Title :
Nonparametric approach for estimating dynamics of stock index
Author :
Guo, Baosheng ; Ren, Ruoen
Author_Institution :
Dept. of Econ. & Manage., Beihang Univ., Beijing
Abstract :
Parametric and nonparametric methods are used in estimating stochastic diffusion process. Nonparametric method has its own advantages; this paper utilizes nonparametric method to estimate drift and diffusion term. Two nonparametric methods have been studied, which are kernel estimation and local linear estimation. Local linear estimation has been used in estimating dynamics of Shanghai Stock Exchange Composite Index.
Keywords :
estimation theory; nonparametric statistics; stochastic processes; stock markets; Shanghai stock exchange composite index; kernel estimation; local linear estimation; stochastic diffusion estimation; Bonding; Diffusion processes; Discrete wavelet transforms; Economic indicators; Kernel; Motion estimation; Partial response channels; Solid modeling; Stochastic processes; Stock markets; Stochastic diffusion process; kernel regression; local linear estimation; stock indices;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634003
