IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03573202.html
   My bibliography  Save this paper

Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study

Author

Listed:
  • Sangram Keshari Jena
  • Amine Lahiani

    (LEO - Laboratoire d'Économie d'Orleans - UO - Université d'Orléans - UT - Université de Tours)

  • Aviral Kumar Tiwari
  • David Roubaud

Abstract

This study cracks the multidimensional asymmetric relationship between trading activity (volume and open interest) and commodity futures prices to analyze the short-term dynamics and long-term cointegrating relationship across different state of the market considering both positive and negative changes in trading activity using a novel Quantile Non-linear Autoregressive Distributed Lag (QNARDL) approach. First, the asymmetric price effect is found in short- and long-run of volume and open interest. Second, the asymmetric price effect due to positive and negative changes in open interest (volume) is found in the short-run (long-run) for copper (gold and crude) futures. Third, distributional asymmetry is found in the above two price effects on all three commodity futures implying that the price effect changes with changes in market conditions such bearish, bullish, and normal. Our findings will help the portfolio managers for effective investment and diversification decision, traders for better trading strategy, hedgers for better risk management strategy, and regulators and concerned exchange for effective policy making in varied market conditions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Sangram Keshari Jena & Amine Lahiani & Aviral Kumar Tiwari & David Roubaud, 2021. "Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study," Post-Print hal-03573202, HAL.
  • Handle: RePEc:hal:journl:hal-03573202
    DOI: 10.1016/j.resourpol.2021.102277
    Note: View the original document on HAL open archive server: https://univ-orleans.hal.science/hal-03573202
    as

