Principal Component Analysis of High-Frequency Data

Volume: 114, Issue: 525, Pages: 287 - 303
Published: Jun 28, 2018
Abstract
We develop the necessary methodology to conduct principal component analysis at high frequency. We construct estimators of realized eigenvalues, eigenvectors, and principal components, and provide the asymptotic distribution of these estimators. Empirically, we study the high-frequency covariance structure of the constituents of the S&P 100 Index using as little as one week of high-frequency data at a time, and examines whether it is compatible...
Paper Details
Title
Principal Component Analysis of High-Frequency Data
Published Date
Jun 28, 2018
Volume
114
Issue
525
Pages
287 - 303
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