5
views
0
recommends
+1 Recommend
3 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Multi-Frequency Information Flows between Global Commodities and Uncertainties: Evidence from COVID-19 Pandemic

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Owing to the adverse impact of the COVID-19 pandemic on world economies, it is expected that information flows between commodities and uncertainties have been transformed. Accordingly, the resulting twisted risk among commodities and related uncertainties is presumed to rise during stressed market conditions. Therefore, investors feel pressured to find safe haven investments during the pandemic. For this reason, we model a mixture of asymmetric and non-linear bi-directional causality between global commodities and uncertainties at different frequencies through the information flow theory. Consequently, we utilise the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the Rényi effective transfer entropy techniques to establish the dynamic flow of information. The intrinsic mode functions (IMFs) from the CEEMDAN are carefully extracted into multi-frequencies through cluster analysis to reconstruct the series into high, medium, and low frequencies in addition to the residue. We utilise daily data from December 31st, 2019, to March 31st, 2021, to provide insights into the COVID-19 pandemic. The correlation coefficients and variances demonstrate that the high frequency (IMFs 1–4) which measures the short-term dynamics is the dominant frequency, suggesting short-lived market fluctuations relative to real economic growth for institutional investors. Moreover, outcomes from the multi-frequency entropy indicate a negative bi-directional causality of information flow between global commodities and uncertainties, especially in the long term. Generally, the findings present pertinent inferences for portfolio diversification, policy decisions, and risk management schemes for global commodities and markets volatilities. We, therefore, advocate that market volatilities act as effective hedges for global commodities, and they clearly act as balancing assets rather than substitutes in the long-term dynamics of the COVID-19 pandemic. Investors who delayed in investing within financial markets of commodities and market volatilities are likely to minimise their portfolio risks.

          Related collections

          Most cited references99

          • Record: found
          • Abstract: not found
          • Article: not found

          A Mathematical Theory of Communication

          C. Shannon (1948)
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              ENSEMBLE EMPIRICAL MODE DECOMPOSITION: A NOISE-ASSISTED DATA ANALYSIS METHOD

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Complexity
                Complexity
                Hindawi Limited
                1099-0526
                1076-2787
                May 11 2022
                May 11 2022
                : 2022
                : 1-32
                Affiliations
                [1 ]Department of Finance, School of Business, University of Cape Coast, Cape Coast, Ghana
                [2 ]Directorate of Finance, University of Cape Coast, Cape Coast, Ghana
                Article
                10.1155/2022/6499876
                f0993f5a-7e77-4e70-abf1-146833b14d61
                © 2022

                https://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article