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Spectral analysis informs the proper frequency in the sampling of financial time series data

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  • Taufemback, Cleiton
  • Da Silva, Sergio

Abstract

Applied econometricians tend to show a long neglect for the proper frequency to be considered while sampling the time series data. The present study shows how spectral analysis can be usefully employed to fix this problem. The case is illustrated with ultra-high-frequency data and daily prices of four selected stocks listed on the Sao Paulo stock exchange.

Suggested Citation

  • Taufemback, Cleiton & Da Silva, Sergio, 2011. "Spectral analysis informs the proper frequency in the sampling of financial time series data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2067-2073.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:11:p:2067-2073
    DOI: 10.1016/j.physa.2011.02.016
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    References listed on IDEAS

    as
    1. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    2. Yacine Aït-Sahalia, 2005. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 351-416.
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    More about this item

    Keywords

    Spectral analysis; Aliasing; Applied econometrics; Econophysics;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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