Wavelet Transform and Its Application in Stock Market Data Analysis
Xiang Heng Xiao · Journal of Southwest Jiaotong University · 2001
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.