On generalized expectation-based estimation of a population spectral distribution from high-dimensional data

Weiming Li () and Jianfeng Yao ()

Annals of the Institute of Statistical Mathematics, 2015, vol. 67, issue 2, 359-373

Abstract: This paper discusses the problem of estimating the population spectral distribution from high-dimensional data. We present a general estimation procedure that covers situations where the moments of this distribution fail to identify the model parameters. The main idea is to use generalized functional expectations as a substitute for the moments. Beyond the consistency, we also prove a central limit theorem for the proposed estimator. Simulation experiments illustrate the implementation of the estimation procedure. An application to the analysis of the eigenvalues of the sample correlation matrix of S&P 500 daily stock returns is proposed. Copyright The Institute of Statistical Mathematics, Tokyo 2015

Keywords: Large sample covariance matrix; Eigenvalues distribution; Population spectral distribution; Empirical spectral distribution; Generalized expectation estimation (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10463-014-0452-2

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