Microsoft (MSFT) Plummets 2.19% on $12.42 Billion Volume Ranking Sixth in Dollar Turnover

On October 10, 2025, Microsoft (MSFT) closed down 2.19% with a trading volume of $12.42 billion, ranking sixth in total dollar turnover among U.S. equities. The decline followed mixed signals from regulatory and operational developments, though specific catalysts remained unclear as broader market sentiment remained neutral.

Recent filings indicated ongoing antitrust litigation pressures, with U.S. regulators intensifying scrutiny over cloud infrastructure dominance. While no immediate rulings were announced, legal uncertainties have historically pressured large-cap tech stocks. Operational updates highlighted delayed AI integration timelines, though these were not explicitly tied to earnings guidance revisions.

Analysts noted the stock’s sensitivity to sector rotation patterns, with institutional outflows observed in high-beta tech positions. Market structure data showed reduced short-term volatility ahead of quarterly earnings, suggesting tempered investor expectations for near-term margin expansion. No material product launches or partnership announcements were disclosed in the period.

I understand the idea: each trading day you’d like to form a portfolio containing the 500 stocks with the highest dollar turnover (price × volume), hold that basket for one day, then repeat the process from the start of 2022 to today. At the moment our available back-testing engines work on a single security (or on single-security event dates). To run a cross-sectional, daily-rebalanced portfolio of 500 names we would need a pre-built data file that lists, for every trading day in the sample period, the tickers that ranked in the top-500 by volume. Without that daily list the engine cannot generate the required buy/close signals. Could you let me know one of the following? 1. Do you already have (or can you supply) a CSV / JSON file that contains, for each date, the 500 tickers to hold? 2. If you don’t have the file, would you like me to show you how to build it outside the chat (e.g., with a Python script), or would you prefer an approximate proxy (for example, testing an ETF that is designed to track the most-traded names)? Once I have clarity on the source of those daily top-500 lists, I can proceed with the back-test and present the results.