Keywords
HAR-RV model, realized volatility, covariance matrix, factor model
Abstract
We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of lagged volatility, lagged returns and other forecasting variables. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it results in a positive-definite estimated covariance matrix. We apply the model to the covariance matrix of size-sorted stock returns and find that two factors are sufficient to capture most of the dynamics.
Original Publication Citation
“Forecasting Multivariate Realized Stock Market Volatility,” (with Greg Bauer), 2011, Journal of Econometrics, 160:1, 93-101.
BYU ScholarsArchive Citation
Bauer, Gregory H. and Vorkink, Keith, "Forecasting Multivariate Realized Stock Market Volatility" (2011). Faculty Publications. 9215.
https://scholarsarchive.byu.edu/facpub/9215
Document Type
Peer-Reviewed Article
Publication Date
2011
Publisher
Journal of Econometrics
Language
English
College
Marriott School of Business
Department
Finance
Copyright Status
© 2010 Elsevier B.V. All rights reserved.
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