Market uncertainty and information content in complex seasonality of prices

In the context of heightened economic and financial market uncertainty, identifying and measuring uncertainty have become an important research question. This study offers a novel approach to uncover uncertainty and its sources by leveraging the complex seasonality inherent in futures prices. Our findings indicate that the temporal hierarchical forecasting method is not universally effective across 35 different commodity futures. However, further analysis reveals that this method outperforms single time series forecasting models when its manually set seasonal components align with those identified through singular spectrum analysis (SSA). The study demonstrates the efficacy of SSA in revealing complex seasonality patterns in various futures prices. Additionally, our event analysis results indicate that shifts in the seasonality patterns of commodity futures prices provide a new perspective for understanding uncertainty and exploring its origins. This research contributes to the literature by extending market uncertainty measures through the linkage with complex seasonality analysis, and offering valuable insights for risk management.