IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i11d10.1007_s13198-024-02542-1.html
   My bibliography  Save this article

Dynamic correlation between hog futures and industry chain: an empirical study based on time-varying copula model

Author

Listed:
  • Hui Liu

    (NanFang College GuangZhou)

  • Xiaoying Zhong

    (NanFang College GuangZhou)

  • Zewu Jiang

    (NanFang College GuangZhou)

  • Shenghan Lai

    (NanFang College GuangZhou)

Abstract

To stabilize hog price and promote hog industry chain development, this research adopted a time-varying copula model to analyze the data collected in the time period of January 8th 2021 to May 31th 2023, encompassing the period when hog futures were listed. The results indicated a significant positive correlation between hog futures and soybean meal and while there is a certain degree of dependency in the relationship with corn spot prices in China. The lower tail correlation between hog futures and hog spot prices was higher than the upper tail correlation, suggesting that hog futures served as a tool for price discovery and guidance, especially during the periods when prices were declined. Therefore, it is advisable to expand the influence and utilization of the hog futures market. Doing so will allow us to more effectively leverage the hog futures market for price discovery and hedging strategies, ultimately contributing to the stability of the hog industry chain and supporting the sustainable development of the sector. This heightened influence will also bring benefits to policy makers, farmers, traders, and consumers by providing them with a more reliable and transparent pricing mechanism. This study provided a new perspective for the optimization of policy making and risk management in hog industry, offering valuable insights for participants and policymakers in hog supply chain.

Suggested Citation

  • Hui Liu & Xiaoying Zhong & Zewu Jiang & Shenghan Lai, 2024. "Dynamic correlation between hog futures and industry chain: an empirical study based on time-varying copula model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(11), pages 5356-5366, November.
  • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:11:d:10.1007_s13198-024-02542-1
    DOI: 10.1007/s13198-024-02542-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-024-02542-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-024-02542-1?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. Steffen Volkenand & Guenther Filler & Marlene Kionka & Martin Odening, 2020. "Duration dependence among agricultural futures with different maturities," Applied Economics Letters, Taylor & Francis Journals, vol. 27(2), pages 150-155, January.
    2. Joe, Harry, 1990. "Families of min-stable multivariate exponential and multivariate extreme value distributions," Statistics & Probability Letters, Elsevier, vol. 9(1), pages 75-81, January.
    3. Andrew McKenzie & Matthew Holt, 2002. "Market efficiency in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 34(12), pages 1519-1532.
    4. Colin A. Carter & Sandeep Mohapatra, 2008. "How Reliable Are Hog Futures as Forecasts?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 367-378.
    5. repec:bla:ecorec:v:0:y:1992:i:0:p:27-33 is not listed on IDEAS
    6. Christian M. Hafner & Hans Manner, 2012. "Dynamic stochastic copula models: estimation, inference and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 269-295, March.
    7. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    8. Raymond M. Leuthold & Philip Garcia & Nabil Chaherli, 1992. "Information, Pricing and Efficiency in Cash and Futures Markets: The Case of Hogs," The Economic Record, The Economic Society of Australia, vol. 68(S1), pages 27-33, December.
    Full references (including those not matched with items on IDEAS)

    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. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
    2. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    3. Zongwu Cai & Guannan Liu & Wei Long & Xuelong Luo, 2024. "Semiparametric Conditional Mixture Copula Models with Copula Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202401, University of Kansas, Department of Economics, revised Jan 2024.
    4. Javier Ojea Ferreiro, 2018. "Contagion spillovers between sovereign and financial European sector from a Delta CoVaR approach," Documentos de Trabajo del ICAE 2018-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    6. repec:kan:wpaper:202105 is not listed on IDEAS
    7. Guannan Liu & Wei Long & Bingduo Yang & Zongwu Cai, 2022. "Semiparametric estimation and model selection for conditional mixture copula models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 287-330, March.
    8. Rubén Loaiza‐Maya & Michael S. Smith & Worapree Maneesoonthorn, 2018. "Time series copulas for heteroskedastic data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 332-354, April.
    9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," 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 1127-1220, Elsevier.
    10. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    11. Liu, Mengqiao & Zhang, Yu Yvette & Jia, Ruixin, 2024. "Is the Chinese gold product a hedge or safe haven for Chinese overseas investors?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343698, Agricultural and Applied Economics Association.
    12. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    13. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    14. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    15. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    16. Zhige Wu & Alex Maynard & Alfons Weersink & Getu Hailu, 2018. "Asymmetric spot‐futures price adjustments in grain markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(12), pages 1549-1564, December.
    17. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
    18. Atina Ahdika & Arum Handini Primandari & Falah Novayanda Adlin, 2023. "Considering the temporal interdependence of human mobility and COVID-19 concerning Indonesia’s large-scale social distancing policies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2791-2810, June.
    19. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    20. David Zimmer, 2015. "Time-Varying Correlation in Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 51(1), pages 86-100, July.
    21. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.

    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:spr:ijsaem:v:15:y:2024:i:11:d:10.1007_s13198-024-02542-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.