DPAL: A Test-Time Adaptation Loss for Financial Time Series Forecasting
DPAL introduces a new loss function for financial time series forecasting called Direction- and Price-Aware Adaptation Loss. It combines standard prediction errors with terms that penalize incorrect return directions and calibrate reconstructed price trajectories. Experiments show DPAL significantly improves test-time adaptation performance across various models and datasets by better capturing directional and price dynamics.