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Macro News and Commodity Returns

Author

Listed:
  • Guglielmo Maria Caporale
  • Fabio Spagnolo
  • Nicola Spagnolo

Abstract

This paper adopts a VAR-GARCH approach to model the dynamic linkages between both the mean and the variance of macro news and commodity returns (Gold, Corn, Wheat, Soybeans, Silver, Platinum, Palladium, Copper, Aluminium and Crude Oil) over the period 01/01/2001-26/09/2014. The chosen specification also controls for the effect of the exchange rate. The results can be summarised as follows. Mean spillovers running from news to commodity returns are positive with the exception of Gold and Silver. Volatility spillovers are bigger in size and affect most commodity returns. Both firstand second moment linkages are stronger in the post-September 2008 period. Overall, our findings confirm that commodities, despite not being financial assets, are sensitive to macro news (especially their volatility), and also suggest that the global financial crisis has strengthened such linkages.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2017. "Macro News and Commodity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 68-80, January.
    • Handle: RePEc:wly:ijfiec:v:22:y:2017:i:1:p:68-80
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    Cited by:

    1. Osamah Al-Khazali & Elie Bouri & David Roubaud, 2018. "The impact of positive and negative macroeconomic news surprises: Gold versus Bitcoin," Economics Bulletin, AccessEcon, vol. 38(1), pages 373-382.
    2. Salisu, Afees A. & Vo, Xuan Vinh & Lucey, Brian, 2021. "Gold and US sectoral stocks during COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 57(C).
    3. Smales, L.A., 2017. "Commodity market volatility in the presence of U.S. and Chinese macroeconomic news," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 15-27.
    4. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    5. Hua, Renhai & Liu, Qingfu & Tse, Yiuman & Yu, Qin, 2023. "The impact of natural disaster risk on the return of agricultural futures," Journal of Asian Economics, Elsevier, vol. 87(C).
    6. Chi, Yeguang & El-Jahel, Lina & Vu, Thanh, 2024. "Novel and old news sentiment in commodity futures markets," Energy Economics, Elsevier, vol. 140(C).
    7. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High-Frequency Impact of Monetary Policy and Macroeconomic Surprises on US MSAs and Aggregate US Housing Returns and Volatility: A GJR-GARCH Approach," Working Papers 201817, University of Pretoria, Department of Economics.
    8. Tarek Chebbi, 2021. "The response of precious metal futures markets to unconventional monetary surprises in the presence of uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1897-1916, April.
    9. Tanin, Tauhidul Islam & Sarker, Ashutosh & Hammoudeh, Shawkat & Shahbaz, Muhammad, 2021. "Do volatility indices diminish gold's appeal as a safe haven to investors before and during the COVID-19 pandemic?," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 214-235.
    10. Smales, L.A. & Lucey, B.M., 2019. "The influence of investor sentiment on the monetary policy announcement liquidity response in precious metal markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 60(C), pages 19-38.
    11. Pham, Linh & Kamal, Javed Bin, 2024. "Blessings or curse: How do media climate change concerns affect commodity tail risk spillovers?," Journal of Commodity Markets, Elsevier, vol. 34(C).
    12. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).
    13. Siwen Zhou, 2021. "Exploring the driving forces of the Bitcoin currency exchange rate dynamics: an EGARCH approach," Empirical Economics, Springer, vol. 60(2), pages 557-606, February.
    14. Wen, Shaobo & An, Haizhong & Huang, Shupei & Liu, Xueyong, 2019. "Dynamic impact of China's stock market on the international commodity market," Resources Policy, Elsevier, vol. 61(C), pages 564-571.
    15. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    16. Jianhua Ding & Turen Guo & Bin Guo, 2018. "Fat Tails, Value at Risk, and the Palladium Returns," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 7(2), pages 95-103, May.
    17. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Fabio & Spagnolo, Nicola, 2022. "Cross-border portfolio flows and news media coverage," Journal of International Money and Finance, Elsevier, vol. 126(C).
    18. 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).
    19. Diandian Ma & Benfu Lv & Xuerong Li & Xiuting Li & Shuqin Liu, 2023. "Heterogeneous Impacts of Policy Sentiment with Different Themes on Real Estate Market: Evidence from China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    20. Sobti, Neharika, 2025. "What triggers intraday price jumps and co-jumps in gold?," International Review of Financial Analysis, Elsevier, vol. 105(C).
    21. Mukherjee, Abhiroop & Panayotov, George & Shon, Janghoon, 2021. "Eye in the sky: Private satellites and government macro data," Journal of Financial Economics, Elsevier, vol. 141(1), pages 234-254.
    22. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    23. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High Frequency Impact Of Monetary Policy And Macroeconomic Surprises On Us Msas, Aggregate Us Housing Returns And Asymmetric Volatility," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 204-229, December.
    24. Walid Bahloul & Rangan Gupta, 2018. "Impact of macroeconomic news surprises and uncertainty for major economies on returns and volatility of oil futures," International Economics, CEPII research center, issue 156, pages 247-253.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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