How Digital Asset Treasury Companies Can Survive Bear Markets: The Case of the Strategy and Bitcoin

Battle Count: 50

The paper has moderate relevance to quantitative trading. It provides insights into the 94.321% correlation between BTC and MSTR stock, mNAV dynamics, and the structural fragility of DAT stocks in bear markets, which are relevant for crypto-equity pair trading and sector rotation strategies. The no-forced-sale condition and liquidity sleeve concepts inform risk management for portfolios with crypto treasury exposure. However, the paper does not propose specific trading signals, alpha models, or algorithmic execution strategies. Its primary contribution is to corporate finance and treasury management rather than to trading strategy development. The fee revenue model and Lightning Network economics could inform crypto payments infrastructure plays but are tangential to traditional quantitative trading.

The conceptual framework (no-forced-sale inequality, KPI disclosures) is straightforward to understand and implement at a policy level. However, the actual implementation of a BTC-to-sats Lightning payments rail at enterprise scale is highly complex: it requires Lightning Network channel management infrastructure, real-time hedging systems for settlement inventory, KYC/AML compliance, integration with enterprise software (Salesforce, Okta, Zoom), multi-currency off-ramps, and sophisticated risk management for the liquidity sleeve. The paper's framework is implementable as a governance and disclosure policy with moderate complexity, but the full payments rail infrastructure represents significant engineering and operational complexity.

The paper is primarily a conceptual framework and case study. The no-forced-sale inequality is formally stated but not empirically calibrated with specific parameter values. No code, datasets, or simulation scripts are provided. The Lightning Network performance data referenced is from public sources. The framework is generalizable in principle but lacks quantitative backtesting or out-of-sample validation. Reproduction would require access to Strategy's internal financials and Lightning channel data.