IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v52y2020ics0275531919308578.html
   My bibliography  Save this article

Trading behaviour connectedness across commodity markets: Evidence from the hedgers’ sentiment perspective

Author

Listed:
  • Ji, Qiang
  • Bahloul, Walid
  • Geng, Jiang-Bo
  • Gupta, Rangan

Abstract

This paper analyses the connectedness network for commercial traders’ sentiment across agriculture, energy, metals and livestock futures markets. The findings find that: (a) producer/merchant/processor/user (PMPU) in agricultural and energy markets are mainly engaged in cross-hedging in the futures market, and most of them would avoid risks in these markets by operating in the metal markets, which can be considered safe for PMPU traders, and that the cross-hedging strategies may play the role of PMPU sentiment spillover across futures markets; (b) as index traders, the swap dealers operate more in two markets, namely between the agricultural and metal markets, or between the agricultural and energy markets; (c) the influence of geopolitical risks in some countries can affect the stability of energy markets, which in turn can cause PMPU system-wide connectedness.

Suggested Citation

  • Ji, Qiang & Bahloul, Walid & Geng, Jiang-Bo & Gupta, Rangan, 2020. "Trading behaviour connectedness across commodity markets: Evidence from the hedgers’ sentiment perspective," Research in International Business and Finance, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:riibaf:v:52:y:2020:i:c:s0275531919308578
    DOI: 10.1016/j.ribaf.2019.101114
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531919308578
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ribaf.2019.101114?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Aaron Tornell & Chunming Yuan, 2012. "Speculation and hedging in the currency futures markets: Are they informative to the spot exchange rates," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(2), pages 122-151, February.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Eric Chang & Ray Y. Chou & Edward F. Nelling, 2000. "Market volatility and the demand for hedging in stock index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(2), pages 105-125, February.
    4. Wang, Changyun, 2004. "Futures trading activity and predictable foreign exchange market movements," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1023-1041, May.
    5. Bahloul, Walid & Bouri, Abdelfettah, 2016. "The impact of investor sentiment on returns and conditional volatility in U.S. futures markets," Journal of Multinational Financial Management, Elsevier, vol. 36(C), pages 89-102.
    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. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    8. Sehgal, Sanjay & Pandey, Piyush & Diesting, Florent, 2017. "Examining dynamic currency linkages amongst South Asian economies: An empirical study," Research in International Business and Finance, Elsevier, vol. 42(C), pages 173-190.
    9. Krista Schwarz, 2012. "Are speculators informed?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 1-23, January.
    10. Henry L. Bryant & David A. Bessler & Michael S. Haigh, 2006. "Causality in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(11), pages 1039-1057, November.
    11. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    12. Yan‐ran Ma & Qiang Ji & Jiaofeng Pan, 2019. "Oil financialization and volatility forecast: Evidence from multidimensional predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(6), pages 564-581, September.
    13. Scott H. Irwin & Satoko Yoshimaru, 1999. "Managed futures, positive feedback trading, and futures price volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(7), pages 759-776, October.
    14. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    15. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    16. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    17. Chang, Eric C. & Michael Pinegar, J. & Schachter, Barry, 1997. "Interday variations in volume, variance and participation of large speculators," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 797-810, June.
    18. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    19. Changyun Wang, 2001. "Investor Sentiment and Return Predictability in Agricultural Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(10), pages 929-952, October.
    20. 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.
    21. Ing-Haw Cheng & Wei Xiong, 2014. "Why Do Hedgers Trade So Much?," The Journal of Legal Studies, University of Chicago Press, vol. 43(S2), pages 183-207.
    22. Ji, Qiang & Bouri, Elie & Roubaud, David, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 1-12.
    23. Sirimon Treepongkaruna & Stephen Gray, 2009. "Information and volatility links in the foreign exchange market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(2), pages 385-405, June.
    24. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    25. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    26. Sanders, Dwight R. & Boris, Keith & Manfredo, Mark, 2004. "Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports," Energy Economics, Elsevier, vol. 26(3), pages 425-445, May.
    27. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    28. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 81-127.
    29. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    30. Sakemoto, Ryuta, 2018. "Do precious and industrial metals act as hedges and safe havens for currency portfolios?," Finance Research Letters, Elsevier, vol. 24(C), pages 256-262.
    31. Bahloul, Walid & Bouri, Abdelfettah, 2016. "Profitability of return and sentiment-based investment strategies in US futures markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 254-270.
    32. Tamakoshi, Go & Hamori, Shigeyuki, 2016. "Time-varying co-movements and volatility spillovers among financial sector CDS indexes in the UK," Research in International Business and Finance, Elsevier, vol. 36(C), pages 288-296.
    33. Li, Sile & Lucey, Brian M., 2017. "Reassessing the role of precious metals as safe havens–What colour is your haven and why?," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 1-14.
    34. Walid Bahloul, 2018. "Short-term contrarian and sentiment by traders’ types on futures markets," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 10(4), pages 298-319, October.
    35. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    36. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    37. Bajo-Rubio, Oscar & Berke, Burcu & McMillan, David, 2017. "The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises," Research in International Business and Finance, Elsevier, vol. 41(C), pages 577-589.
    38. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    39. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    40. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    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. Geng, Jiang-Bo & Du, Ya-Juan & Ji, Qiang & Zhang, Dayong, 2021. "Modeling return and volatility spillover networks of global new energy companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    3. Geng, Jiang-Bo & Xu, Xiao-Yue & Ji, Qiang, 2020. "The time-frequency impacts of natural gas prices on US economic activity," Energy, Elsevier, vol. 205(C).
    4. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    5. Śmiech, Sławomir & Papież, Monika & Shahzad, Syed Jawad Hussain, 2020. "Spillover among financial, industrial and consumer uncertainties. The case of EU member states," International Review of Financial Analysis, Elsevier, vol. 70(C).
    6. Shao, Liuguo & Zhang, Hua & Chen, Jinyu & Zhu, Xuehong, 2021. "Effect of oil price uncertainty on clean energy metal stocks in China: Evidence from a nonparametric causality-in-quantiles approach," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 407-419.
    7. Bosch, David & Smimou, K., 2022. "Traders’ motivation and hedging pressure in commodity futures markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    8. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    9. Marfatia, Hardik & Zhao, Wan-Li & Ji, Qiang, 2020. "Uncovering the global network of economic policy uncertainty," Research in International Business and Finance, Elsevier, vol. 53(C).
    10. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    11. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
    12. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    13. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    14. Plakandaras, Vasilios & Tiwari, Aviral Kumar & Gupta, Rangan & Ji, Qiang, 2020. "Spillover of sentiment in the European Union: Evidence from time- and frequency-domains," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 105-130.
    15. Adeleke, Musefiu A. & Awodumi, Olabanji B. & Adewuyi, Adeolu O., 2022. "Return and volatility connectedness among commodity markets during major crises periods: Static and dynamic analyses with asymmetries," Resources Policy, Elsevier, vol. 79(C).
    16. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).

