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Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity

  • Kris Boudt

    ()

    (Department of Business, Vrije Universiteit Brussel, Belgium and VU University Amsterdam, Netherlands)

  • Sébastien Laurent

    ()

    (Aix-Marseille University, Aix-Marseille School of Economics, CNRS & EHESS, France)

  • Asger Lunde

    ()

    (Aarhus University and CREATES)

  • Rogier Quaedvlieg

    ()

    (Department of Finance, Maastricht University, Netherlands)

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.

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Paper provided by Department of Economics and Business Economics, Aarhus University in its series CREATES Research Papers with number 2014-05.

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Length: 32
Date of creation: 02 2014
Date of revision:
Handle: RePEc:aah:create:2014-05
Contact details of provider: Web page: http://www.econ.au.dk/afn/

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