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

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  • Cartea, Álvaro
  • Karyampas, Dimitrios

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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 35 (2011)
Issue (Month): 12 ()
Pages: 3319-3334

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Handle: RePEc:eee:jbfina:v:35:y:2011:i:12:p:3319-3334

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Web page: http://www.elsevier.com/locate/jbf

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Keywords: Volatility estimation; High-frequency data; Market microstructure noise; Covariation of assets; Kalman filter;

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Cited by:
  1. Korhonen, Iikka & Peresetsky , Anatoly, 2013. "Extracting global stochastic trend from non-synchronous data," BOFIT Discussion Papers 15/2013, Bank of Finland, Institute for Economies in Transition.

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