Cryptocurrencies in the Balance Sheet: Insights from (Micro)Strategy – Bitcoin Interactions

ArXiv ID: 2505.14655 “View on arXiv”

Authors: Sabrina Aufiero, Antonio Briola, Tesfaye Salarin, Fabio Caccioli, Silvia Bartolucci, Tomaso Aste

Abstract

This paper investigates the evolving link between cryptocurrency and equity markets in the context of the recent wave of corporate Bitcoin (BTC) treasury strategies. We assemble a dataset of 39 publicly listed firms holding BTC, from their first acquisition through April 2025. Using daily logarithmic returns, we first document significant positive co-movements via Pearson correlations and single factor model regressions, discovering an average BTC beta of 0.62, and isolating 12 companies, including Strategy (formerly MicroStrategy, MSTR), exhibiting a beta exceeding 1. We then classify firms into three groups reflecting their exposure to BTC, liquidity, and return co-movements. We use transfer entropy (TE) to capture the direction of information flow over time. Transfer entropy analysis consistently identifies BTC as the dominant information driver, with brief, announcement-driven feedback from stocks to BTC during major financial events. Our results highlight the critical need for dynamic hedging ratios that adapt to shifting information flows. These findings provide important insights for investors and managers regarding risk management and portfolio diversification in a period of growing integration of digital assets into corporate treasuries.

Keywords: corporate Bitcoin treasury, co-movements, beta, transfer entropy, information flow, Cryptocurrency

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders
• Why: The paper employs standard econometric techniques (Pearson correlation, single-factor regression, and transfer entropy) with moderate mathematical complexity, while demonstrating strong empirical rigor through the compilation of a proprietary dataset of 39 firms, comprehensive time-series analysis, and clear identification of actionable insights for risk management.

  flowchart TD
    A["Research Goal<br>Cryptocurrency & Equity Market Link"] --> B["Data Collection<br>39 Public Firms, Daily Log Returns, April 2025"]
    B --> C["Co-movement Analysis<br>Pearson Correlation & Beta Regressions"]
    C --> D["Classification<br>Firms Grouped by BTC Exposure, Liquidity & Co-movements"]
    D --> E["Directional Analysis<br>Transfer Entropy Calculation"]
    E --> F["Key Findings<br>BTC as Dominant Driver, Dynamic Hedging Needed"]