DocumentCode
2957620
Title
Nonparametric approach for estimating dynamics of stock index
Author
Guo, Baosheng ; Ren, Ruoen
Author_Institution
Dept. of Econ. & Manage., Beihang Univ., Beijing
fYear
2008
fDate
1-8 June 2008
Firstpage
1556
Lastpage
1561
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634003
Filename
4634003
Link To Document