IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i5p280-d1151894.html
   My bibliography  Save this article

Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict

Author

Listed:
  • Antonis A. Michis

    (Central Bank of Cyprus, Nicosia 1076, Cyprus
    Department of Business Administration, School of Business and Law, Frederick University, Nicosia 1036, Cyprus)

Abstract

We examined the evolution of cross-market linkages between four major precious metals and US stock returns, before (Phase I) and after (Phase II) the COVID-19 outbreak. Phase II was also extended to encompass the Ukrainian conflict, which prolonged the period of uncertainty in financial markets. Due to the increase in volatility observed in Phase II, we used a heteroskedasticity-adjusted correlation coefficient to examine the evolution of correlation changes since the COVID-19 outbreak. We also propose a relevant dissimilarity measure in multidimensional scaling analysis that can be used for depicting associations between financial returns in turbulent times. Our results suggest that (i) the correlation levels of gold, silver, platinum, and palladium returns with US stock returns have not changed substantially since the COVID-19 outbreak, and (ii) all precious metal returns exhibit movements that are less synchronized with US stock returns, with palladium and gold being the least synchronized.

Suggested Citation

  • Antonis A. Michis, 2023. "Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict," JRFM, MDPI, vol. 16(5), pages 1-18, May.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:5:p:280-:d:1151894
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/5/280/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/16/5/280/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antonis A. Michis, 2022. "Multiscale Partial Correlation Clustering of Stock Market Returns," JRFM, MDPI, vol. 15(1), pages 1-22, January.
    2. Germán G. Creamer & Chihoon Lee, 2019. "A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1531-1542, September.
    3. Antonis A. Michis, 2021. "Wavelet Multidimensional Scaling Analysis of European Economic Sentiment Indicators," Journal of Classification, Springer;The Classification Society, vol. 38(3), pages 443-480, October.
    4. Sadorsky, Perry, 2014. "Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat," Energy Economics, Elsevier, vol. 43(C), pages 72-81.
    5. Geertsema, Paul & Lu, Helen, 2020. "The correlation structure of anomaly strategies," Journal of Banking & Finance, Elsevier, vol. 119(C).
    6. Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
    7. Dror Y. Kenett & Xuqing Huang & Irena Vodenska & Shlomo Havlin & H. Eugene Stanley, 2015. "Partial correlation analysis: applications for financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 569-578, April.
    8. Thomas Chiang & Lin Tan & Huimin Li, 2007. "Empirical analysis of dynamic correlations of stock returns: evidence from Chinese A-share and B-share markets," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 651-667.
    9. Peng, Xiaofan, 2020. "Do precious metals act as hedges or safe havens for China's financial markets?," Finance Research Letters, Elsevier, vol. 37(C).
    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. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    2. Antonis A. Michis, 2022. "Multiscale Partial Correlation Clustering of Stock Market Returns," JRFM, MDPI, vol. 15(1), pages 1-22, January.
    3. Jingying Yang & Guishu Bai & Mei Yan, 2023. "Minimum Residual Sum of Squares Estimation Method for High-Dimensional Partial Correlation Coefficient," Mathematics, MDPI, vol. 11(20), pages 1-22, October.
    4. Chunhachinda, Pornchai & de Boyrie, Maria E. & Pavlova, Ivelina, 2019. "Measuring the hedging effectiveness of commodities," Finance Research Letters, Elsevier, vol. 30(C), pages 201-207.
    5. 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).
    6. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    7. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    8. 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).
    9. Gabauer, David & Chatziantoniou, Ioannis & Stenfors, Alexis, 2023. "Model-free connectedness measures," Finance Research Letters, Elsevier, vol. 54(C).
    10. Morema, Kgotso & Bonga-Bonga, Lumengo, 2020. "The impact of oil and gold price fluctuations on the South African equity market: Volatility spillovers and financial policy implications," Resources Policy, Elsevier, vol. 68(C).
    11. Geraci, Marco Valerio & Gnabo, Jean-Yves & Veredas, David, 2023. "Common short selling and excess comovement: Evidence from a sample of LSE stocks," Journal of Financial Markets, Elsevier, vol. 65(C).
    12. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    13. Zhao, Xiaojun & Shang, Pengjian & Lin, Aijing, 2017. "Transfer mutual information: A new method for measuring information transfer to the interactions of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 517-526.
    14. François-Éric Racicot & Raymond Théoret, 2022. "Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios: a nonlinear VAR approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    15. Wang, Xunxiao & Wu, Chongfeng, 2018. "Asymmetric volatility spillovers between crude oil and international financial markets," Energy Economics, Elsevier, vol. 74(C), pages 592-604.
    16. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    17. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela Ben, 2015. "Price discovery and regime shift behavior in the relationship between sharia stocks and sukuk: A two-state Markov switching analysis," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 121-135.
    18. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    19. Kanjamapornkul, K. & Pinčák, Richard & Bartoš, Erik, 2016. "The study of Thai stock market across the 2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 117-133.
    20. Farid, Saqib & Kayani, Ghulam Mujtaba & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain, 2021. "Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 72(C).

    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:gam:jjrfmx:v:16:y:2023:i:5:p:280-:d:1151894. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.