Lead Lag

Lead-lag analysis focuses on identifying temporal dependencies between multiple time series, where changes in one series precede changes in another. Current research emphasizes developing sophisticated models, such as transformer-based architectures and factor-augmented tree ensembles, to accurately capture these complex relationships, often incorporating techniques like clustering and network analysis to identify groups of leading and lagging variables. This work has significant implications for forecasting in diverse fields, from finance (predicting market movements) to environmental science (analyzing ecological interactions), by leveraging the predictive power of leading indicators.