Ten lectures on wavelets
Neural Networks
An introduction to wavelets
The nature of statistical learning theory
The nature of statistical learning theory
Neural network models for time series forecasts
Management Science
Applied Wavelet Analysis with S-Plus
Applied Wavelet Analysis with S-Plus
Kernel partial least squares regression in reproducing kernel hilbert space
The Journal of Machine Learning Research
Overview and recent advances in partial least squares
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Multi-agent modeling of multiple FX-markets by neural networks
IEEE Transactions on Neural Networks
Chaos-based support vector regressions for exchange rate forecasting
Expert Systems with Applications: An International Journal
Using Gaussian process based kernel classifiers for credit rating forecasting
Expert Systems with Applications: An International Journal
Forecasting stock indices with wavelet domain kernel partial least square regressions
Applied Soft Computing
A sparse kernel algorithm for online time series data prediction
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
This study implements a novel expert system for financial forecasting. In the first stage, wavelet analysis transforms the input space of raw data to a time-scale feature space suitable for financial forecasting, and then a Recurrent Self-Organizing Map (RSOM) algorithm is used for partitioning and storing temporal context of the feature space. In the second stage, multiple kernel partial least square regressors (as local models) that best fit partitioned regions are constructed for final forecasting. Compared with neural networks, pure SVMs or traditional GARCH models, the proposed model performs best. The root-mean-squared forecasting errors are significantly reduced.