IDEAS home Printed from
   My bibliography  Save this article

Detecting intraday periodicities with application to high frequency exchange rates


  • Chris Brooks
  • Melvin J. Hinich


Many recent papers have documented periodicities in returns, return volatility, bid-ask spreads and trading volume, in both equity and foreign exchange markets. We propose and employ a new test for detecting subtle periodicities in time series data based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8-h and 12-h frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule that is based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules can generate returns that are considerably greater than those of a buy-and-hold strategy, although they cannot retain their profitability net of transactions costs. We conjecture that this methodology could constitute an important tool for financial market researchers which will enable them to detect, quantify and rank the various periodic components in financial data better. Copyright 2006 Royal Statistical Society.

Suggested Citation

  • Chris Brooks & Melvin J. Hinich, 2006. "Detecting intraday periodicities with application to high frequency exchange rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 241-259.
  • Handle: RePEc:bla:jorssc:v:55:y:2006:i:2:p:241-259

    Download full text from publisher

    File URL:
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Romero-Meza, Rafael & Bonilla, Claudio & Benedetti, Hugo & Serletis, Apostolos, 2015. "Nonlinearities and financial contagion in Latin American stock markets," Economic Modelling, Elsevier, vol. 51(C), pages 653-656.
    2. Taylor, James W., 2010. "Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles," International Journal of Forecasting, Elsevier, vol. 26(4), pages 627-646, October.
    3. Escañuela Romana, Ignacio, 2011. "Evidencia empírica sobre la predictibilidad de los ciclos bursátiles: el comportamiento del índice Dow Jones Industrial Average en las crisis bursátiles de 1929, 1987 y 2997
      [Empirical evidence on
      ," MPRA Paper 33150, University Library of Munich, Germany.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssc:v:55:y:2006:i:2:p:241-259. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley Content Delivery). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.