IDEAS home Printed from https://ideas.repec.org/a/spr/jecfin/v48y2024i1d10.1007_s12197-023-09647-6.html
   My bibliography  Save this article

Quantile coherency of futures prices in palm and soybean oil markets

Author

Listed:
  • Panos Fousekis

    (Aristotle University)

Abstract

The objective of the present work is to investigate the contemporaneous price co-movement in the futures markets of soybean and palm oil. This is pursued using quantile coherency (a statistical tool that allows for both frequency- and quantile-dependent linkages between stochastic processes) and daily futures prices from 2015 to 2023. The empirical findings suggest: (a) The co-movement between palm and soybean oil prices is not very high and, at the same time, it is asymmetric; prices in the two markets are more likely to crash than to boom together. (b) The intensity of co-movement tends to increase monotonically with the time-scale considered. However, the bulk of the adjustments to shocks tend to be completed within 1 month; the differences between coherency estimates in the medium- and in the long-run are rather small. (c) Price co-movement appears to be driven by both pure (short-run) contagion as well as by fundamental-based (long-run) contagion.

Suggested Citation

  • Panos Fousekis, 2024. "Quantile coherency of futures prices in palm and soybean oil markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(1), pages 129-141, March.
    • Handle: RePEc:spr:jecfin:v:48:y:2024:i:1:d:10.1007_s12197-023-09647-6
    DOI: 10.1007/s12197-023-09647-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12197-023-09647-6
    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/s12197-023-09647-6?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. Mensi, Walid & Lee, Yun-Jung & Vo, Xuan Vinh & Yoon, Seong-Min, 2021. "Quantile connectedness among gold, gold mining, silver, oil and energy sector uncertainty indexes," Resources Policy, Elsevier, vol. 74(C).
    2. Bodart, Vincent & Candelon, Bertrand, 2009. "Evidence of interdependence and contagion using a frequency domain framework," Emerging Markets Review, Elsevier, vol. 10(2), pages 140-150, June.
    3. Gallegati, Marco, 2012. "A wavelet-based approach to test for financial market contagion," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3491-3497.
    4. Xinquan Zhou & Guillaume Bagnarosa & Alexandre Gohin & Joost M.E. Pennings & Philippe Debie, 2023. "Microstructure and high-frequency price discovery in the soybean complex," Post-Print hal-04059421, HAL.
    5. A. D. Owen & K. Chowdhury & J. R. R. Garrido, 1997. "Price interrelationships in the vegetable and tropical oils market," Applied Economics, Taylor & Francis Journals, vol. 29(1), pages 119-124.
    6. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    7. Fernández-Macho, Javier, 2018. "Time-localized wavelet multiple regression and correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1226-1238.
    8. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    9. Jesús Otero & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "Multivariate Cointegration and Temporal Aggregation: Some Further Simulation Results," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 59-70, January.
    10. Georgios Bampinas & Theodore Panagiotidis, 2017. "Oil and stock markets before and after financial crises: A local Gaussian correlation approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(12), pages 1179-1204, December.
    11. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    12. In, Francis & Inder, Brett, 1997. "Long‐run Relationships Between World Vegetable Oil Prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 41(4), pages 1-16.
    13. Wang, Suhui, 2023. "Tail dependence, dynamic linkages, and extreme spillover between the stock and China's commodity markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    14. Kley, Tobias, 2016. "Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i03).
    15. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    16. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Balli, Faruk & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency domain quantile coherence of emerging stock markets with gold and oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    17. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    18. Zhou, Xinquan & Bagnarosa, Guillaume & Gohin, Alexandre & Pennings, Joost M.E. & Debie, Philippe, 2023. "Microstructure and high-frequency price discovery in the soybean complex," Journal of Commodity Markets, Elsevier, vol. 30(C).
    19. Borri, Nicola, 2019. "Conditional tail-risk in cryptocurrency markets," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 1-19.
    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. Fousekis, Panos, 2024. "Connectedness between conventional and organic milk prices in the USA," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    2. Elie Bouri & Rangan Gupta & Shixuan Wang, 2019. "Contagion between Stock and Real Estate Markets: International Evidence from a Local Gaussian Correlation Approach," Working Papers 201917, University of Pretoria, Department of Economics.
    3. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
    4. Zhang, Yan & Xu, Yushi & Zhu, Xintong & Huang, Jionghao, 2024. "Coal price shock propagation through sectoral financial interconnectedness in China's stock market: Quantile coherency network modelling and shock decomposition analysis," Journal of Commodity Markets, Elsevier, vol. 34(C).
    5. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    6. Hanif, Waqas & Hadhri, Sinda & El Khoury, Rim, 2024. "Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers," Journal of Commodity Markets, Elsevier, vol. 34(C).
    7. Mudassar Hasan & Muhammad Abubakr Naeem & Muhammad Arif & Syed Jawad Hussain Shahzad & Xuan Vinh Vo, 2022. "Liquidity connectedness in cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    8. Elie Bouri & Rangan Gupta & Shixuan Wang, 2022. "Nonlinear contagion between stock and real estate markets: International evidence from a local Gaussian correlation approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2089-2109, April.
    9. Kołodziejczyk, Hanna, 2023. "Stablecoins as diversifiers, hedges and safe havens: A quantile coherency approach," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    10. Mensi, Walid & Gök, Remzi & Gemici, Eray & Vo, Xuan Vinh & Kang, Sang Hoon, 2025. "Extreme dependence, connectedness, and causality between US sector stocks and oil shocks," International Review of Economics & Finance, Elsevier, vol. 98(C).
    11. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2015. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 575-611, December.
    13. Saba Qureshi & Muhammad Aftab, 2023. "Exchange Rate Interdependence in ASEAN Markets: A Wavelet Analysis," Global Business Review, International Management Institute, vol. 24(6), pages 1180-1204, December.
    14. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    15. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Time–frequency quantile dependence between Bitcoin and global equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    16. Vácha, Lukáš & Šmolík, Filip & Baxa, Jaromír, 2019. "Comovement and disintegration of EU sovereign bond markets during the crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 541-556.
    17. Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    18. Baur, Dirk G. & Hoang, Lai T., 2021. "A crypto safe haven against Bitcoin," Finance Research Letters, Elsevier, vol. 38(C).
    19. Georgios Bampinas & Theodore Panagiotidis, 2017. "Oil and stock markets before and after financial crises: A local Gaussian correlation approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(12), pages 1179-1204, December.
    20. Naeem, Muhammad Abubakr & Agyemang, Abraham & Hasan Chowdhury, Md Iftekhar & Hasan, Mudassar & Shahzad, Syed Jawad Hussain, 2022. "Precious metals as hedge and safe haven for African stock markets," Resources Policy, Elsevier, vol. 78(C).

    More about this item

    Keywords

    Price co-movement; Quantile-dependent; Frequency-dependent; Palm and soybean oil; Asymmetry;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

    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:spr:jecfin:v:48:y:2024:i:1:d:10.1007_s12197-023-09647-6. 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.