The Maat Cycle: A Symmetric Framework for Detecting Recovery From Financial Stress

This paper presents SEWS-R (Spectral Recovery Detection), the symmetric completion of the SEWS framework, and introduces the Maat Cycle: a four-phase model of complete system stress and recovery (STABLE → DRIFT → BROKEN → RETURN). Using 80 quarters of U.S. banking sector data (2005–2024), SEWS-R successfully detected the early onset of recovery from the Global Financial Crisis (approx. 12 quarters before conventional confirmation) and the COVID-19 shock (approx. 4 quarters early). The framework is built on the Stability-Balance Theorem (DOI: 10.5281/zenodo.19539578) and extends the SEWS Bank preprint (DOI: 10.5281/zenodo.19544383).