The Role of Realized Ex-post Covariance Measures and Dynamic Model Choice on the Quality of Covariance Forecasts

Rasmus Varneskov () and Valeri Voev ()
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Rasmus Varneskov: School of Economics and Management, Aarhus University and CREATES, Postal: Bartholins Allé 10, Aarhus, Denmark

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

Abstract: Recently, consistent measures of the ex-post covariation of financial assets based on noisy high-frequency data have been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data based covariance measures. The aim of this paper is to investigate whether more sophisticated estimation approaches lead to more precise covariance forecasts, both in a statistical precision sense and in terms of economic value. A further issue we address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs. the model’s dynamic specification. The main finding is that the largest gains result from switching from daily to high-frequency data. Further gains are achieved if a simple sparsesampling covariance measure is replaced with a more efficient and noise-robust estimator.

Keywords: Forecast evaluation; Volatility forecasting; Portfolio optimization; Mean-variance analysis. (search for similar items in EconPapers)
JEL-codes: C32 C53 G11 (search for similar items in EconPapers)
Pages: 27
Date: 2010-08-26
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Journal Article: The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2010-45

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