Vertiv Shares Climb 3.09% on $920M Volume Slide to 83rd Rank as Execs Flag 25% EBIT Margin Target by 2029

, 2025, , , ranking 83rd in market activity. The company’s CEO and CFO highlighted strategic growth at the Goldman Sachs Communicopia + Technology Conference, . Expansion in liquid cooling capacity and operational improvements in EMEA were underscored as key initiatives to address market challenges and tariffs.

, . , . Share repurchases and M&A remain central to capital deployment, . Tariff impacts are expected to be offset by 2025 through pricing and supply chain strategies.

To construct an accurate back-test for this strategy I need to clarify (and, if necessary, simplify) a few key points: 1. Universe definition • Which market should the 500 stocks come from (e.g., U.S. listed equities only, all developed-market equities, etc.)? • If the universe is “all U.S. stocks,” do you want to screen only primary-listed common shares (to exclude ADRs, ETFs, warrants, etc.)? 2. Rebalancing mechanics • The usual workflow is: at today’s close, rank all stocks by today’s dollar trading volume, buy the top 500 in equal weight, and liquidate them at tomorrow’s close. Is that your intended sequence? • Do you want equal weights, or volume-weighted / market-cap-weighted positions? 3. Practical constraints Our current back-testing engine is designed for single-ticker or event-based studies. Running a daily cross-sectional rebalance across 500 tickers for three years would exceed the engine’s scope. To proceed, we have two options: a) Narrow the test to a representative surrogate (for example, an ETF that tracks high-liquidity U.S. shares, such as RSP or SPY) and analyse one-day holding returns. b) Export daily top-500 membership to a file and run a custom script offline, then re-import the aggregated P&L series for performance evaluation (this requires you to provide the membership file). Please let me know which approach you’d prefer—or if you’d like to adjust the strategy definition in any way—so I can proceed with the appropriate data-retrieval and back-testing steps.