EMFactorTiming/docs/METHODOLOGY.md

Methodology & Benchmark Discipline

1. The Multi-Country Benchmark Problem: In a multi-country factor panel (153 JKP factors across 22 emerging and 23 developed markets), each country-factor mean is estimated from a noisy history. Testing a learned model against each series own expanding mean (hist_mean) conflates genuine time-series predictability with cross-sectional pooling of unconditional means (size = 87.5% under a no-predictability null).
2. Shrinkage-Mean Benchmark (shrink_mean): Shrinking each series expanding mean toward the regional mean of the same factor restores nominal 5.0% size while retaining 92.5%-100% power.
3. Deviation Forecasting & Turnover-Penalized Portfolios: All learned models (ols, enet, gbrt, nn) forecast deviations from shrink_mean across three scopes (own, dm_only, pooled) and are evaluated via out-of-sample $R^2_{\text{OS}}$, Clark-West $t$-statistics, and timing portfolios net of 20 bp per unit of turnover.