Zhang, Y. Hu and E.B. Patuwo, "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis", European Journal of Operation Research, Vol. 116, pp. 16- 32, 1999
[11] P.L Brockett, L.L. Golden, J. Jang, and C. Yang, "A comparison of neural network, statistical methods and variable choice for life insurers- financial distress prediction", Journal of Risk and Insurance, Vol. 73, No. 3, pp. 397-419, 2006
[12] E. Giovanis, "Application of Logit Model and Self-Organizing Maps (SOM) for the prediction of Financial Crisis Periods in US Economy", Journal of Financial Economic Policy, Vol. 2, No. 2, pp. 98-125, 2010
[13] H. Ni and H. Yin, "Exchange rate prediction using hybrid neural networks and trading indicators", Neurocomputing, Vol. 72, No. 13-15, pp. 2815-2823, 2009
[14] W.H. Greene, Econometric Analysis, Sixth Edition, Prentice Hall: New Jersey, 2008, pp. 666-668
[15] J.-S.R. Jang, "ANFIS: Adaptive-Network-based Fuzzy Inference Systems," IEEE Trans. on Systems, Man, and Cybernetics, Vol. 23, No. 3, pp. 665-685, 1993
[16] J.-S. R. Jang and C.-T. Sun, "Neuro-fuzzy Modeling and Control," Proceedings of the IEEE, Vol. No. 83, No. 3, 378-406, March, 1995
[17] L. Khan, S. Anjum and R. Bada, "Standard Fuzzy Model Identification using Gradient Methods," World Applied Sciences Journal, Vol. 8, No. 1, pp. 01-09, 2010
[18] M.A. Denai, F. Palis and A. Zeghbib, ANFIS Based Modelling and Control of Non-Linear systems: A Tutorial, IEEE Conf. on Systems, Man, and Cybernetics, Vol. 4, pp. 3433-3438, 2004
[19] L.H. Tsoukalas, and R.E. Uhrig, Fuzzy and Neural Approaches in Engineering, First Edition, John Wiley & Sons, 1997, pp. 445-470.
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