Hidden noise structure and random matrix models of stock correlations

DOI10.1080/14697688.2012.664931zbMath1278.91187arXiv0909.1383OpenAlexW2036405411MaRDI QIDQ2873030

Ivailo I. Dimov, Dan Y. C. Shiber, Lee MacLin, Petter Kolm

Publication date: 17 January 2014

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0909.1383

zbMATH Keywords

clusteringrandom matrix theoryPCAparticipation ratioresidual risk biasstock return cross correlationsTAQ

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Random matrices (probabilistic aspects) (60B20) Financial applications of other theories (91G80)

Related Items (2)

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues ⋮ Cleaning large correlation matrices: tools from random matrix theory

Cites Work

• Random magnets and correlations of stock price fluctuations
• On the top eigenvalue of heavy-tailed random matrices
• DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES

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