RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting

The Regime-Aware Variable-context Expert Network (RAVEN) has been introduced as a Mixture-of-Experts framework specifically designed for financial time series forecasting. RAVEN adapts its temporal context dynamically rather than relying on a fixed look-back window, utilizing a Cumulative Importance Thresholding mechanism to create nested context windows and incorporating a Global Compressed Representation for enhanced temporal coherence. Experimental results indicate that RAVEN outperforms state-of-the-art models, achieving significant improvements in Pearson correlation and mean squared error across multiple financial datasets, which is crucial for practitioners dealing with non-stationary financial data.