A note on conditional covariance matrices for elliptical distributions
Probability
2017-03-06 v1 Statistics Theory
Risk Management
Statistics Theory
Abstract
In this short note we provide an analytical formula for the conditional covariance matrices of the elliptically distributed random vectors, when the conditioning is based on the values of any linear combination of the marginal random variables. We show that one could introduce the univariate invariant depending solely on the conditioning set, which greatly simplifies the calculations. As an application, we show that one could define uniquely defined quantile-based sets on which conditional covariance matrices must be equal to each other if only the vector is multivariate normal. The similar results are obtained for conditional correlation matrices of the general elliptic case.
Cite
@article{arxiv.1703.00918,
title = {A note on conditional covariance matrices for elliptical distributions},
author = {Piotr Jaworski and Marcin Pitera},
journal= {arXiv preprint arXiv:1703.00918},
year = {2017}
}