Volatility and covariation of financial assets: a high-frequency analysis

Álvaro Cartea () and Dimitrios Karyampas

DEE - Working Papers. Business Economics. WB from Universidad Carlos III de Madrid. Departamento de Economía de la Empresa

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 efficient 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 microstructure noise affects portfolio decisions and calculations of the equity beta in a CAPM setting.

Keywords: Volatility; estimation; High-frequency; data; Market; microstructure; theory; Covariation; of; assets; Matrix; process; Kalman; filter (search for similar items in EconPapers)
JEL-codes: C22 G12 G14 (search for similar items in EconPapers)
Date: 2009-12
New Economics Papers: this item is included in nep-ecm and nep-mst
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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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Persistent link: https://EconPapers.repec.org/RePEc:cte:wbrepe:wb097609

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