Abstract
This work presents an integrated approach for modelling the behaviour of financial markets with Artificial Neural Networks (ANNs). The model allows to forecast financial time series. Its originality lies in the fact that it is based on statistics and macroeconomics principles and it integrates fundamental economic knowledge in a multivariate nonlinear time series ANN model. The model is applied to real-life case studies and the results are discussed.
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© 1995 Springer-Verlag/Wien
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Ankenbrand, T., Tomassini, M. (1995). Multivariate Time Series Modelling of Financial Markets with Artificial Neural Networks. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_68
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_68
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
eBook Packages: Springer Book Archive