Application of Wavelet Coherence and Connectedness Approaches to Unearth Nickel Price Dynamics

Understanding the nature of connections and causal relationships between economic variables is crucial, especially in industries with significant uncertainties, such as the mineral industry. More accurately capturing causal relationships provides greater insight into engineering and economic phenomena. This paper aims to demonstrate the causal relationships of some phenomena in mineral economies through novel approaches. The proposed approach has a twofold focus: (1) wavelet analysis, a robust and adaptable technique for investigating the time–frequency domain, and (2) the connectedness method, which detects interconnected relationships between variables. Wavelet analysis is presented by the wavelet coherence methodology, which is used to determine the degree of dynamic correlation or causal links between two time series across different time scales. In other words, it unlocks the interactions of the variables across low, medium, and high time scales. Furthermore, the research expands the connectedness method to consider the interconnections between elements in a system, recognizing that modifications in one aspect could have a cascading effect on the entire system rather than individual components. Case studies are conducted on a dataset that includes nickel prices and various financial variables such as Shanghai indices, the ratios of currencies, and the 6-month bonds of the USA and Canada. The analysis using both methods identifies nickel as a key shock sender, particularly influencing the Shanghai indices, Canadian bonds, and the Canadian dollar and United States dollar exchange rate. In some cases, the results of the two methods presented conflicting outcomes. These findings highlight nickel’s significant but varying impact on global financial markets, emphasizing the need for multiple methods to capture its complex nature. The results show wavelet coherence detects associations and causal links in short-, medium-, and long-term cases. The connectedness approach demonstrates how chosen variables are interconnected within the chosen sample by detecting the shock transmission between variables. The variables are transmitting or receiving the shocks, and the transmitters influence variables. The findings suggest that the wavelet coherence and connectedness approach can be valuable tools for decision-making and risk management in the mineral industry.