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Forecast of realized covariance matrix based on asymptotic distribution of the LU decomposition with an application for balancing minimum variance portfolio

Title
Forecast of realized covariance matrix based on asymptotic distribution of the LU decomposition with an application for balancing minimum variance portfolio
Authors
Kim H.-S.Shin D.W.
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2019
Journal Title
Applied Economics Letters
ISSN
1350-4851JCR Link
Citation
Applied Economics Letters vol. 26, no. 8, pp. 661 - 668
Keywords
Cholesky decompositionGHARLU decompositionminimum variance portfolioportfolio optimizationrealized covariance
Publisher
Routledge
Indexed
SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
We derive the asymptotic distribution for the LU decomposition, that is, the Cholesky decomposition, of realized covariance matrix. Distributional properties are combined with an existing generalized heterogeneous autoregressive (GHAR) method for forecasting realized covariance matrix, which will be referred to as a generalized HARQ (GHARQ) method. An out-of-sample forecast comparison of a real data set shows that the proposed GHARQ method outperforms other existing methods in terms of optimizing the variances of portfolios. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
DOI
10.1080/13504851.2018.1489108
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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