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Accurate estimator of correlations between asynchronous signals

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  • Tóth, Bence
  • Kertész, János

Abstract

The estimation of the correlation between time series is often hampered by the asynchronicity of the signals. Cumulating data within a time window suppresses this source of noise but weakens the statistics. We present a method to estimate correlations without applying long time windows. We decompose the correlations of data cumulated over a long window using decay of lagged correlations as calculated from short window data. This increases the accuracy of the estimated correlation significantly and decreases the necessary effort of calculations both in real and computer experiments.

Suggested Citation

  • Tóth, Bence & Kertész, János, 2009. "Accurate estimator of correlations between asynchronous signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1696-1705.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:8:p:1696-1705
    DOI: 10.1016/j.physa.2008.12.062
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    References listed on IDEAS

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    1. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 225-239.
    2. Precup, Ovidiu V. & Iori, Giulia, 2004. "A comparison of high-frequency cross-correlation measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 252-256.
    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.
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    Cited by:

    1. Materassi, Donatello & Innocenti, Giacomo, 2009. "Unveiling the connectivity structure of financial networks via high-frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3866-3878.
    2. Iacopo Mastromatteo & Matteo Marsili & Patrick Zoi, 2010. "Financial correlations at ultra-high frequency: theoretical models and empirical estimation," Papers 1011.1011, arXiv.org, revised Feb 2011.

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