Volatility and Covariation of Financial Assets: A High-Frequency Analysis

Álvaro Cartea () and Dimitrios Karyampas
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Dimitrios Karyampas: Department of Economics, Mathematics & Statistics, Birkbeck

No 913, Birkbeck Working Papers in Economics and Finance from Birkbeck, Department of Economics, Mathematics & Statistics

Abstract: Using high frequency data for the price dynamics of equities we measure the impact that market microstructure noise has on estimates of the: (i) volatility of returns; and (ii) variance-covariance matrix of n. assets. We propose a Kalman-filter-based methodology that allows us to deconstruct price series into the true effcient price and the microstructure noise. This approach allows us to employ volatility estimators that achieve very low Root Mean Squared Errors (RMSEs) compared to other estimators that have been proposed to deal with market microstructure noise at high frequencies. Furthermore, this price series decomposition allows us to estimate the variance covariance matrix of n assets in a more efficient way than the methods so far proposed in the literature. We illustrate our results by calculating how microstructre noise affects portfolio decisions and calculations of the equity beta in a CAPM setting.

Date: 2009-10
New Economics Papers: this item is included in nep-ecm and nep-mst
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https://eprints.bbk.ac.uk/id/eprint/7608 First version, 2009 (application/pdf)

Related works:
Journal Article: Volatility and covariation of financial assets: A high-frequency analysis (2011)
Working Paper: Volatility and covariation of financial assets: a high-frequency analysis (2009)
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