Neural computation and self-organizing maps: an introduction
Neural computation and self-organizing maps: an introduction
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Analyzing currency crises' real effects with partial least squares sensitivity analysis
Intelligent Data Analysis
SVM sensitivity analysis: an application to currency crises aftermaths
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Empirical Analysis Of Speculative Attacks With Contractionary Real Effects
International Journal of Intelligent Systems in Accounting and Finance Management
Decomposing the global financial crisis: A Self-Organizing Time Map
Pattern Recognition Letters
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In some cases, currency crises are followed by strong recessions (e.g., recent Asian and Argentinean crises), but in other cases they are not. This paper uses Self-Organizing Maps (SOM) to search for meaningful associations between speculative attacks' real effects and 28 variables that characterize the economic, financial, legal, and socio-political structure of the country at the onset of the attack. SOM is a neural network-based generalization of Principal Component Analysis (PCA) that provides an efficient non-linear projection of the multidimensional data space on a curved surface. This paper finds a strong association of speculative attacks` real effects with fundamentals and the banking sector structure.