C++ Neural Networks and Fuzzy Logic: Preface

C++ Neural Networks and Fuzzy Logic

by Valluru B. Rao

MTBooks, IDG Books Worldwide, Inc.

ISBN: 1558515526   Pub Date: 06/01/95

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You can set up a similar function for x(t + h), the stock price at time t + h, and have a separate network

computing it using the backpropagation paradigm. You will then be generating future prices of the stock and

the future buy/sell signals hand in hand, but parallel.

Michitaka Kosaka, et al. (1991) report that they used time−series data over five years to identify the network

model, and time−series data over one year to evaluate the model’s forecasting performance, with a success

rate of 65% for turning points.