摘要
把股票日收益率看作一维时间信号 ,通过子波变换与多尺度分析 ,求出了体现股市数据奇异性的Lipschitz指数α。α为负表明在奇异点比不连续更加奇异 ,证明了股票价格的变化是分形的。同时 ,由文中图示可知 ,在尺度s很大时 ,子波变换和多尺度分析可以将股市数据中偶然因素造成的涨跌消除 ,具有突出主要因素和宏观突变点的特点 ,这一点对于从宏观上预测股价的走势有重要意义。
A lipschitz exponent α, which ref lects the singlarity nature of stock data, is obtained with wavelet trans form and muti scale analysis by regarding stock day profit ratio as a one dimentional time signal. α in this paper is negative, showing that the singul arity is more singular than non continuum. This proves that the variation of st ock prices is fractal. At the same time, it is pointed out that when scale s is very big, wavelet transform and multi scale analysis can remove the up an d down of stock market data caused by accidental factors and give prominence t o primary factors and macroscopic sudden change points. This is important in predicting the variat ion trend of stock prices from macroscopic aspect.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2001年第1期109-112,共4页
Journal of Southwest Jiaotong University
