Time-frequency analysis of financial stress and global commodities prices: Insights from wavelet-based approaches - Mohammed Armah; Godfred Amewu; Ahmed Bossman (Cogent Economics & Finance, 2022)
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.
Keywords: C58; E44; F15; G01; G11; Q02; 330; financial stress; global commodities prices; commodity financialisation; bivariate wavelet; wavelet multiple correlations; interdependence