Outlier's Detection of Financial Time Series Based on Wavelet Modulus Maxima Line Method
Mao Yi-bo · Journal of Chongqing University. English Edition · 2007
This paper investigates the application of wavelet transform methods on outlier detection of financial time series.Through Continuous Wavelet Transform and the analysis of modulus maxima line corresponding sample point,the authors put forward an approach of Outlier's detection of Financial Time Series Based on Wavelet Modulus Maxima Line Algorithms.By digital simulation of GARCH-M model,they prove that the method has much value in practical.The method can be more accurate to identify the concrete outliers of financial assets return what motion take place,and have an important meaning to estimate financial property rate of return as well.