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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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    Cited by:

    1. Jena, Sangram Keshari & Lahiani, Amine & Tiwari, Aviral Kumar & Roubaud, David, 2021. "Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study," Resources Policy, Elsevier, vol. 74(C).
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.

    More about this item

    Keywords

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    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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