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Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market

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  • David McMillan
  • Alan Speight

Abstract

Recent research has suggested that intra-day volatility may possess a component structure due to heterogeneous information arrivals. This paper reports evidence for the existence of such components in FTSE-100 stock index futures returns data. Preliminary GARCH model estimates support previous evidence for other markets indicating the breakdown of theoretical GARCH temporal aggregation properties over the intra-day period. However, the fractional integration properties of absolute and squared returns, and FIGARCH conditional volatility model estimates, lend strong support to the contention that volatility dynamics results from multiple sources given the invariance of the fractional difference parameter estimates to the degree of intra-day data temporal aggregation.

Suggested Citation

  • David McMillan & Alan Speight, 2006. "Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(13), pages 959-972.
  • Handle: RePEc:taf:apfiec:v:16:y:2006:i:13:p:959-972 DOI: 10.1080/09603100500426507
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    References listed on IDEAS

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    Cited by:

    1. David G. McMillan & Alan E. H. Speight, 2006. "Market trader heterogeneity and high frequency volatility dynamics: further evidence from intra-day FTSE-100 futures data," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 2(2), pages 99-103, March.
    2. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    3. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
    4. Anagnostidis, Panagiotis & Emmanouilides, Christos J., 2015. "Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 473-487.

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