A Unified Framework for Zero-Parameter Signal Processing and Sovereign Memory-Augmented State Estimation in High-Volatility Markets

This paper presents a zero-parameter adaptive framework combining integral mass modeling with sovereign neural memory. The system incorporates a holographic weighting mechanism where next-step state estimation is derived from aggregated derivatives across context windows. This enables adaptive, self-healing behavior without reliance on fixed parameters. Empirical evaluation on Nasdaq-100 (QQQ) demonstrates stable drawdown control under out-of-sample conditions.