Dell's 1.36% Rally Defies 39.39% Volume Drop as Stock Slides to 174th in Market's Trading Activity

On September 18, 2025, , . , indicating subdued short-term liquidity demand.

Recent strategic updates highlighted Dell’s focus on enterprise AI infrastructure and hybrid cloud solutions, with management emphasizing long-term capital efficiency. , signaling confidence in balance sheet strength amid macroeconomic uncertainty. Analysts noted that the buyback, , could underpin investor sentiment despite near-term sector volatility.

Operational metrics showed improved gross margins for the fiscal quarter, driven by supply chain optimization and higher-margin service contracts. However, . .

To run this back-test rigorously I need to pin down a few practical details and be sure the data universe we’ll pull from matches your intent. Could you please confirm the following? 1. Universe • Do you want to scan every common stock listed in the U.S. (NYSE + NASDAQ + AMEX), or just a subset such as the S&P 500 constituents? • Are ADRs, ETFs and preferred shares excluded? 2. Re-balancing & execution model • The usual implementation is: at today’s close we rank all stocks by today’s dollar volume and buy the top 500 names equally; we close (sell) all of them at tomorrow’s close. – Is that the trade schedule you have in mind? • Slippage/transaction costs: should we ignore them, use a flat bps estimate, or another convention? 3. Pricing data • Entry/exit price: “close-to-close” (today’s close to tomorrow’s close) is typical. Is that acceptable? 4. Feasibility note Daily “top-500-by-volume” requires pulling volume and price for thousands of tickers each day. Our current tool set can do this, but the run-time is long and storage heavy. – If you would accept a simpler proxy (e.g., always holding the current S&P 500 constituents, or working with the top-500 names ranked by *average* volume in 2021-2022 rather than re-ranking every day), the back-test can be completed much faster. Let me know your preferences (especially on points 1 and 4). Once I have that, I can generate the data-retrieval plan and run the back-test.