    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. Qiang Ji & Walid Bahloul & Jiang-bo Geng & Rangan Gupta, 2019. "Does Trading Behaviour Converge across Commodity Markets? Evidence from the Perspective of Hedgers’ Sentiment," Working Papers 201930, University of Pretoria, Department of Economics.
    2. Song, Yingjie & Ji, Qiang & Du, Ya-Juan & Geng, Jiang-Bo, 2019. "The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets," Energy Economics, Elsevier, vol. 84(C).
    3. Lee, Chien-Chiang & Zhou, Hegang & Xu, Chao & Zhang, Xiaoming, 2023. "Dynamic spillover effects among international crude oil markets from the time-frequency perspective," Resources Policy, Elsevier, vol. 80(C).
    4. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    5. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    6. Bahloul, Walid & Bouri, Abdelfettah, 2016. "The impact of investor sentiment on returns and conditional volatility in U.S. futures markets," Journal of Multinational Financial Management, Elsevier, vol. 36(C), pages 89-102.
    7. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    8. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    9. Thobekile Qabhobho & Anokye M. Adam & Anthony Adu-Asare Idun & Emmanuel Asafo-Adjei & Ebenezer Boateng, 2023. "Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 272-283, March.
    10. Dai, Zhifeng & Tang, Rui & Zhang, Xiaotong, 2023. "A new multilayer network for measuring interconnectedness among the energy firms," Energy Economics, Elsevier, vol. 124(C).
    11. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    12. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).
    13. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    14. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    15. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    16. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    17. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    18. Dai, Zhifeng & Zhang, Xiaotong & Yin, Zhujia, 2023. "Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 118(C).
    19. Yang, Lu & Hamori, Shigeyuki, 2021. "Systemic risk and economic policy uncertainty: International evidence from the crude oil market," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 142-158.
    20. Dahl, Roy Endré & Jonsson, Erlendur, 2018. "Volatility spillover in seafood markets," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 44-59.

    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:riibaf:v:52:y:2020:i:c:s0275531919308578. 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/ribaf .

    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.