    Download full text from publisher

    File URL: https://univ-orleans.hal.science/hal-03573202/document
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.resourpol.2021.102277?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Paul Cashin & C. John McCDermott, 2002. "The Long-Run Behavior of Commodity Prices: Small Trends and Big Variability," IMF Staff Papers, Palgrave Macmillan, vol. 49(2), pages 1-2.
    2. 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.
    3. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    4. 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.
    5. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    6. 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.
    7. 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.
    8. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, 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. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    11. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    12. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    13. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in Quantiles and Dynamic Relations in Energy Markets," Working Papers 116, VATT Institute for Economic Research.
    14. Brunetti, Celso & Büyükşahin, Bahattin & Harris, Jeffrey H., 2016. "Speculators, Prices, and Market Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(5), pages 1545-1574, October.
    15. Zaremba, Adam & Umar, Zaghum & Mikutowski, Mateusz, 2019. "Inflation hedging with commodities: A wavelet analysis of seven centuries worth of data," Economics Letters, Elsevier, vol. 181(C), pages 90-94.
    16. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    17. repec:dau:papers:123456789/6887 is not listed on IDEAS
    18. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    19. Tarun Chordia & Bhaskaran Swaminathan, 2000. "Trading Volume and Cross‐Autocorrelations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(2), pages 913-935, April.
    20. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    21. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
    22. Ripple, Ronald D. & Moosa, Imad A., 2009. "The effect of maturity, trading volume, and open interest on crude oil futures price range-based volatility," Global Finance Journal, Elsevier, vol. 20(3), pages 209-219.
    23. Brooks, Robert D. & Faff, Robert W. & Fry, Tim R. L., 2001. "GARCH modelling of individual stock data: the impact of censoring, firm size and trading volume," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 11(2), pages 215-222, June.
    24. Changyun Wang, 2002. "The effect of net positions by type of trader on volatility in foreign currency futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(5), pages 427-450, May.
    25. Kirchler, Michael, 2010. "Partial knowledge is a dangerous thing - On the value of asymmetric fundamental information in asset markets," Journal of Economic Psychology, Elsevier, vol. 31(4), pages 643-658, August.
    26. Nguyen, Duc Khuong & Sensoy, Ahmet & Sousa, Ricardo M. & Salah Uddin, Gazi, 2020. "U.S. equity and commodity futures markets: Hedging or financialization?," Energy Economics, Elsevier, vol. 86(C).
    27. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    28. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in quantiles and dynamic relations in energy markets: (De)tails matter," Energy Policy, Elsevier, vol. 133(C).
    29. Irwin, Scott H. & Sanders, Dwight R. & Merrin, Robert P., 2009. "Devil or Angel? The Role of Speculation in the Recent Commodity Price Boom (and Bust)," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(2), pages 377-391, August.
    30. Jouini, Elyès & Napp, Clotilde, 2008. "Are more risk averse agents more optimistic? Insights from a rational expectations model," Economics Letters, Elsevier, vol. 101(1), pages 73-76, October.
    31. repec:dau:papers:123456789/29 is not listed on IDEAS
    32. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    33. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    34. 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.
    35. Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
    36. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
    37. Martin T. Bohl & Christian A. Salm & Michael Schuppli, 2011. "Price discovery and investor structure in stock index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(3), pages 282-306, March.
    38. 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.
    39. Imad A. Moosa & Param Silvapulle & Mervyn Silvapulle, 2003. "Testing for Temporal Asymmetry in the Price‐Volume Relationship," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 373-389, October.
    40. Chordia, Tarun & Subrahmanyam, Avanidhar & Anshuman, V. Ravi, 2001. "Trading activity and expected stock returns," Journal of Financial Economics, Elsevier, vol. 59(1), pages 3-32, January.
    41. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    42. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    43. Moosa, Imad A. & Silvapulle, Param, 2000. "The price-volume relationship in the crude oil futures market Some results based on linear and nonlinear causality testing," International Review of Economics & Finance, Elsevier, vol. 9(1), pages 11-30, February.
    44. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    45. 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.
    46. Dietrich Domanski & Alexandra Heath, 2007. "Financial investors and commodity markets," BIS Quarterly Review, Bank for International Settlements, March.
    47. 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.
    48. Elyès Jouini & Clotilde Napp, 2008. "Are More Risk-Averse Agents More Optimistic? Insights from a Simple Rational Expectations Equilibrium Model," Post-Print halshs-00176630, HAL.
    49. 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.
    50. Fousekis, Panos & Tzaferi, Dimitra, 2019. "Price returns and trading volume changes in agricultural futures markets: An empirical analysis with quantile regressions," The Journal of Economic Asymmetries, Elsevier, vol. 19(C), pages 1-1.
    51. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    52. Qin, Zhenjiang, 2013. "Speculations in option markets enhance allocation efficiency with heterogeneous beliefs and learning," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4675-4694.
    53. Williams, Jeffrey C., 2001. "Commodity futures and options," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 13, pages 745-816, Elsevier.
    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. Xiaodong Huang & Chang Lei, 2023. "Covid-19 impact on financial growth and guidelines for green recovery in BRICS: fresh insights from econometric analysis," Economic Change and Restructuring, Springer, vol. 56(2), pages 1243-1261, April.

    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. 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.
    2. 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.
    3. 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.
    4. Doojin RYU & Hyein SHIM, 2017. "Intraday Dynamics of Asset Returns, Trading Activities, and Implied Volatilities: A Trivariate GARCH Framework," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 45-61, June.
    5. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    6. Holmes, Phil & Rougier, Jonathan, 2005. "Trading volume and contract rollover in futures contracts," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 317-338, March.
    7. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    8. 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.
    9. 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.
    10. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    11. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    12. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    13. Gagnon, Louis & Karolyi, G. Andrew, 2009. "Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 953-986, August.
    14. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    15. Masahiro Watanabe, 2003. "A Model of Stochastic Liquidity," Yale School of Management Working Papers ysm385, Yale School of Management.
    16. 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).
    17. Nyborg, Kjell G. & Östberg, Per, 2014. "Money and liquidity in financial markets," Journal of Financial Economics, Elsevier, vol. 112(1), pages 30-52.
    18. Chordia, Tarun & Sarkar, Asani & Subrahmanyam, Avanidhar, 2005. "The Joint Dynamics of Liquidity, Returns, and Volatility Across Small and Large Firms," University of California at Los Angeles, Anderson Graduate School of Management qt6z81z2wc, Anderson Graduate School of Management, UCLA.
    19. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    20. Henryk Gurgul & Tomasz Wójtowicz, 2006. "Long-run properties of trading volume and volatility of equities listed in DJIA index," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(3-4), pages 29-56.

    More about this item

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:hal:journl:hal-03573202. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.