Quantum Portfolio Management (QPM): Projected Dynamical Systems for Executable Decision Flows Under Constraints

Quantum Portfolio Management (QPM) is investigated in this work through a deliberately reduced and falsifiable architecture for constrained decision systems. The framework separates desired forcing, executable motion, and constraint interaction using projected decision dynamics, and introduces structural diagnostics including Coherence Debt, Constraint Pressure, and model-based Margin. The reduced architecture is evaluated through a frozen historical replay with causal estimators, explicit benchmarks, pre-specified null hypotheses, and no TEST-period retuning. The results do not support QPM as a distinct execution mechanism or as a financially superior optimizer in the tested setting. Coherence Debt is shown to be redundant with simple movement magnitude, while Constraint Pressure remains untestable under the realized constraint geometry. Model-based Margin, however, retains incremental explanatory information relative to the tested retrospective Debt-slope rival, although its weekly directional interpretation does not survive. The resulting evidence supports a narrower interpretation of QPM as an auditable diagnostic architecture for constrained decision systems and establishes R1 as the first explicit operational falsification stage of the QPM research program.