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A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China

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  • Su, Dongwei
  • He, Xingxing

Abstract

This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning system (EWS) for predicting economic crises. Using quarterly data on 12 macroeconomic and financial variables for the Chinese economy during 1999 and 2008, the paper finds that the hybrid model possesses strong predictive power and the likelihood of economic crises in China during 2009 and 2010 remains high.

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File URL: http://mpra.ub.uni-muenchen.de/19962/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 19962.

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Date of creation: 11 Jan 2010
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Handle: RePEc:pra:mprapa:19962

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Keywords: Computational intelligence; artificial neural networks; fuzzy optimization; early warning system; economic crises;

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  1. Alvarez-Plata, Patricia & Schrooten, Mechthild, 2004. "Misleading indicators? The Argentinean currency crisis," Journal of Policy Modeling, Elsevier, vol. 26(5), pages 587-603, July.
  2. Morris Goldstein & Carmen M. Reinhart, 2000. "Assessing Financial Vulnerability: An Early Warning System for Emerging Markets," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 100.
  3. Bussiere, Matthieu & Fratzscher, Marcel, 2006. "Towards a new early warning system of financial crises," Journal of International Money and Finance, Elsevier, vol. 25(6), pages 953-973, October.
  4. Reinhart, Carmen & Kaminsky, Graciela, 1999. "The twin crises: The causes of banking and balance of payments problems," MPRA Paper 14081, University Library of Munich, Germany.
  5. Peng, Duan & Bajona, Claustre, 2008. "China's vulnerability to currency crisis: A KLR signals approach," China Economic Review, Elsevier, vol. 19(2), pages 138-151, June.
  6. Kaminsky, Graciela & Lizondo, Saul & Reinhart, Carmen M., 1997. "Leading indicators of currency crises," Policy Research Working Paper Series 1852, The World Bank.
  7. Sawischlewski, Katja & Menkhoff, Lukas & Beckmann, Daniela, 2005. "Robust Lessons about Practical Early Warning Systems," Proceedings of the German Development Economics Conference, Kiel 2005 3, Verein für Socialpolitik, Research Committee Development Economics.
  8. Lean Yu & Kin Keung Lai & Shou-Yang Wang, 2006. "Currency Crisis Forecasting With General Regression Neural Networks," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 437-454.
  9. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
  10. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
  11. W. R. M. Perraudin & Manmohan S. Kumar & Uma Moorthy, 2002. "Predicting Emerging Market Currency Crashes," IMF Working Papers 02/7, International Monetary Fund.
  12. Niemira, Michael P. & Saaty, Thomas L., 2004. "An Analytic Network Process model for financial-crisis forecasting," International Journal of Forecasting, Elsevier, vol. 20(4), pages 573-587.
  13. Kalotychou, Elena & Staikouras, Sotiris K., 2006. "An empirical investigation of the loan concentration risk in Latin America," Journal of Multinational Financial Management, Elsevier, vol. 16(4), pages 363-384, October.
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