10 citations · 16 across the 6 of their papers we have counts for
7 papers
The Generalized Fisher Transformation: Finite-Sample Properties and Inference
Ilya Archakov, Peter Reinhard Hansen
We study the finite-sample behavior of the Generalized Fisher Transformation (GFT), the parametrization of a correlation matrix by . The GFT coo…
A Robust Similarity Estimator
Ilya Archakov
We analyze a measure of statistical association based on the similarity of the outcomes of random variables, in both sign and magnitude. Motivated by its attractive properties, we…
Cluster GARCH
Chen Tong, Peter Reinhard Hansen, Ilya Archakov
We introduce a novel multivariate GARCH model with flexible convolution-t distributions that is applicable in high-dimensional systems. The model is called Cluster GARCH because it…
A New Method for Generating Random Correlation Matrices
Ilya Archakov, Peter Reinhard Hansen, Yiyao Luo
We propose a new method for generating random correlation matrices that makes it simple to control both location and dispersion. The method is based on a vector parameterization, g…
A New Parametrization of Correlation Matrices
Ilya Archakov, Peter Reinhard Hansen
We introduce a novel parametrization of the correlation matrix. The reparametrization facilitates modeling of correlation and covariance matrices by an unrestricted vector, where p…
A Multivariate Realized GARCH Model
Ilya Archakov, Peter Reinhard Hansen, Asger Lunde
We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector parametrizati…
A Canonical Representation of Block Matrices with Applications to Covariance and Correlation Matrices
Ilya Archakov, Peter Reinhard Hansen
We obtain a canonical representation for block matrices. The representation facilitates simple computation of the determinant, the matrix inverse, and other powers of a block matri…