High-dimensional multivariate realized volatility estimation

Published

Journal Article

© 2019 Elsevier B.V. We provide a new factor-based estimator of the realized covolatility matrix, applicable in situations when the number of assets is large and the high-frequency data are contaminated with microstructure noises. Our estimator relies on the assumption of a factor structure for the noise component, separate from the latent systematic risk factors that characterize the cross-sectional variation in the frictionless returns. The new estimator provides theoretically more efficient and finite-sample more accurate estimates of large-scale integrated covolatility and correlation matrices than other recently developed realized estimation procedures. These theoretical and simulation-based findings are further corroborated by an empirical application related to portfolio allocation and risk minimization involving several hundred individual stocks.

Full Text

Duke Authors

Cited Authors

  • Bollerslev, T; Meddahi, N; Nyawa, S

Published Date

  • September 1, 2019

Published In

Volume / Issue

  • 212 / 1

Start / End Page

  • 116 - 136

Electronic International Standard Serial Number (EISSN)

  • 1872-6895

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/j.jeconom.2019.04.023

Citation Source

  • Scopus