Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/69427
標題: A new approach to modeling early warning systems for currency crises: Can a machine-learning fuzzy expert system predict the currency crises effectively?
作者: Lin, C.S.
Khan, H.A.
Chang, R.Y.
Wang, Y.C.
關鍵字: Currency crises
Neuro fuzzy
inductive learning
Signal approach
Logit
neural-network models
bankruptcy prediction
speculative attacks
payments crises
discriminant-analysis
financial crises
contagion
balance
indicators
experience
期刊/報告no:: Journal of International Money and Finance, Volume 27, Issue 7, Page(s) 1098-1121.
摘要: This paper presents a hybrid causal model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning ability of the neural network with the inference mechanism of fuzzy logic. The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis. Significantly, the model can also construct a reliable causal relationship among the variables through the obtained knowledge base. Compared to neural network and the traditionally used techniques such as logic, the proposed model can thus lead to a somewhat more prescriptive modeling approach based on determinate causal mechanisms towards finding ways to prevent currency crises. (C) 2008 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/69427
ISSN: 0261-5606
文章連結: http://dx.doi.org/10.1016/j.jimonfin.2008.05.006
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