Title :
Online Time Series Forecasting Based on Biorthogonal Wavelet Kernel Support Vector Machine
Author :
Chao, Huang ; Li-li, Huang ; Hong-yan, Jiang ; Wei-jun, Zhong
Author_Institution :
Sch. of Econ. & Manage., Southeast Univ., Nanjing, China
Abstract :
As a Special wavelet, biorthogonal wavelet has many advantages in signal processing. This paper constructs a new biorthogonal wavelet based on CDF method and constructs the biorthogonal wavelet kernel function. Then we study the update of incremental model and propose online forecasting algorithm. We research the algorithm based on biorthogonal wavelet kernel support vector machine (SVM) and use this algorithm to forecast the Chinese Csi 300 stock index futures at last. The experiment result shows the algorithm has ideal prediction effect.
Keywords :
financial data processing; forecasting theory; stock markets; support vector machines; time series; wavelet transforms; CDF method; Chinese Csi 300 stock index futures; SVM; biorthogonal wavelet kernel function; biorthogonal wavelet kernel support vector machine; ideal prediction effect; incremental model; online time series forecasting algorithm; signal processing; Forecasting; Indexes; Kernel; Low pass filters; Prediction algorithms; Support vector machines; Training; Biorthogonal Wavelet; Forecast; Kernel Function; Online Time Series; Support Vector Machine (SVM);
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
DOI :
10.1109/CSSS.2012.16
