IDEAS home Printed from https://ideas.repec.org/p/uts/wpaper/122.html
   My bibliography  Save this paper

The Role of Intra-Day and Inter-Day Data Effects in Determining Linear and Nonlinear Granger Causality Between Australian Futures and Cash Index Markets

Author

Listed:
  • R. M. Eldridge
  • Maurice Peat

    (Discipline of Finance, University of Sydney)

  • Max Stevenson

    (Discipline of Finance, University of Sydney)

Abstract

In order to explain the incidence of Granger causality between indices from the futures and the underlying cash market, as reported by numerous empirical studies in the literature, it is important to account for mean and volatility (second-order) persistence effects in the data. Further, there is need to control for inter-day and intra-day effects by imposing an appropriate autocorrelation structure upon each of the index returns from both markets. Once all these effects are controlled for, then linear Granger causality ceases to be statistically significant and the associated lead-lag phenomenon is no longer observable when the information flow between the spot and futures markets is completed within a five-minute observation interval. Additionally, nonlinear Granger causality testing indicates no compelling need to account for nonlinear effects (beyond the second-order moment condition) in order to explain causality. This result supports the price discovery role of futures markets.

Suggested Citation

  • R. M. Eldridge & Maurice Peat & Max Stevenson, 2003. "The Role of Intra-Day and Inter-Day Data Effects in Determining Linear and Nonlinear Granger Causality Between Australian Futures and Cash Index Markets," Working Paper Series 122, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  • Handle: RePEc:uts:wpaper:122
    as

    Download full text from publisher

    File URL: http://www.finance.uts.edu.au/research/wpapers/wp122.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    2. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    3. Abhyankar, A & Copeland, L S & Wong, W, 1997. "Uncovering Nonlinear Structure in Real-Time Stock-Market Indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 1-14, January.
    4. Baeck, E.G. & Brock, W.A., 1992. "A Nonparametric Test for Independence of a Multivariate Time Series," Working papers 9204, Wisconsin Madison - Social Systems.
    5. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 77-102.
    6. McInish, Thomas H & Wood, Robert A, 1984. "Intertemporal Differences in Movements of Minute-to-Minute Stock Returns," The Financial Review, Eastern Finance Association, vol. 19(4), pages 359-371, November.
    7. Dwyer, Gerald P, Jr & Locke, Peter R & Yu, Wei, 1996. "Index Arbitrage and Nonlinear Dynamics between the S&P 500 Futures and Cash," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 301-332.
    8. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    9. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    10. Stoll, Hans R. & Whaley, Robert E., 1990. "The Dynamics of Stock Index and Stock Index Futures Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(04), pages 441-468, December.
    11. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    12. Grunbichler Andreas & Longstaff Francis A. & Schwartz Eduardo S., 1994. "Electronic Screen Trading and the Transmission of Information: An Empirical Examination," Journal of Financial Intermediation, Elsevier, vol. 3(2), pages 166-187, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:uts:wpaper:122. 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: (Duncan Ford) or (Marina Grazioli). General contact details of provider: http://edirc.repec.org/data/sfutsau.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.