Clustering Analysis of Stock Volume and Price Relationship based on Gaussian Mixture Model

DOI

10.2991/meic-14.2014.350How to use a DOI?

Keywords

Clustering analysis; Gaussian Mixture Model;Stock trading volume; Stock price

Abstract

The research of stock price volatility is very important. Traditionally, the stock price is usually processed as a time series, and don't consider the influence of stock trading volume. In this paper, we use Gaussian Mixture Model method to the clustering analysis of stock price volatility based on stock trading volume. The method is used to analysis the real data of Wuliangye stock in Shenzhen stock market of China. The experimental results show that it is possible to get the better clustering results by considering the influence of daily trading volume to stock closing price.fusion method based on the Nonsubsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Networks (PCNN) is proposed in this paper. First, we gain three components of visible image, luminance I, chrominance H and saturation S, using the IHS transform. Then, we gain three coefficients, low frequency sub-band, passband sub-band and high frequency coefficient by decomposing the component I and infrared image with the help of the NSCT. Next, we use weighted-sum method to fuse the low frequency sub-band and PCNN method to fuse the other sub-band coefficient respectively. At last, we gain the fusion image by using the inverse IHS transform on the fusion component I gained by the inverse NSCT transform. Experiments show that our method have better fusion quality and can be more better to keep the visible spectral and detail information than some traditional methods such as, Laplace method, Wavelet method and Lifting Wavelet method.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaohui Bai
AU  - Jianwu Dang
PY  - 2014/11
DA  - 2014/11
TI  - Clustering Analysis of Stock Volume and Price Relationship based on Gaussian Mixture Model
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1552
EP  - 1555
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.350
DO  - 10.2991/meic-14.2014.350
ID  - Bai2014/11
ER  -