[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v24y2018icp247-255.html
   My bibliography  Save this article

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

Author

Listed:
  • Jena, Sangram Keshari
  • Tiwari, Aviral Kumar
  • Roubaud, David
  • Shahbaz, Muhammad
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

  • Jena, Sangram Keshari & Tiwari, Aviral Kumar & Roubaud, David & Shahbaz, Muhammad, 2018. "Index futures volatility and trading activity: Measuring causality at a multiple horizon," Finance Research Letters, Elsevier, vol. 24(C), pages 247-255.
  • Handle: RePEc:eee:finlet:v:24:y:2018:i:c:p:247-255
    DOI: 10.1016/j.frl.2017.09.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612317302702
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2017.09.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    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.
    2. James C. Luu & Martin Martens, 2003. "Testing the mixture‐of‐distributions hypothesis using “realized” volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(7), pages 661-679, July.
    3. 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.
    4. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    5. 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.
    6. Sangram K. Jena, 2016. "Sequential Information Arrival Hypothesis: More Evidence from the Indian Derivatives Market," Vision, , vol. 20(2), pages 101-110, June.
    7. Bessembinder, Hendrik & Seguin, Paul J., 1993. "Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 21-39, March.
    8. Bessembinder, Hendrik & Chan, Kalok & Seguin, Paul J., 1996. "An empirical examination of information, differences of opinion, and trading activity," Journal of Financial Economics, Elsevier, vol. 40(1), pages 105-134, January.
    9. Julio Lucia & Angel Pardo, 2010. "On measuring speculative and hedging activities in futures markets from volume and open interest data," Applied Economics, Taylor & Francis Journals, vol. 42(12), pages 1549-1557.
    10. 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.
    11. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Short and long run causality measures: Theory and inference," Journal of Econometrics, Elsevier, vol. 154(1), pages 42-58, January.
    12. 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.
    13. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    14. Moonis Shakeel & Shahid Ashraf, 2012. "Empirical Relationship Between Index Futures Prices, Volume and Open Interest: Evidence from Indian Futures Market," The IUP Journal of Applied Finance, IUP Publications, vol. 18(3), pages 48-66, July.
    15. Janusz Brzeszczynski & Michael Melvin, 2006. "Explaining trading volume in the euro," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 25-34.
    16. 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.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    3. Sensoy, Ahmet & Serdengeçti, Süleyman, 2019. "Intraday volume-volatility nexus in the FX markets: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 1-12.
    4. 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.
    5. 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).
    6. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    7. Tribhuvan N. Puri & George C. Philippatos, 2008. "Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures," European Financial Management, European Financial Management Association, vol. 14(3), pages 528-563, June.
    8. Antonakakis, Nikolaos & Kizys, Renatas & Floros, Christos, 2014. "Dynamic Spillover Effects in Futures Markets," MPRA Paper 53876, University Library of Munich, Germany.
    9. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    10. Alizadeh, Amir H. & Tamvakis, Michael, 2016. "Market conditions, trader types and price–volume relation in energy futures markets," Energy Economics, Elsevier, vol. 56(C), pages 134-149.
    11. 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.
    12. Ahadzie, Richard Mawulawoe & Jeyasreedharan, Nagaratnam, 2020. "Trading volume and realized higher-order moments in the Australian stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    13. Martin T. Bohl & Pierre L. Siklos & Claudia Wellenreuther, 2018. "Speculative activity and returns volatility of Chinese major agricultural commodity futures," CAMA Working Papers 2018-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Biswal, P.C. & Jain, Anshul, 2019. "Should central banks use the currency futures market to manage spot volatility? Evidence from India," Journal of Multinational Financial Management, Elsevier, vol. 52.
    15. Alizadeh, Amir H., 2013. "Trading volume and volatility in the shipping forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 250-265.
    16. Bohl, Martin T. & Siklos, Pierre L. & Wellenreuther, Claudia, 2018. "Speculative activity and returns volatility of Chinese agricultural commodity futures," Journal of Asian Economics, Elsevier, vol. 54(C), pages 69-91.
    17. Ai-ru (Meg) Cheng & Yin-Wong Cheung, 2008. "Return, Trading Volume, and Market Depth in Currency Futures Markets," Working Papers 202008, Hong Kong Institute for Monetary Research.
    18. Saji Gopinath & Chandrasekhar Krishnamurti, 2001. "Number Of Transactions And Volatility: An Empirical Study Using High-Frequency Data From Nasdaq Stocks," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 24(2), pages 205-218, June.
    19. Chionis, Dionysios & MacDonald, Ronald, 1997. "Some tests of market microstructure hypotheses in the foreign exchange market," Journal of Multinational Financial Management, Elsevier, vol. 7(3), pages 203-229, October.
    20. repec:dau:papers:123456789/11681 is not listed on IDEAS
    21. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:24:y:2018:i:c:p:247-255. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.