Analysis of factors influencing metal markets across multiple scales – A smooth transition regression approach

Despite the significant influence of global factors on metal markets, this area remains underexplored, particularly regarding the distinction between short-term and long-term effects. This study examines the multiscale risk spillover effect from factors such as interest rates, energy markets, and developed and emerging stock markets. Additionally, it analyzes the risk transmission between precious and industrial metals. In this process, the study constructs systemic risk time-series for all markets using the Mahalanobis Distance methodology. By transforming raw data into wavelet D6 signals, long-term time-series are generated. Both raw and wavelet-based data are then integrated into a smooth transition regression model to assess nonlinear spillover effects over different time horizons. The findings reveal that precious metal markets are exposed to risk spillovers from industrial metals, energy markets, and stock markets, but only in the low-volatility regime and over the short term. In contrast, industrial metals experience spillover effects across both low- and high-volatility regimes within the short-term horizon. The most pronounced spillover effects originate from BRICS stock markets to industrial metal markets during periods of low volatility. In the long term, the results indicate that risk spillovers from industrial to precious metals become more prominent, suggesting that both markets are heavily influenced by broader economic cycles. The paper provides a wide range of results, which can be valuable for investors, portfolio managers, and policymakers.