General Dynamics Rises 0.09% on $320M Volume, Clings to 369th Spot in Daily Trading Activity

On October 2, 2025, General Dynamics (GD) closed with a 0.09% increase, trading on a volume of $0.32 billion, ranking 369th in market activity for the day. The stock’s performance aligned with broader market trends, though its volume suggested moderate investor engagement relative to peers. Analysts noted that the company’s recent operational updates and defense sector positioning remained central to its valuation framework.

Recent developments highlighted General Dynamics’ strategic focus on defense modernization contracts, which have historically supported its revenue stability. While no immediate earnings or dividend announcements were reported, the company’s participation in key government tenders and R&D milestones were cited as long-term tailwinds. Market participants observed that the stock’s muted volatility reflected cautious positioning ahead of upcoming fiscal Q3 reporting dates.

I understand the strategy conceptually—each day you want to: 1. Rank all stocks by the day’s trading volume. 2. Buy the top-500 names at that day’s close (or next day’s open). 3. Exit all those positions one trading day later. 4. Repeat the process from 1 Jan 2022 to the present and track the aggregate return. Unfortunately, the back-testing tools integrated into this chat currently evaluate one ticker at a time. They’re not designed to run a cross-sectional, daily-rebalanced portfolio of hundreds of tickers in a single pass. To move forward we have two main options: A. Approximation • Use a proxy (for example, a broad-market ETF or an index of highly liquid stocks) to demonstrate the mechanics. • This would illustrate the workflow but would not fully capture the top-500-by-volume logic. B. Full custom back-test (external) • We export the raw daily volume and price data for the full universe, then code the ranking, portfolio construction, and performance calculation outside of this chat interface (e.g., in Python). • After generating the daily P&L series, we can re-import it and use the strategy evaluation module to compute the final statistics and visualization. Which approach would you prefer? If you’d like to proceed with the full custom back-test, please let me know the market/universe (e.g., U.S. equities only), and I can outline the exact data pulls you would need to run the calculation on your side.