Temporal Structural Forecasting: A Comprehensive Empirical Refutation of Weak-Form Market Efficiency

This registered report presents the most comprehensive empirical challenge to weak-form market efficiency ever assembled. We introduce Temporal Structural Forecasting (TSF), a methodology that identifies exploitable patterns in historical price data through multi-cycle seasonal decomposition. The study tests 44 preregistered hypotheses across four papers using 346 S&P 500 stocks spanning 11 GICS sectors over 20 years (2006–2025). We establish four independent refutation paths: (1) predictable structure exists in price data, (2) entry timing is exploitable after transaction costs, (3) exit timing is independently exploitable regardless of entry methodology, and (4) temporal structure improves factor portfolio returns. Preliminary results from a 30-stock pilot study (2015–2024) confirm all four refutation paths with 27/44 hypotheses (61%) supported. Most notably, applying TSF exit signals to benchmark strategies improved excess returns in 72.7% of cases (p = 1.19 × 10⁻⁵), demonstrating that exit timing constitutes an independent market inefficiency—a finding that uses zero TSF entry signals. The methodology, hypotheses, and analysis plan are locked via Zenodo deposit prior to primary data analysis on the 346-stock universe.