Evidence map›Paper›PMID 37007434›Full record

ArticleSN business & economics2023

High frequency volatility spillover between oil and non-energy commodities during crisis and tranquil periods.

Mutaju Isaack Marobhe, Jonathan Mukiza Peter Kansheba

Open access · bronzeAbstract read
In one paragraph

Article in SN business & economics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 4 countries.

Mutaju Isaack MarobheDepartment of Finance and Accounting, Tanzania Institute of Accountancy, Dar es Salaam, Tanzania.ORCID 0000-0002-5344-4778
Jonathan Mukiza Peter KanshebaDepartment of Management, School of Business and Law, Universitetet i Agder, Kristiansand, Vest-Agder, Norway.
Institute of Accountancy Arusha · TZUniversity of Agder · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this article, we scrutinize volatility spillover between oil and individual non-energy commodities during crisis and non-crisis periods. We use high-frequency data to capture the effects of both the global financial crisis (2008) and the COVID-19 pandemic between 2008 and 2022. To this end, we utilize wavelet coherence analysis to diagnose the magnitudes of dynamic co-movements and lead-lag effects between commodities. Our results provide evidence of strong coherence between oil and the majority of individual non-energy commodities during both crises. Precious metals were generally found to exhibit heightened levels of co-movement with oil as opposed to other non-energy commodities. On the other hand, weak co-movements were found between oil and a few commodities, namely soy, wheat, zinc, and tin. The lead-lag effects of oil on agricultural commodities, base metals, and precious metals were evident, especially during crisis periods. However, aluminium and precious metals, especially gold, silver, and palladium, also had a lead-lag effect on oil at different points in time, including during the pandemic. We further utilize dynamic frequency-domain connectedness for capturing pairwise volatility spillover indices, with the results providing evidence of heightened volatility spillovers during turbulent times. Our findings have significant implications for retail investors, portfolio managers, and policymakers.

Indexed as

Agricultural commoditiesBase metalsCOVID-19OilPrecious metalsThe global financial crisis

Identifiers

PMID37007434
PMCPMC10049898
OpenAlexW4361303515

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.