Multivariate tail measure and the estimation of CoVar
Author
Nguyen, Tilo
Samorodnitsky, Gennady
Abstract
The quality of estimation of multivariate tails depends significantly on the portion of the sample included in the estimation. A simple approach involving sequential statistical testing is proposed in order to select which observations should be used for estimation of the tail and spectral measures. We prove that the estimator is consistent. We test the proposed method on simulated data, and subsequently apply it to analyze CoVar for stock and index returns.
Sponsorship
This research was partially supported by the ARO
grants W911NF-07-1-0078 and W911NF-12-10385, NSF grant DMS-1005903
and NSA grant H98230-11-1-0154 at Cornell University.
grants W911NF-07-1-0078 and W911NF-12-10385, NSF grant DMS-1005903
and NSA grant H98230-11-1-0154 at Cornell University.
Date Issued
2012-10-09
Keywords
Type
technical report