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On October 10, 2025,
(GD) closed at a 2.87% decline, with a trading volume of $0.31 billion, ranking 416th in market liquidity for the day. The stock's performance followed mixed signals from macroeconomic updates and sector-specific developments.Analysts noted subdued investor sentiment in the defense sector amid delayed congressional budget approvals, which raised uncertainty over future defense spending allocations. While no company-specific earnings or strategic announcements were reported, broader market rotations toward low-volatility assets pressured GD's short-term positioning.
Technical indicators showed increased short-term volatility, with the stock testing key support levels near its 50-day moving average. Institutional trading activity remained muted, as reflected in the relatively low volume rank despite the sharp price drop. Market participants are now monitoring upcoming fiscal policy statements for clarity on capital expenditure timelines.
To build and back-test this “top-500-by-volume” strategy accurately we first need to pin down several practical details: 1. Market universe • Which exchange(s) should we scan each day—U.S. listed stocks (NYSE + NASDAQ), only the S&P 500 constituents, or another universe? 2. Weighting & sizing • Do we allocate equal dollar weight to every selected stock, or some other weighting rule? • Should we assume unlimited liquidity (no slippage) or impose basic trading-cost assumptions? 3. Trade-price convention • Do we “rank on day t’s close, buy at day t’s close, then sell at day t+1’s close” (close-to-close)? • Or rank on day t’s volume, “buy at next day’s open, sell at next day’s close” (open-to-close)? • Please confirm the convention you want. 4. Back-test engine availability My current one-ticker back-test engine is not geared for a 500-ticker daily-rotating basket. • If you are comfortable with an approximated proxy (e.g., trading an ETF that best represents the high-liquidity segment), I can proceed immediately. • Otherwise, we will need to run a custom multi-asset simulation outside the built-in tool-set. Let me know your preferences on the four points above, and I’ll map out the most efficient path (or workaround) to deliver the performance results you need.

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