ABSTRACT This article proposed a novel hybrid framework, the WTC‐DCA‐Informer, for forecasting volatility in the Australian stock market. The findings indicated that (1) through a comprehensive comparison with various machine learning and deep learning models, the proposed WTC‐DCA‐Informer framework significantly outperformed traditional methods in terms of predictive performance. (2) Across different training set proportions, the WTC‐DCA‐Informer model demonstrated exceptional forecasting capabilities, achieving …