Abstract : The Fear of Missing Out (FOMO) in financial markets refers to the tendency of investors to engage in rapid, sentiment-driven decisions under conditions of perceived scarcity or urgency. Within the context of Society 5.0, characterized by the integration of cyber-physical systems, human-centric innovation, and interconnected socio-financial ecosystems, these behaviors are amplified by advancing technological, cultural, and psychological dynamics. This study introduces the FOMO Index Conceptual Framework (FICF), which integrates sentiment analysis, digital behavioral tracking, psychometric profiling, cultural adaptability metrics, pragmatic VUCA (volatility, uncertainty, complexity, and ambiguity) risk assessments, and ethical governance considerations. The framework is implemented alongside the FOMO Index Lifecycle Management and Evolving Categorization (FI-LMEC) model, enabling continuous recalibration in response to macroeconomic, geopolitical, and technological transformations. A case study on Artificial Intelligence (AI) based investment illustrates the FICF's capacity to associate elevated sentiment signals with accelerated trading activity while identifying structural factors that stabilize volatility. The FOMO index provides an adaptive and scalable instrument for predictive analytics, investment portfolio optimization, and systemic risk mitigation.

Keyword : AI-Based Investment, Behavioral Finance, FOMO Index, Sentiment Analytics, VUCA Risk Assessment