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Cross-Correlation Measures in the High-Frequency Domain

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Author Info
Ovidiu Precup () (King’s College London)
Giulia Iori () (Department of Economics, City University, London)

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Abstract

On a high-frequency scale, financial time series are not homogeneous, therefore standard correlation measures can not be directly applied to the raw data. To deal with this problem the time series have to be either homogenized through interpolation or methods that can handle raw non-synchronous time series need to be employed. This paper compares two traditional methods that use interpolation with an alternative method applied directly to the actual time series. The three methods are tested on simulated data and actual trades time series. The temporal evolution of the correlation matrix is revealed through the analysis of the full correlation matrix and of the Minimum Spanning Tree representation. To perform the analysis we implement several measures from the theory of random weighted networks.

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Publisher Info
Paper provided by Department of Economics, City University, London in its series City University Economics Discussion Papers with number 05/04.

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Length: 20 pages
Date of creation: Oct 2005
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Publication status: Forthcoming in European Journal of Finance, 2007.
Handle: RePEc:cty:dpaper:0504

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Related research
Keywords: High-Frequency Correlation; Fourier method; Epps Effect; Minimum Spanning Tree; random networks;

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July. [Downloadable!] (restricted)
  2. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciche` & N. Vandewalle & R. N. Mantegna, 2004. "Networks of equities in financial markets," Quantitative Finance Papers cond-mat/0401300, arXiv.org. [Downloadable!]
  3. Maria Elvira Mancino & Paul Malliavin, 2002. "Fourier series method for measurement of multivariate volatilities," Finance and Stochastics, Springer, vol. 6(1), pages 49-61. [Downloadable!] (restricted)
  4. de Jong, Frank & Nijman, Theo, 1997. "High frequency analysis of lead-lag relationships between financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 259-277, June. [Downloadable!] (restricted)
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  5. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility of diffusion processes with high frequency data," Economics Letters, Elsevier, vol. 74(3), pages 371-378, February. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. S. Sanfelici & M. E. Mancino, 2008. "Covariance estimation via Fourier method in the presence of asynchronous trading and microstructure noise," Economics Department Working Papers 2008-ME01, Department of Economics, Parma University (Italy). [Downloadable!]
  2. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre. [Downloadable!]
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