Based on original papers which represent new and significant research, developments and applications in finance and investment. The author takes a pragmatic view of neural networks, treating them as computationally equivalent to well-understood, non-parametric inference methods in decision science. The author also makes comparisons with established techniques where appropriate.
This book take you to a nice and different approach to how neural networks build their solutions for time series problems. There is a nice good explanation about applying this tool for real problems in financial world. IMHO, this is one of the bibles of neural networks in this days.
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