Abstract:
This paper improves stock market prediction based on genetic algorithms (GA) and wavelet neural networks (WNN) and reports significantly better accuracies compared to exi...Show MoreMetadata
Abstract:
This paper improves stock market prediction based on genetic algorithms (GA) and wavelet neural networks (WNN) and reports significantly better accuracies compared to existing approaches to stock market prediction, including the hierarchical GA (HGA) WNN. Specifically, we added information such as trading volume as inputs and we used the Morlet wavelet function instead of Morlet-Gaussian wavelet function in our prediction model. We also employed a smaller number of hidden nodes in WNN compared to other research work. The prediction system is tested using Shenzhen Composite Index data.
Date of Conference: 06-11 July 2014
Date Added to IEEE Xplore: 04 September 2014
ISBN Information: