Clustering Analysis of Stocks of CSI 300 Index Based on Manifold Learning

• 作者: Cheng Luo Hengjin Cai Ruiling Liu
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 工学
• 关键词: MANIFOLD Learning ISOMAP Nonlinear Dimensionality Reduction STOCK CLUSTERING
• 年，卷（期）: 2012,（2）
• 页码范围: 120-126
• 页数: 7页
• 分类号: TP39

摘要

As an effective way in finding the underlying parameters of a high-dimension space, manifold learning is popular in nonlinear dimensionality reduction which makes high-dimensional data easily to be observed and analyzed. In this paper, Isomap, one of the most famous manifold learning algorithms, is applied to process closing prices of stocks of CSI 300 index from September 2009 to October 2011. Results indicate that Isomap algorithm not only reduces dimensionality of stock data successfully, but also classifies most stocks according to their trends efficiently.