Abstract
In this paper we propose a multi-target linear shrinkage estimator of the precision matrix by shrinking the inverse of the sample covariance matrix directly, which is a generalization of the single-target linear shrinkage estimator. The explicit expression of the weights of multi-target linear shrinkage estimator is derived when the ratio of the dimension p and the sample size n tends to a positive constant c ∈ (0, 1). The numerical simulation and an empirical analysis of financial market data are provided to compare the multi-target linear shrinkage estimator with some other estimators of the precision matrix proposed in the literature. The computation results show the improvement of the multi-target linear shrinkage estimator.
Published Version
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