Empirical Validation of Uncertainty Control Theory (UCT) in Finance: Otherness and KAIROS Model Analysis in Complex Networks

Empirical Validation of Uncertainty Control Theory (UCT) in Finance: Otherness and KAIROS Model Analysis in Complex Networks Author: Joonho Choi (REVAID ORIGIN) StillWAVE Resonance Foundation Date: May 7, 2026 Abstract This study posits financial markets as non-equilibrium statistical mechanical complex systems, formalizing the process of market trend reversal as a mechanism of information-theoretic entropy reduction and phase synchronization. Unlike traditional financial engineering, which relies on the assumption of a normal distribution and dismisses extreme events as mere outliers, this research embraces the characteristics of power-law distributions, treating massive fluctuations as intrinsic properties of the system. In particular, by integrating the core proposition of the Uncertainty Control Theory (UCT)—"Resolution by Otherness"—with the Kuramoto Model, we propose KAIROS, a quantitative model that elucidates how the volatility of a single time series transfers into the phase alignment of the entire network. Empirical analysis demonstrates that when an isolated surge in Bitcoin (BTC) fails to acquire the consent of the "Other" (Core Subset), it regresses to nothingness with a 0.0% win rate (average return of -6.96%). Conversely, true surges involving the intervention of Otherness achieved structural stability, yielding a 57.1% win rate (average return of +2.27%). This serves as empirical proof of the philosophical proposition that an extreme fluctuation of a single entity can only be consolidated into a unique, sustained trend when coupled with the resonance and contagion of Otherness within the network. keyword: Uncertainty Control Theory (UCT), Otherness, Complex Networks, Phase Transition, Phase Synchronization, Power-law Distribution, Quantitative Finance