作者: Adel Sharkasi , Martin Crane , Heather J. Ruskin , Jose A. Matos
DOI: 10.1016/J.PHYSA.2005.12.048
关键词: Covariance matrix 、 Wavelet 、 Mathematics 、 Covariance 、 Eigenvalues and eigenvectors 、 Econometrics 、 Stock market 、 Wavelet transform 、 Discrete wavelet transform 、 Emerging markets
摘要: Abstract We study here the behaviour of first three eigenvalues ( λ 1 , 2 3 ) and their ratios [ / ] covariance matrices original return series those rebuilt from wavelet components for emerging mature markets. It has been known some time that largest eigenvalue contains information on risk associated with particular assets which matrix is comprised. Here, we wish to ascertain whether subdominant hold stock market also measure recovery To do this, use discrete transform gives a clear picture movements in by reconstructing them using each component. Our results appear indicate markets respond crashes differently ones, may take up two months recover while major less than month so. In addition, appears show give additional movement, especially other provide insight crash dynamics.