The book delves into the interdependence structure and the predictive capacities of commodities on high-pressure currencies including Ghana, Malawi, Gambia, and Madagascar, spanning from January 2015 to December 2023, utilizing the bivariate, partial, and multivariate wavelet algorithms. The research identifies the asymmetric dependence patterns between sampled markets. Notably, GHS and MGA emerge as currencies adversely driven by both exports and imports, with pronounced predictiveness, especially during the global health crisis era. Validation of the partial and multivariate algorithms reveals diminished predictive capacity in the partial and heightened systemic predictiveness in the multivariate. Within the Malawian and Madagascan sub-systems, crude and corn exhibit lagging and leading behaviors, corroborated by the outcomes of the wavelet-based nonparametric causality. The study unveils substantial implications for the central banks and various stakeholders, including individual and corporate importers and exporters. These findings underscore the importance of strategic management to counteract currency fluctuations and bolster investor confidence for economic advancement.