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Intra-day Futures Price Volatility: Information Effects and Variance Persistence

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  • Locke, P R
  • Sayers, C L
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    Abstract

    This paper examines the role of the rate of information arrival proxy variables, as they relate to persistence in the variance structure of minute-by-minute S&P 500 Index Futures returns series. The role of contract volume, floor transactions, the number of price changes, executed order imbalance, and an information composite in reducing variance persistence is examined. All proxy variables are found to explain a significant amount of returns variance. While the characteristics of returns data vary daily, some evidence of remaining variance persistence is found, regardless of the definition of the rate of information arrival variable. Our results suggest that utilization of a pure ARCH-type model for high-frequency returns data implies a mis-specification. Copyright 1993 by John Wiley & Sons, Ltd.

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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

    Volume (Year): 8 (1993)
    Issue (Month): 1 (Jan.-March)
    Pages: 15-30

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    Handle: RePEc:jae:japmet:v:8:y:1993:i:1:p:15-30

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    Cited by:
    1. Shin-Juh Lin & Jian Yang, 2000. "Examining Intraday Returns with Buy/Sell Information," Research Paper Series 38, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Andrew C. Worthington & Helen Higgs, 2003. "Modelling the Intraday Return Volatility Process In The Australian Equity Market: An Examination Of The Role Of Information Arrival In S&P/Asx 50 Stocks," School of Economics and Finance Discussion Papers and Working Papers Series 150, School of Economics and Finance, Queensland University of Technology.
    3. Weaver, Robert D & Natcher, William C, 2000. "Commodity Price Volatility under New Market Orientations," MPRA Paper 9862, University Library of Munich, Germany.
    4. Hodgson, Allan & Masih, A. Mansur M. & Masih, Rumi, 2006. "Futures trading volume as a determinant of prices in different momentum phases," International Review of Financial Analysis, Elsevier, vol. 15(1), pages 68-85.
    5. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    6. Joshua V. Rosenberg & Leah G. Traub, 2006. "Price discovery in the foreign currency futures and spot market," Staff Reports 262, Federal Reserve Bank of New York.
    7. Antonakakis, Nikolaos & Kizys, Renatas & Floros, Christos, 2014. "Dynamic Spillover Effects in Futures Markets," MPRA Paper 53876, University Library of Munich, Germany.
    8. Kofman, Paul & Martens, Martin, 1997. "Interaction between stock markets: an analysis of the common trading hours at the London and New York stock exchange," Journal of International Money and Finance, Elsevier, vol. 16(3), pages 387-414, June.
    9. Chang, Yuanchen & Taylor, Stephen J., 2003. "Information arrivals and intraday exchange rate volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(2), pages 85-112, April.

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