MulticolIinearity Problems in Modeling Time Series With Trading-Day Variation
讨论了交易日变化影响的时间序列模型估计中的多重共线性问题，分析了设计矩阵并计算了共线性程度，同时考察了一种常用参数化的设计矩阵特征，表明在某些情况下该参数化能显著缓解多重共线性。
Abstract This article discusses the multicollinearity problems associated with the estimation of time series models influenced by trading-day variation. An analysis of the design matrix is performed, and measures of the degree of multicollinearity are computed. The characteristics of the design matrix of a popular parameterization are also analyzed, and it is shown that in some cases use of this reparameterization significantly alleviates the multicollinearity problem. KEY WORDS: Condition indexesVariance decomposition proportionsEigenvalues