Abstract
This paper discusses the feasibility of using the support vector machine (SVM) to build empirical models of currency crises. The main idea is to develop an estimation algorithm, by training a model on a data set, which provide reasonably accurate model outputs. The proposed approach is illustrated to model currency crises in Venezuela.
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Rocco, C.M., Moreno, J.A. (2004). A Support Vector Machine Model for Currency Crises Discrimination. In: Chen, SH., Wang, P.P. (eds) Computational Intelligence in Economics and Finance. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06373-6_6
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DOI: https://doi.org/10.1007/978-3-662-06373-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07902-3
Online ISBN: 978-3-662-06373-6
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