Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches
We examine the time-frequency lead–lag relationships and the degree of integration between the US financial stress index and global commodity prices (i.e., oil, gold, silver, and cocoa) with data covering over 47 decades (January 1975 to December 2021). For this purpose, we resort to the bi- and mul...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Cogent Economics & Finance |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23322039.2022.2114161 |
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| _version_ | 1849717419552014336 |
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| author | Mohammed Armah Godfred Amewu Ahmed Bossman |
| author_facet | Mohammed Armah Godfred Amewu Ahmed Bossman |
| author_sort | Mohammed Armah |
| collection | DOAJ |
| description | We examine the time-frequency lead–lag relationships and the degree of integration between the US financial stress index and global commodity prices (i.e., oil, gold, silver, and cocoa) with data covering over 47 decades (January 1975 to December 2021). For this purpose, we resort to the bi- and multiple wavelet econometric approaches. Findings from the bivariate wavelet analysis evidence the significant influence of the US financial stress in driving the price-generating process in commodities markets. Our findings support the hedging abilities of commodities across the time-frequency space. Findings from the multiple correlations explicate that the interrelation between the commodities and financial stress is attributable to their interdependence in the long term during financial market meltdowns. The dynamic and nonhomogeneous lead/lag relations underscored by our findings highlight the importance of cross-commodity investments. As such, by acknowledging the response of different commodities to financial stress, asset allocation should factor in commodities that offer opposing responses to a financial stress to hedge downside risks associated with portfolios. Our findings are of interest to regulators, risk managers, investors, and commodities producers. |
| format | Article |
| id | doaj-art-7197b399324149fbb10e00bfa7b43e59 |
| institution | DOAJ |
| issn | 2332-2039 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Economics & Finance |
| spelling | doaj-art-7197b399324149fbb10e00bfa7b43e592025-08-20T03:12:40ZengTaylor & Francis GroupCogent Economics & Finance2332-20392022-12-0110110.1080/23322039.2022.2114161Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approachesMohammed Armah0Godfred Amewu1Ahmed Bossman2School of Business, Ghana Institute of Management and Public Administration (GIMPA), Accra, GhanaDepartment of Finance, School of Business, University of Ghana, Legon, GhanaDepartment of Finance, School of Business, University of Cape Coast, Cape Coast, GhanaWe examine the time-frequency lead–lag relationships and the degree of integration between the US financial stress index and global commodity prices (i.e., oil, gold, silver, and cocoa) with data covering over 47 decades (January 1975 to December 2021). For this purpose, we resort to the bi- and multiple wavelet econometric approaches. Findings from the bivariate wavelet analysis evidence the significant influence of the US financial stress in driving the price-generating process in commodities markets. Our findings support the hedging abilities of commodities across the time-frequency space. Findings from the multiple correlations explicate that the interrelation between the commodities and financial stress is attributable to their interdependence in the long term during financial market meltdowns. The dynamic and nonhomogeneous lead/lag relations underscored by our findings highlight the importance of cross-commodity investments. As such, by acknowledging the response of different commodities to financial stress, asset allocation should factor in commodities that offer opposing responses to a financial stress to hedge downside risks associated with portfolios. Our findings are of interest to regulators, risk managers, investors, and commodities producers.https://www.tandfonline.com/doi/10.1080/23322039.2022.2114161financial stressglobal commodities pricescommodity financialisationbivariate waveletwavelet multiple correlationsinterdependence |
| spellingShingle | Mohammed Armah Godfred Amewu Ahmed Bossman Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches Cogent Economics & Finance financial stress global commodities prices commodity financialisation bivariate wavelet wavelet multiple correlations interdependence |
| title | Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches |
| title_full | Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches |
| title_fullStr | Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches |
| title_full_unstemmed | Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches |
| title_short | Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches |
| title_sort | time frequency analysis of financial stress and global commodities prices insights from wavelet based approaches |
| topic | financial stress global commodities prices commodity financialisation bivariate wavelet wavelet multiple correlations interdependence |
| url | https://www.tandfonline.com/doi/10.1080/23322039.2022.2114161 |
| work_keys_str_mv | AT mohammedarmah timefrequencyanalysisoffinancialstressandglobalcommoditiespricesinsightsfromwaveletbasedapproaches AT godfredamewu timefrequencyanalysisoffinancialstressandglobalcommoditiespricesinsightsfromwaveletbasedapproaches AT ahmedbossman timefrequencyanalysisoffinancialstressandglobalcommoditiespricesinsightsfromwaveletbasedapproaches |