A2006
Title: Identifying structural types in techno-capital complex systems
Authors: Tsung-Han Ke - National Chi Nan University (Taiwan) [presenting]
Hung-Chun Huang - National Chi Nan University (Taiwan)
Hsin-Yu Shih - National Chi Nan University (Taiwan)
Yun-Xun Hsu - Tunghai university (Taiwan)
Abstract: A Lyapunov-based decomposition framework is developed for analyzing nonlinear dependence structures in techno-capital complex systems. Semiconductor patent activity (TT) and the NASDAQ Composite (NAQ) are transformed into Lyapunov dynamic series to measure evolutionary instability and structural variation under nonlinear conditions. The framework decomposes system dynamics into kinetic energy and potential energy components to distinguish short-term fluctuations from long-run structural accumulation. Three resonance structures are identified from the decomposition: kinetic-to-kinetic resonance reflects synchronized dynamics, kinetic-to-potential resonance captures adaptive feedback, and potential-to-potential resonance represents long-run structural coupling and self-organization. Empirical evidence reveals weak short-term kinetic synchronization but significant long-term potential resonance between TT and NAQ. The results further reveal a shared evolutionary trajectory in which semiconductor innovation dynamics lead financial market adjustment over time. These findings suggest that techno-capital systems evolve primarily through institutional co-evolution and potential-based self-organization rather than short-term market synchronization. The framework provides a statistical approach for identifying self-organizing structures and nonlinear dependence patterns in complex adaptive systems.
