Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity

Kris Boudt (), Sébastien Laurent, Asger Lunde () and Rogier Quaedvlieg
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Kris Boudt: Department of Business, Vrije Universiteit Brussel, Belgium and VU University Amsterdam, Netherlands, Postal: Pleinlaan 2, 1050 Brussel, Belgium
Asger Lunde: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many observations as possible. The estimator is guaranteed positive semidefinite. Monte Carlo simulations confirm good finite sample properties. In the application we forecast portfolio Value-at-Risk and sector risk exposures for a portfolio of 52 stocks. We find that forecasts obtained from dynamic models utilizing the proposed high-frequency estimator provide statistically and economically superior forecasts to models using daily returns.

Keywords: Cholesky decomposition; Integrated covariance; Non-synchronous trading; Positive semidefinite; Realized covariance (search for similar items in EconPapers)
JEL-codes: C10 C58 (search for similar items in EconPapers)
Pages: 32
Date: 2014-02-24
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mst and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Positive semidefinite integrated covariance estimation, factorizations and asynchronicity (2017)
Working Paper: Positive semidefinite integrated covariance estimation, factorizations and asynchronicity (2017)
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