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Index futures volatility and trading activity: Measuring causality at a multiple horizon

Author

Listed:
  • Sangram Keshari Jena

    (Université d'Hyderabad)

  • Aviral Kumar Tiwari

    (Université d'Hyderabad, Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School)

  • David Roubaud

    (MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier)

  • Muhammad Shahbaz

    (Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School)

Abstract

Copeland (1976) and Shalen (1993) state that the causal relationship between trading activity variables, such as volume, open interest and volatility, the three most important factors for traders and portfolio managers, extends beyond one day. However, the literature on causality thus far concerns a one-day horizon. In this study, we provide a more powerful causality test by measuring the strength of the causal relationship over a multiple horizon. The robustness of the results is analysed by splitting the sample into two period pre and post 2008 crisis. Our findings may impact the designing of trading strategies.

Suggested Citation

  • Sangram Keshari Jena & Aviral Kumar Tiwari & David Roubaud & Muhammad Shahbaz, 2018. "Index futures volatility and trading activity: Measuring causality at a multiple horizon," Post-Print hal-02061357, HAL.
    • Handle: RePEc:hal:journl:hal-02061357
    DOI: 10.1016/j.frl.2017.09.012
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    References listed on IDEAS

    as
    1. Shalen, Catherine T, 1993. "Volume, Volatility, and the Dispersion of Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 405-434.
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    3. Sangram Keshari Jena & Ashutosh Dash, 2014. "Trading activity and Nifty index futures volatility: an empirical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 24(17), pages 1167-1176, September.
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    12. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    13. Roger A. Fujihara & Mbodja Mougoué, 1997. "Linear dependence, nonlinear dependence and petroleum futures market efficiency," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(1), pages 75-99, February.
    14. Sangram K. Jena, 2016. "Sequential Information Arrival Hypothesis: More Evidence from the Indian Derivatives Market," Vision, , vol. 20(2), pages 101-110, June.
    15. Zhang, Hui Jun & Dufour, Jean-Marie & Galbraith, John W., 2016. "Exchange rates and commodity prices: Measuring causality at multiple horizons," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 100-120.
    16. Fung, Hung-Gay & Patterson, Gary A., 1999. "The dynamic relationship of volatility, volume, and market depth in currency futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(1), pages 33-59, January.
    17. Paul Berhanu Girma & Mbodja Mougoué, 2002. "An empirical examination of the relation between futures spreads volatility, volume, and open interest," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(11), pages 1083-1102, November.
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    Cited by:

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    2. Park, Beum-Jo, 2022. "The COVID-19 pandemic, volatility, and trading behavior in the bitcoin futures market," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Park, Keun Woo & Hong, Dahae & Oh, Ji Yeol Jimmy, 2019. "Investor behavior around monetary policy announcements: Evidence from the Korean stock market," Finance Research Letters, Elsevier, vol. 28(C), pages 355-362.
    4. Parizad Phiroze Dungore & Sarosh Hosi Patel, 2021. "Analysis of Volatility Volume and Open Interest for Nifty Index Futures Using GARCH Analysis and VAR Model," IJFS, MDPI, vol. 9(1), pages 1-11, January.
    5. Czudaj, Robert L., 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Econometrics and Statistics, Elsevier, vol. 12(C), pages 78-145.
    6. Sania Wadud & Robert D. Durand & Marc Gronwald, 2021. "Connectedness between the Crude Oil Futures and Equity Markets during the Pre- and Post-Financialisation Eras," CESifo Working Paper Series 9202, CESifo.

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    More about this item

    Keywords

    Trading activity; Multiple-horizon; Granger causality; Open interest;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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