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

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  • R. M. Eldridge
  • Maurice Peat

    (Discipline of Finance, University of Sydney)

  • Max Stevenson

    (Discipline of Finance, University of Sydney)

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    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.

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    Bibliographic Info

    Paper provided by Finance Discipline Group, UTS Business School, University of Technology, Sydney in its series Working Paper Series with number 122.

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    Date of creation: 01 Jan 2003
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    Handle: RePEc:uts:wpaper:122

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    1. 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.
    2. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-37, July.
    3. 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 301-32.
    4. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-77, December.
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    7. 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.
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    9. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    10. 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.
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