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arXiv · 2511.17646

Bayesian probabilistic exploration of Bitcoin informational quanta and interactions under the GITT-VT paradigm

Quan-Hoang Vuong·Viet-Phuong La·Minh-Hoang Nguyen
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Abstract

This study explores Bitcoin's value formation through the Granular Interaction Thinking Theory-Value Theory (GITT-VT). Rather than stemming from material utility or cash flows, Bitcoin's value arises from informational attributes and interactions of multiple factors, including cryptographic order, decentralization-enabled autonomy, trust embedded in the consensus mechanism, and socio-narrative coherence that reduce entropy within decentralized value-exchange processes. To empirically assess this perspective, a Bayesian linear model was estimated using daily data from 2022 to 2025, operationalizing four informational value dimensions: Store-of-Value (SOV), Autonomy (AUT), Social-Signal Value (SSV), and Hedonic-Sentiment Value (HSV). Results indicate that only SSV exerts a highly credible positive effect on next-day returns, highlighting the dominant role of high-entropy social information in short-term pricing dynamics. In contrast, SOV and AUT show moderately reliable positive associations, reflecting their roles as low-entropy structural anchors of long-term value. HSV displays no credible predictive effect. The study advances interdisciplinary value theory and demonstrates Bitcoin as a dual-layer entropy-regulating socio-technological ecosystem. The findings offer implications for digital asset valuation, investment education, and future research on entropy dynamics across non-cash-flow digital assets.

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Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen. 2025-11-20. Bayesian probabilistic exploration of Bitcoin informational quanta and interactions under the GITT-VT paradigm. https://arxiv.org/abs/2511.17646

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