摘要
本文使用小波变换模极大值方法分析次贷危机中美国证券市场的突变。研究发现,小波模极大值方法准确定位了金融资产价格异常点的具体时刻;检测出了2类奇异点,其中峰值点检测比过零点检测更稳健;这些奇异点对应了美国次贷危机主要发展阶段的重大经济事件,反应出危机中美国经济系统异常对金融市场造成的影响。文章最后进行了稳健性检验。
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.
出处
《统计研究》
CSSCI
北大核心
2012年第3期97-101,共5页
Statistical Research
基金
国家自然科学基金重点项目(项目批准号:70381001)
创新群体项目(项目批准号:70821061)的资助
关键词
小波变换
模极大值
李普西兹指数
奇异性
Financial Markets
Wavelets Transform
Modulus Maxima Curve
Lipschitz Exponent
Singular
