Cross-Asset Shock Diffusion: A Reproducible Test of Residual Underreaction, Shock Coherence, and Trading Economics

Abstract

This paper examines whether differences in the speed with which traded assets respond to a common market shock can predict subsequent relative returns. The framework combines a lagged rolling factor model with Absorption Gap (AG), which measures an asset’s response error, and Shock Coherence (SC), which characterizes the contemporaneous market state. The public specification is evaluated using executable next-open timing, explicit transaction costs, dependence-aware inference, randomized-signal benchmarks, chronological diagnostics, and machine-learning extensions. The study uses 24 ETFs from 4 January 2010 through 28 August 2026, with eight factor proxies excluded from the 16-asset traded cross-section. The corrected public baseline produces a combined Rank IC of -0.00592, an approximately flat zero-cost gross result, and materially negative performance after transaction costs. A within-date randomized-signal benchmark yields an empirical two-sided p-value of 0.299, while standalone Absorption Gap, coherence-conditioned tests, chronological subsamples, and machine-learning models provide no robust evidence of economically viable public alpha. The contribution is therefore methodological as much as empirical: the paper connects an economic hypothesis about heterogeneous information absorption to an executable trading test, documents why the disclosed implementation fails, separates diagnostic and exploratory analysis from confirmatory evidence, and establishes a reproducible public baseline while keeping the proprietary alpha layer outside the evidence package.