IDEAS home Printed from https://ideas.repec.org/a/ags/polpwa/266522.html
   My bibliography  Save this article

Linear and Non-linear Relationships Between Shares of the Agrifood Industries of the Warsaw Stock Exchange. Risk Aspect

Author

Listed:
  • Pera, Jacek

Abstract

Despite a wide range of research on the agricultural market conducted so far, relatively little attention has been devoted to a comprehensive analysis of linear and non-linear causality in relation to the entire agri-food sector in Poland, in the context of risk. The objective of this study is therefore to analyze the linear and non-linear relationships between shares of WSE's agri-food industry sectors in terms of risk. The study covered three sectors of agri-food sector currently existing on the WSE (29 listed companies): Foods (21 listed companies), Agricultural Production and Fisheries (5 listed companies) and Food and Foodstuffs and fast-trafficking foodstuffs (3 listed companies). The existence of linear relationships was verified using the test procedure proposed by Hong, Liu, Wang and Łęt, while non-linear relationships were verified using the Diks-Panchenko, Orzeszko and Osińska tests’s. The study was carried out on the basis of data from companies of the agri-food industry listed on the Warsaw Stock Exchange in the period from 1 May 2010 to 1 May 2017. The chosen research methodology was dictated by the correlation with investment risk on the WSE. The strongest and most enduring dependencies have been found in the agricultural and fisheries sectors. In the foodstuff sector and the fast-marketable sector, the risk of investment in the listed companies was temporary.

Suggested Citation

  • Pera, Jacek, . "Linear and Non-linear Relationships Between Shares of the Agrifood Industries of the Warsaw Stock Exchange. Risk Aspect," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 17(32, Part ).
    • Handle: RePEc:ags:polpwa:266522
    DOI: 10.22004/ag.econ.266522
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/266522/files/2017_4_25.pdf
    Download Restriction: no
    File URL: https://ageconsearch.umn.edu/record/266522/files/2017_4_25.pdf?subformat=pdfa
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.266522?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
    ---><---

    References listed on IDEAS

    as
    1. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    2. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    3. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    4. Hoover,Kevin D., 2001. "Causality in Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521452175, November.
    5. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    6. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    7. Rembeza, Jerzy, 2009. "Powiązania pomiędzy cenami produktów rolnych w Polsce i krajach UE," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 7(22), pages 1-9, June.
    8. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    9. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    10. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    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. Stephanie-Carolin Grosche, 2014. "What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 279-302, June.
    2. Magdalena Osinska, 2011. "On the Interpretation of Causality in Granger’s Sense," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 129-140.
    3. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    4. Alexander Zeitlberger & Alexander Brauneis, 2016. "Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 149-176, March.
    5. Marcin Fałdziński & Magdalena Osińska & Tomasz Zdanowicz, 2012. "Detecting Risk Transfer in Financial Markets using Different Risk Measures," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(1), pages 45-64, March.
    6. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
    7. Xu, Haifeng & Hamori, Shigeyuki, 2012. "Dynamic linkages of stock prices between the BRICs and the United States: Effects of the 2008–09 financial crisis," Journal of Asian Economics, Elsevier, vol. 23(4), pages 344-352.
    8. Neto, David, 2022. "Revisiting spillovers between investor attention and cryptocurrency markets using noisy independent component analysis and transfer entropy," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    9. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    10. Md Nain & Bandi Kamaiah, 2014. "Financial development and economic growth in India: some evidence from non-linear causality analysis," Economic Change and Restructuring, Springer, vol. 47(4), pages 299-319, November.
    11. Parthajit Kayal & Moinak Maiti, 2023. "Examining the asymmetric information flow between pairs of gold, silver, and oil: a transfer entropy approach," SN Business & Economics, Springer, vol. 3(10), pages 1-22, October.
    12. Ari, Ibrahim & Akkas, Erhan & Asutay, Mehmet & Koç, Muammer, 2019. "Public and private investment in the hydrocarbon-based rentier economies: A case study for the GCC countries," Resources Policy, Elsevier, vol. 62(C), pages 165-175.
    13. Balcilar, Mehmet & Gungor, Hasan & Hammoudeh, Shawkat, 2015. "The time-varying causality between spot and futures crude oil prices: A regime switching approach," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 51-71.
    14. Xiaojuan He & Dervis Kirikkaleli & Melike Torun & Zecheng Li, 2021. "Modeling Economic Risk in the QISMUT Countries: Evidence From Nonlinear Cointegration Tests," SAGE Open, , vol. 11(4), pages 21582440211, October.
    15. Stern, David I. & Enflo, Kerstin, 2013. "Causality between energy and output in the long-run," Energy Economics, Elsevier, vol. 39(C), pages 135-146.
    16. Kanda, Patrick & Burke, Michael & Gupta, Rangan, 2018. "Time-varying causality between equity and currency returns in the United Kingdom: Evidence from over two centuries of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1060-1080.
    17. Zheng Fang & Jiang Yu, 2020. "The role of human capital in energy-growth nexus: an international evidence," Empirical Economics, Springer, vol. 58(3), pages 1225-1247, March.
    18. Nazlioglu, Saban & Soytas, Ugur & Gupta, Rangan, 2015. "Oil prices and financial stress: A volatility spillover analysis," Energy Policy, Elsevier, vol. 82(C), pages 278-288.
    19. 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).
    20. Hassan Tawakol A. Fadol, 2020. "Study the Possibility of Address Complex Models in Linear and Non-Linear Causal Relationships between Oil Price and GDP in KSA: Using the Combination of Toda-Yamamoto, Diks-Panchenko and VAR Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 672-678.

    More about this item

    Keywords

    ;
    ;
    ;

    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:ags:polpwa:266522. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/wesggpl.html .

    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.