IDEAS home Printed from https://ideas.repec.org/a/cup/macdyn/v14y2010is1p88-110_09.html
   My bibliography  Save this article

Identifying Nonlinear Serial Dependence In Volatile, High-Frequency Time Series And Its Implications For Volatility Modeling

Author

Listed:
  • Wild, Phillip
  • Foster, John
  • Hinich, Melvin J.

Abstract

In this article, we show how tests of nonlinear serial dependence can be applied to high-frequency time series data that exhibit high volatility, strong mean reversion, and leptokurtotis. Portmanteau correlation, bicorrelation, and tricorrelation tests are used to detect nonlinear serial dependence in the data. Trimming is used to control for the presence of outliers in the data. The data that are employed are 161,786 half-hourly spot electricity price observations recorded over nearly a decade in the wholesale electricity market in New South Wales, Australia. Strong evidence of nonlinear serial dependence is found and its implications for time series modeling are discussed.

Suggested Citation

  • Wild, Phillip & Foster, John & Hinich, Melvin J., 2010. "Identifying Nonlinear Serial Dependence In Volatile, High-Frequency Time Series And Its Implications For Volatility Modeling," Macroeconomic Dynamics, Cambridge University Press, vol. 14(S1), pages 88-110, May.
    • Handle: RePEc:cup:macdyn:v:14:y:2010:i:s1:p:88-110_09
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1365100509090543/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Wild, Phillip & Hinich, Melvin J. & Foster, John, 2010. "Are daily and weekly load and spot price dynamics in Australia's National Electricity Market governed by episodic nonlinearity?," Energy Economics, Elsevier, vol. 32(5), pages 1082-1091, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:cup:macdyn:v:14:y:2010:i:s1:p:88-110_09. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/mdy .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.