Proves sharp operator-norm concentration and expectation bounds for sample cross-covariances of sub-Gaussian and Gaussian vectors, governed by effective ranks of the marginal covariances.
The Annals of Statistics , volume=
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A Group Fused LASSO plus LASSO approach with adaptive weights detects change points in piecewise-constant sparse covariance matrices and yields consistent estimators under stated conditions.
A large-deviations method generates plausible stress scenarios for financial losses by concentrating on most likely configurations conditional on large losses, recovering stressed loss laws even with sparse data.
citing papers explorer
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Concentration Inequalities for Sample Cross-Covariances
Proves sharp operator-norm concentration and expectation bounds for sample cross-covariances of sub-Gaussian and Gaussian vectors, governed by effective ranks of the marginal covariances.
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Change-point detection in variance-covariance matrix
A Group Fused LASSO plus LASSO approach with adaptive weights detects change points in piecewise-constant sparse covariance matrices and yields consistent estimators under stated conditions.
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Generating Plausible Stress Scenarios via Large Deviations
A large-deviations method generates plausible stress scenarios for financial losses by concentrating on most likely configurations conditional on large losses, recovering stressed loss laws even with sparse data.