IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v81y2023ics0301420723000041.html
   My bibliography  Save this article

Dynamic volatility contagion across the Baltic dry index, iron ore price and crude oil price under the COVID-19: A copula-VAR-BEKK-GARCH-X approach

Author

Listed:
  • Chen, Yufeng
  • Xu, Jing
  • Miao, Jiafeng

Abstract

The international dry bulk shipping market is closely related to the commodity and crude oil markets. At the same time, the Baltic Dry Index (BDI) is usually considered as the main indicator of economic activities. In order to clarify the correlations between the three markets, this paper employs the Copula-VAR-BEKK-GARCH-X model to explore the dynamic dependence and volatility spillovers between the Baltic Dry Index, iron ore price and Brent crude oil price. In addition, the influence of exogenous variables (BDI/Iron ore/Brent) on market volatility and co-volatility is further discussed. The empirical results indicate that: first, the dependence between BDI, iron ore price and Brent crude oil price is time-varying and time-lag, especially when suffering from major crises. Second, dynamic dependencies and volatility spillovers between BDI, iron ore price and Brent crude oil price have significantly strengthened during COVID-19, manifesting that the impact of market turmoil has reinforced the linkages between markets. Third, this paper reaffirms the role of BDI as an intra and inter market indicator, while finding indication that iron ore is beginning to emerge its predictive indicator post-COVID-19. The results are not only conducive to the investment portfolio selection of individual investors and institutional investors, but also beneficial to formulating trade policies or shipping strategies by countries or shipping organizations.

Suggested Citation

  • Chen, Yufeng & Xu, Jing & Miao, Jiafeng, 2023. "Dynamic volatility contagion across the Baltic dry index, iron ore price and crude oil price under the COVID-19: A copula-VAR-BEKK-GARCH-X approach," Resources Policy, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:jrpoli:v:81:y:2023:i:c:s0301420723000041
    DOI: 10.1016/j.resourpol.2023.103296
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723000041
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103296?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. Shun Chen & Hilde Meersman & Eddy van de Voorde, 2010. "Dynamic interrelationships in returns and volatilities between Capesize and Panamax markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(1), pages 65-90, March.
    2. Raquel L�pez, 2014. "Volatility contagion across commodity, equity, foreign exchange and Treasury bond markets," Applied Economics Letters, Taylor & Francis Journals, vol. 21(9), pages 646-650, June.
    3. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    4. Wolfgang Drobetz & Dirk Schilling & Lars Tegtmeier, 2010. "Common risk factors in the returns of shipping stocks," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(2), pages 93-120, March.
    5. Juncal Cunado & Soojin Jo & Fernando Perez de Gracia, 2015. "Revisiting the Macroeconomic Impact of Oil Shocks in Asian Economies," Staff Working Papers 15-23, Bank of Canada.
    6. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    7. Cheng, Dong & Shi, Xunpeng & Yu, Jian & Zhang, Dayong, 2019. "How does the Chinese economy react to uncertainty in international crude oil prices?," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 147-164.
    8. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    9. Ma, Yiqun & Wang, Junhao, 2019. "Co-movement between oil, gas, coal, and iron ore prices, the Australian dollar, and the Chinese RMB exchange rates: A copula approach," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    10. Lutz Kilian & Robert J. Vigfusson, 2017. "The Role of Oil Price Shocks in Causing U.S. Recessions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1747-1776, December.
    11. Ghose, Devajyoti & Kroner, Kenneth F., 1995. "The relationship between GARCH and symmetric stable processes: Finding the source of fat tails in financial data," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 225-251, September.
    12. Cunado, Juncal & Jo, Soojin & Perez de Gracia, Fernando, 2015. "Macroeconomic impacts of oil price shocks in Asian economies," Energy Policy, Elsevier, vol. 86(C), pages 867-879.
    13. Lin, Arthur J. & Chang, Hai Yen & Hsiao, Jung Lieh, 2019. "Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 265-283.
    14. Chen, Yufeng & Wang, Chuwen & Zhu, Zhitao, 2022. "Toward the integration of European gas futures market under COVID-19 shock: A quantile connectedness approach," Energy Economics, Elsevier, vol. 114(C).
    15. 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.
    16. Bauwens, Luc & Lubrano, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 321-342, August.
    17. Chen, Yufeng & Xu, Jing, 2023. "Digital transformation and firm cost stickiness: Evidence from China," Finance Research Letters, Elsevier, vol. 52(C).
    18. Manolis Kavussanos, 1997. "The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 433-443.
    19. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    20. Chen, Yufeng & Xu, Jing & Hu, May, 2022. "Asymmetric volatility spillovers and dynamic correlations between crude oil price, exchange rate and gold price in BRICS," Resources Policy, Elsevier, vol. 78(C).
    21. Jayasinghe, Prabhath & Tsui, Albert K. & Zhang, Zhaoyong, 2014. "New estimates of time-varying currency betas: A trivariate BEKK approach," Economic Modelling, Elsevier, vol. 42(C), pages 128-139.
    22. Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
    23. Han, Liyan & Wan, Li & Xu, Yang, 2020. "Can the Baltic Dry Index predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 32(C).
    24. Yimiao Gu & Zhenxi Chen & Donald Lien, 2019. "Baltic Dry Index and iron ore spot market: dynamics and interactions," Applied Economics, Taylor & Francis Journals, vol. 51(35), pages 3855-3863, July.
    25. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    26. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    27. Ruan, Qingsong & Wang, Yao & Lu, Xinsheng & Qin, Jing, 2016. "Cross-correlations between Baltic Dry Index and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 278-289.
    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. Cheng-Wen Chang & Ming-Hsien Hsueh & Chia-Nan Wang & Cheng-Chun Huang, 2023. "Exploring the Factors Influencing the Impact of the COVID-19 Pandemic on Global Shipping: A Case Study of the Baltic Dry Index," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    2. Kyungbo Park & Hangook Kim & Jeonghwa Cha, 2023. "An Exploratory Study on the Development of a Crisis Index: Focusing on South Korea’s Petroleum Industry," Energies, MDPI, vol. 16(14), pages 1-24, July.
    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. Melike Bildirici & Işıl Şahin Onat & Özgür Ömer Ersin, 2023. "Forecasting BDI Sea Freight Shipment Cost, VIX Investor Sentiment and MSCI Global Stock Market Indicator Indices: LSTAR-GARCH and LSTAR-APGARCH Models," Mathematics, MDPI, vol. 11(5), pages 1-27, March.
    5. Chen, Yufeng & Msofe, Zulkifr Abdallah & Wang, Chuwen, 2024. "Asymmetric dynamic spillover and time-frequency connectedness in the oil-stock nexus under COVID-19 shock: Evidence from African oil importers and exporters," Resources Policy, Elsevier, vol. 90(C).
    6. Hoque, Mohammad Enamul & Sahabuddin, Mohammad & Bilgili, Faik, 2024. "Volatility interconnectedness among financial and geopolitical markets: Evidence from COVID-19 and Ukraine-Russia crises," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 303-320.
    7. Ji, Hao & Naeem, Muhammad & Zhang, Jing & Tiwari, Aviral Kumar, 2024. "Dynamic dependence and spillover among the energy related ETFs: From the hedging effectiveness perspective," Energy Economics, Elsevier, vol. 136(C).
    8. Kejin Wu & Sayar Karmakar & Rangan Gupta, 2023. "GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables," Papers 2308.13346, arXiv.org, revised Sep 2024.
    9. Marina Yu. Malkina, 2024. "Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 452-475.
    10. Su, Miao & Nie, Yufei & Li, Jiankun & Yang, Lin & Kim, Woohyoung, 2024. "Futures markets and the baltic dry index: A prediction study based on deep learning," Research in International Business and Finance, Elsevier, vol. 71(C).
    11. Liu, Zixin & Hu, Jun & Zhang, Shuguang & He, Zhipeng, 2024. "Risk spillovers among oil, gold, stock, and foreign exchange markets: Evidence from G20 economies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    12. Liu, Jiexian, 2024. "Analyzing the Co-movement of FinTech market efficiency and oil Resource efficiency: An Input-Output study," Resources Policy, Elsevier, vol. 90(C).
    13. Qin, Yun & Zhang, Zitao, 2024. "Transmission mechanisms of the effects of geopolitical risk on energy returns and volatility," International Review of Financial Analysis, Elsevier, vol. 95(PA).

