基于函数型数据分析的金融数据多层凝聚算法

Multilevel Aggregation Algorithm of Financial Data Based on Functional Data Analysis

将多层核心集凝聚算法应用于函数型数据分析,并应用于金融数据聚类.首先,依托金融数据的函数型特征对其进行基函数展开;其次,对产生的高维数据进行特征提取;最后,用多层核心集凝聚算法进行聚类.实验对股票波动率曲线进行聚类,挖掘出股票数据波动的内在特征,可以客观地对股票板块进行划分.

This paper applies the multilevel core-sets aggregation algorithm to functional data analysis and apply it to financial data clustering.First of all,based on the functional characteristics of financial data to expand the basis function.Secondly,feature extraction is performed on the high-dimensional data.Finally,the multilevel core-sets aggregation algorithm is used for clustering.The experiment clusters the stock volatility curve,and digs out the inherent characteristics of stock data fluctuations,which can objectively divide the stock sector.