Bayesian Signals and Bitcoin’s Informational Value

Summary

The study frames Bitcoin’s value as arising from informational features and their interactions, including decentralization, consensus trust, cryptographic ordering, and social narratives. It represents these dimensions with four measures: store-of-value, autonomy, social-signal value, and hedonic sentiment, then uses a Bayesian linear model to examine their relationship with next-day returns using daily data from 2022 to 2025.

The reported results distinguish short-term predictive association from structural interpretations: social-signal value has a highly credible positive effect on next-day returns, while store-of-value and autonomy have moderately reliable positive associations. Hedonic sentiment shows no credible predictive effect. These findings are specific to the proposed measures, model, period, and return horizon; the summary provides no details about out-of-sample validation or whether the associations support a profitable trading strategy. The broader entropy-based account is an interpretive framework rather than evidence that Bitcoin’s value is fully explained by these dimensions.

Key ideas

• The paper models Bitcoin value through store-of-value, autonomy, social-signal, and hedonic-sentiment dimensions.
• A Bayesian linear model relates those dimensions to next-day Bitcoin returns.
• Social-signal value has the strongest reported positive predictive association.
• Store-of-value and autonomy show moderately reliable positive associations, while hedonic sentiment does not show a credible predictive effect.
• The reported relationships do not by themselves establish out-of-sample trading profitability.

Tags

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


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









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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.