关键词: 小波变换, 模极大值, 李普西兹指数, 奇异性

Abstract: Based on the wavelet transform modulus maxima method, this paper analyzes singularity of financial time series in subprime crisis. The results show that modulus maxima method are more accurate in detecting abnormal points and its appearing time of financial asset prices. Detections of peak point are more robust than that of zero-crossing point. These singular points correspond to the major economic events of mainly stage of the subprime crisis and react the impact of economic system abnormalities on financial markets in crisis. Finally, we take robust test.

Key words: Financial Markets, Wavelets Transform, Modulus Maxima Curve,, Lipschitz Exponent, Singular