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

Author

Listed:
  • Quan-Hoang Vuong
  • Viet-Phuong La
  • Minh-Hoang Nguyen

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.

Suggested Citation

  • Quan-Hoang Vuong & Viet-Phuong La & Minh-Hoang Nguyen, 2025. "Bayesian probabilistic exploration of Bitcoin informational quanta and interactions under the GITT-VT paradigm," Papers 2511.17646, arXiv.org.
    • Handle: RePEc:arx:papers:2511.17646
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    References listed on IDEAS

    as
    1. Manisha Yadav, 2024. "Behavioral biases of cryptocurrency investors: a prospect theory model to explain cryptocurrency returns," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 16(4), pages 643-667, January.
    2. repec:osf:osfxxx:qgpvn_v1 is not listed on IDEAS
    3. Vuong, Quan-Hoang & Nguyen, Minh-Hoang & La, Viet-Phuong, 2022. "The mindsponge and BMF analytics for innovative thinking in social sciences and humanities," OSF Preprints qgpvn, Center for Open Science.
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