In this paper,we introduce a nonparametric test against the constancy of the factor loading matrix of large dimensional continuous time factor model using high frequency data.
A screening problem is tackled by proposing a parametric class of distributions designed to match the behavior of the partially observed screened data.
Let(εj)j≥0 be a sequence of independent p-dimensional random vectors and τ≥ 1 a given integer.From a sample ε1,...,εT+τ of the sequence,the so-called lag- auto-covariance matrix is C τ = T-1∑Tj =1
Modeling and estimation of correlation coefficient is a fundamental step in risk management,especially with the aftermath of the financial crisis in 2008,which challenged the traditional measuring of