The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting
The episode discusses 'The Label Horizon Paradox,' a paper revealing that forcing training labels to match final prediction targets is insufficient in financial forecasting. Researchers found that noise accumulates rapidly, necessitating a shift from static learning cycles. The conclusion is that dynamic, adaptive methods are required to find the optimal signal based on time-dependent information utility.