Abstract

Commodities have become a new tool for global diversification among stocks, currencies, and other assets. Their dynamics and statistical characteristics have become crucial to financial research. Furthermore, in the connected world of today, the importance of uncertainties is greater than ever. This article examines the comovements between energy commodities and the influence of uncertainty measures through the bi, partial and multiple wavelet techniques. We show the significance of uncertainties by highlighting their influence on financial decisions. To measure uncertainty, we use GEPU, OVX, and VIX. By using the wavelet approaches, we examine how energy commodities interact in both the time and frequency domains, which helps us better comprehend interdependencies. The results show that most energy commodities display high comovements in the short-, and long-terms, except with natural gas. According to the partial wavelet, OVX has the most significant impact on the connectedness amongst energy commodities. For the wavelet multiple cross-correlations, Petroleum maximises the multiple cross-correlations at most scales (short, medium and long terms) followed by Brent crude with a potential to lead or lag. These findings have substantial policy implications for policymakers as well as meaning for investors.

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