Spectral Analysis Informs the Proper Frequency in the Sampling of Financial Time Series Data
AbstractApplied 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 28720.
Date of creation: 2011
Date of revision:
Econophysics; Spectral analysis; Aliasing; Sampling; Financial time series;
Other versions of this item:
- 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.
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-02-19 (All new papers)
- NEP-CIS-2011-02-19 (Confederation of Independent States)
- NEP-ECM-2011-02-19 (Econometrics)
- NEP-ETS-2011-02-19 (Econometric Time Series)
- NEP-MST-2011-02-19 (Market Microstructure)
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.:
- Yacine Aït-Sahalia, 2005.
"How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise,"
Review of Financial Studies,
Society for Financial Studies, vol. 18(2), pages 351-416.
- Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc.
- 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.
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