    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. Lin, Arthur J. & Chang, Hai Yen & Hsiao, Jung Lieh, 2019. "Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 265-283.
    2. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Abakah, Emmanuel Joel Aikins & Abdullah, Mohammad & Dankwah, Boakye & Lee, Chi-Chuan, 2024. "Asymmetric dynamics between the Baltic Dry Index and financial markets during major global economic events," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    4. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    5. Ma, Yiqun, 2021. "Do iron ore, scrap steel, carbon emission allowance, and seaborne transportation prices drive steel price fluctuations?," Resources Policy, Elsevier, vol. 72(C).
    6. Bai, Xiwen & Lam, Jasmine Siu Lee, 2021. "Freight rate co-movement and risk spillovers in the product tanker shipping market: A copula analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    7. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    8. 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).
    9. Arunava Bandyopadhyay & Prabina Rajib, 2023. "The asymmetric relationship between Baltic Dry Index and commodity spot prices: evidence from nonparametric causality-in-quantiles test," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 217-237, June.
    10. Jiang, Zhuhua & Yoon, Seong-Min, 2020. "Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis," Energy Economics, Elsevier, vol. 90(C).
    11. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    12. Ma, Yiqun & Wang, Junhao, 2021. "Time-varying spillovers and dependencies between iron ore, scrap steel, carbon emission, seaborne transportation, and China's steel stock prices," Resources Policy, Elsevier, vol. 74(C).
    13. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    14. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    15. 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.
    16. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    17. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    18. Ma, Yiqun & Wang, Junhao, 2019. "Co-movement between oil, gas, coal, and iron ore prices, the Australian dollar, and the Chinese RMB exchange rates: A copula approach," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    19. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    20. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.

    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:jrpoli:v:81:y:2023:i:c:s0301420723000041. 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/inca/30467 .

    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.