Predicting stock price performance: a neural network approach

The prediction of stock price performance is a difficult and complex problem. Multivariate analytical techniques using both quantitative and qualitative variables have repeatedly been used to help form the basis of investor stock price expectations and, hence, influence investment decision making. However, the performance of multivariate analytical techniques is often less than conclusive and needs to be improved to more accurately forecast stock price performance. A neural network method has demonstrated its capability of addressing complex problems. A neural network method may be able to enhance an investor's forecasting ability. The purpose of this paper is to examine the capability of a neural network method and compares its predictive power with that of multiple discriminant analysis methods.<<ETX>>

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