What question did this study set out to answer?

The aim is to develop a zero-parameter framework for state estimation using adaptive mechanisms.

April 28, 2026Open Access

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

Key Points

The aim is to develop a zero-parameter framework for state estimation using adaptive mechanisms.
Combines integral mass modeling with sovereign neural memory.
Employs a holographic weighting mechanism for state estimation.
Evaluated empirically on Nasdaq-100 (QQQ) under out-of-sample conditions.
Demonstrated stable drawdown control in volatile market conditions.

Abstract

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.

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

Key Points

Abstract

Cite This Study