IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v43y2021ics1544612321000805.html
   My bibliography  Save this article

Patterns of Spillover in Energy, Agricultural, and Metal Markets: A Connectedness Analysis for Years 1780-2020

Author

Listed:
  • Umar, Zaghum
  • Riaz, Yasir
  • Zaremba, Adam

Abstract

This paper investigates the connectedness of nine different commodity classes over more than two centuries. The data sample includes monthly observations from the years 1780 to 2020. Our static analysis shows precious metals, soft foods, grains and, base metals as a net transmitter of spillover. The time-varying analysis shows that connectedness increases during economic crises, political uncertainty, and commodity-driven supply shocks. Our results have important implications for regulators, portfolio managers, and policymakers.

Suggested Citation

  • Umar, Zaghum & Riaz, Yasir & Zaremba, Adam, 2021. "Patterns of Spillover in Energy, Agricultural, and Metal Markets: A Connectedness Analysis for Years 1780-2020," Finance Research Letters, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321000805
    DOI: 10.1016/j.frl.2021.101999
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321000805
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.101999?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. 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.
    2. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    3. Samuel Bazzi & Christopher Blattman, 2014. "Economic Shocks and Conflict: Evidence from Commodity Prices," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(4), pages 1-38, October.
    4. Erten, Bilge & Ocampo, José Antonio, 2013. "Super Cycles of Commodity Prices Since the Mid-Nineteenth Century," World Development, Elsevier, vol. 44(C), pages 14-30.
    5. Yoon, Seong-Min & Al Mamun, Md & Uddin, Gazi Salah & Kang, Sang Hoon, 2019. "Network connectedness and net spillover between financial and commodity markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 801-818.
    6. 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.
    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. Umar, Zaghum & Yousaf, Imran & Gubareva, Mariya & Vo, Xuan Vinh, 2022. "Spillover and risk transmission between the term structure of the US interest rates and Islamic equities," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    2. Ghosh, Bikramaditya & Pham, Linh & Teplova, Tamara & Umar, Zaghum, 2023. "COVID-19 and the quantile connectedness between energy and metal markets," Energy Economics, Elsevier, vol. 117(C).
    3. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    4. Alam, Md Rafayet & Forhad, Md. Abdur Rahman & Sah, Nilesh B., 2022. "Consumption- and speculation-led change in demand for oil and the response of base metals: A Markov-switching approach," Finance Research Letters, Elsevier, vol. 47(PB).
    5. Cheng, Sheng & Zhang, Zongyou & Cao, Yan, 2022. "Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
    6. Umar, Zaghum & Mokni, Khaled & Manel, Youssef & Gubareva, Mariya, 2024. "Dynamic spillover between oil price shocks and technology stock indices: A country level analysis," Research in International Business and Finance, Elsevier, vol. 69(C).
    7. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    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. Umar, Zaghum & Yousaf, Imran & Aharon, David Y., 2021. "The relationship between yield curve components and equity sectorial indices: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    10. Bossman, Ahmed & Umar, Zaghum & Agyei, Samuel Kwaku & Teplova, Tamara, 2023. "The impact of the US yield curve on sub-Saharan African equities," Finance Research Letters, Elsevier, vol. 53(C).
    11. Umar, Zaghum & Manel, Youssef & Riaz, Yasir & Gubareva, Mariya, 2021. "Return and volatility transmission between emerging markets and US debt throughout the pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    12. 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).
    13. Aloui, Riadh & Ben Jabeur, Sami & Rezgui, Hichem & Ben Arfi, Wissal, 2023. "Geopolitical risk and commodity future returns: Fresh insights from dynamic copula conditional value-at-risk approach," Resources Policy, Elsevier, vol. 85(PB).
    14. Arfaoui, Nadia & Yousaf, Imran & Jareño, Francisco, 2023. "Return and volatility connectedness between gold and energy markets: Evidence from the pre- and post-COVID vaccination phases," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 617-634.
    15. Jana, Rabin K. & Ghosh, Indranil, 2023. "Time-varying relationship between geopolitical uncertainty and agricultural investment," Finance Research Letters, Elsevier, vol. 52(C).
    16. Adewuyi, Adeolu O. & Adeleke, Musefiu A. & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel, 2023. "Dynamic linkages between shipping and commodity markets: Evidence from a novel asymmetric time-frequency method," Resources Policy, Elsevier, vol. 83(C).
    17. Cheng Xin & Kailin Ji & Hao Chang & Yang Li & Ya-Qiong Liu, 2022. "Price Co-Movement between Electrical Equipment and Metal Commodities—A Time-Frequency Analysis," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
    18. Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2023. "Asymmetric effects of market uncertainties on agricultural commodities," Energy Economics, Elsevier, vol. 127(PB).

    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. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    2. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
    3. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    4. Muhammad Abubakr Naeem & Saqib Farid & Safwan Mohd Nor & Syed Jawad Hussain Shahzad, 2021. "Spillover and Drivers of Uncertainty among Oil and Commodity Markets," Mathematics, MDPI, vol. 9(4), pages 1-26, February.
    5. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    6. Youtao Xiang & Sumuya Borjigin, 2024. "High–low volatility spillover network between economic policy uncertainty and commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1295-1319, August.
    7. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2020. "Extreme spillovers across Asian-Pacific currencies: A quantile-based analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    8. Mensi, Walid & Ziadat, Salem Adel & Rababa'a, Abdel Razzaq Al & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Oil, gold and international stock markets: Extreme spillovers, connectedness and its determinants," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 1-17.
    9. Rehman, Mobeen Ur & Vo, Xuan Vinh & Ko, Hee-Un & Ahmad, Nasir & Kang, Sang Hoon, 2023. "Quantile connectedness between Chinese stock and commodity futures markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    10. Boakye, Robert Owusu & Mensah, Lord Kwaku & Kang, Sang Hoon & Osei, Kofi Acheampong, 2023. "Foreign exchange market return spillovers and connectedness among African countries," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Zhuhua Jiang & Rim El Khoury & Muneer M. Alshater & Seong‐Min Yoon, 2024. "Impact of global macroeconomic factors on spillovers among Australian sector markets: Fresh findings from a wavelet‐based analysis," Australian Economic Papers, Wiley Blackwell, vol. 63(1), pages 78-105, March.
    12. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    13. Huifu Nong, 2024. "Connectedness and risk transmission of China’s stock and currency markets with global commodities," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-24, February.
    14. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    15. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    16. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    17. Liow, Kim Hiang & Huang, Yuting, 2018. "The dynamics of volatility connectedness in international real estate investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 195-210.
    18. Wang, Peiwen & Chen, Minghua & Wu, Ji & Yan, Yuanyun, 2023. "Do peer effects matter in bank risk? Some cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    19. Siddique, Md Abubakar & Nobanee, Haitham & Karim, Sitara & Naz, Farah, 2022. "Investigating the role of metal and commodity classes in overcoming resource destabilization," Resources Policy, Elsevier, vol. 79(C).
    20. Le, Trung H. & Pham, Linh & Do, Hung X., 2023. "Price risk transmissions in the water-energy-food nexus: Impacts of climate risks and portfolio implications," Energy Economics, Elsevier, vol. 124(C).

    More about this item

    Keywords

    Commodities; Connectedness; Early commodity prices; Network analysis; Variance decompositions;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    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:eee:finlet:v:43:y:2021:i:c:s1544612321000805. 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/frl .

    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.