Meta's $26B AI-Driven Data Center Financing Pushes Stock to 10th in Trading Volume

On September 5, 2025, , ranking 10th in market activity. , structured to keep debt off its balance sheet while advancing AI infrastructure ambitions. , .

Central to the deal is Meta’s residual value guarantee, a novel mechanism offering investors protection against potential asset devaluation. , . This clause, unprecedented in large-scale data center financings, addresses risks tied to rapid technological obsolescence in AI infrastructure. The arrangement, led by . and , highlights Meta’s strategic approach to securing capital-intensive projects while maintaining financial flexibility.

Industry experts note the deal could set a precedent for future tech infrastructure financing. The Hyperion project is part of a broader trend, . , . The structure’s complexity and investor safeguards underscore the sector’s evolving risk profile amid heightened demand for specialized infrastructure.

To run this back-test robustly I need to pin down a few implementation details: 1. Universe • Which market should we rank for “top-500 stocks by trading volume” – e.g. all U.S. listed equities (NYSE + NASDAQ), only S&P 500 constituents, or another universe? 2. Execution price assumptions • Do we (a) rank on today’s volume at the close, buy at that same close, then exit at tomorrow’s close (1-day holding period), or (b) rank on yesterday’s volume, buy at today’s open, and exit at today’s close? 3. Transaction frictions • Should we apply any explicit trading cost/slippage, or assume frictionless execution? 4. Benchmark / performance metrics • Is simple cumulative return sufficient, or would you like additional metrics (e.g., annualized return, volatility, Sharpe, max drawdown)? Once these points are confirmed I can build the data-retrieval plan and run the back-test.