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Dynamic spillovers and network structure among commodity, currency, and stock markets

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  • Reboredo, Juan Carlos
  • Ugolini, Andrea
  • Hernandez, Jose Arreola

Abstract

This paper examines connectedness spillovers among three blocks of markets: commodities (agriculture, industrial metals, precious metals, energy, and livestock), currencies (EUR, GBP, CHF, JPY, AUD, CAD) and six major stock markets. At the aggregate level, we find that stock markets transmit the largest spillovers to the commodity and currency markets, while the commodity markets receive the largest spillovers from the other two markets. Stocks spill over more strongly on commodities than on currencies, commodities more on currencies than on stocks, and currencies more on commodities than on stocks, while stocks receive the smallest spillovers from the commodity and currency markets. At a more specific level, the currencies transmit/receive the largest spillovers to/from industrial metals and precious metals, and EUR and JPY are the largest and smallest transmitters/receivers of spillovers to/from the other currencies, respectively. The commodities transmit/receive the largest spillovers to/from the FTSE UK and TSX CA stock markets, the TOPIX JP and ASX AU transmit the smallest spillovers to the commodities, and currencies transmit/receive the largest spillovers to/from the S&P500 US and the TSX CA markets. These results may be useful to international investors for diversification purposes, risk management, and asset portfolio hedging.

Suggested Citation

  • Reboredo, Juan Carlos & Ugolini, Andrea & Hernandez, Jose Arreola, 2021. "Dynamic spillovers and network structure among commodity, currency, and stock markets," Resources Policy, Elsevier, vol. 74(C).
  • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721002774
    DOI: 10.1016/j.resourpol.2021.102266
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    2. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    3. Wang, Gang-Jin & Wan, Li & Feng, Yusen & Xie, Chi & Uddin, Gazi Salah & Zhu, You, 2023. "Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
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    5. Mensi, Walid & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Multiscale dependence, spillovers, and connectedness between precious metals and currency markets: A hedge and safe-haven analysis," Resources Policy, Elsevier, vol. 77(C).
    6. Yang, Cai & Wang, Xinyi & Gao, Wang, 2022. "Is Bitcoin a better hedging and safe-haven investment than traditional assets against currencies? Evidence from the time-frequency domain approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Yıldırım, Durmuş Çağrı & Erdoğan, Fatma & Tarı, Elif Nur, 2022. "Time-varying volatility spillovers between real exchange rate and real commodity prices for emerging market economies," Resources Policy, Elsevier, vol. 76(C).
    8. Li, Houjian & Li, Yanjiao & Guo, Lili, 2023. "Extreme risk spillover effect and dynamic linkages between uncertainty and commodity markets: A comparison between China and America," Resources Policy, Elsevier, vol. 85(PA).
    9. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    10. 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.
    11. Asadi, Mehrad & Tiwari, Aviral Kumar & Gholami, Samad & Ghasemi, Hamid Reza & Roubaud, David, 2023. "Understanding interconnections among steel, coal, iron ore, and financial assets in the US and China using an advanced methodology," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Guannan Wang & Juan Meng & Bin Mo, 2023. "Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies," Mathematics, MDPI, vol. 11(4), pages 1-25, February.
    13. Jorge Andrés Muñoz Mendoza & Carmen Lissette Veloso Ramos & Sandra María Sepúlveda Yelpo & Carlos Leandro Delgado Fuentealba & Edinson Edgardo Cornejo Saavedra, 2022. "Exchange Markets and Stock Markets Integration in Latin-America," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(3), pages 1-24, Julio - S.
    14. Costola, Michele & Iacopini, Matteo & Wichers, Casper, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," SAFE Working Paper Series 407, Leibniz Institute for Financial Research SAFE.

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    More about this item

    Keywords

    Currencies; Commodities; Stock markets; Spillovers;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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