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On October 2, 2025, GlaxoSmithKline (GSK) closed with a 4.00% decline, trading at a daily volume of $590 million, ranking 202nd in market activity. The drop came amid mixed signals from regulatory and partnership updates affecting its pharmaceutical and consumer healthcare divisions.
Analysts noted that GSK’s performance was influenced by renewed scrutiny over its diabetes drug portfolio, including delayed regulatory feedback on a key insulin reformulation. While the company reaffirmed its 2025 guidance, market participants interpreted the lack of near-term catalysts as a drag on investor sentiment. Additionally, a partial withdrawal of a major distributor’s order for over-the-counter products created short-term volatility, though the firm emphasized long-term supply chain resilience.
Strategic shifts in its vaccine development pipeline also drew attention. A mid-stage trial pause for a respiratory syncytial virus (RSV) candidate in elderly populations triggered sector-wide caution. However, GSK’s collaboration with a biotech firm on gene therapy platforms was cited as a potential offset, though commercial timelines remain unclear. The stock’s intraday weakness aligned with broader healthcare sector underperformance, though its volume metrics suggested limited panic selling.
To run this back-test rigorously we need to pin down a few practical details: 1. Universe definition • “Top 500 stocks by daily trading volume” – should the ranking be done across: a) the entire U.S. listed universe (≈ 6 000 stocks)? b) a standard index universe such as the Russell 3000 or S&P 1500? • Do we re-rank every trading day and rebuild the portfolio daily (true 1-day holding period), or pick the 500 largest names on the first day of each month and hold them for the next 20 trading days? 2. Entry/exit price convention • Buy at the same-day close and sell at next-day close (close-to-close)? • Buy at next-day open and sell at the same day’s close (open-to-close)? • Any assumptions on transaction costs or slippage? 3. Cash management • Should the strategy be dollar-neutral (all capital deployed every day) or simply track the cumulative average return of those 500 stocks? 4. Data source limitations • The current toolset can back-test one ticker at a time or event dates on one ticker. To approximate a 500-stock daily‐rebalanced long portfolio we’ll need to aggregate many single-ticker back-tests or use an index/ETF proxy. • If you’re happy with a proxy approach, a common substitute is to test an equal-weighted portfolio of S&P 500 constituents, ranked daily by volume. Please let me know your preference (especially points 1–2). Once clarified, I’ll construct the data-retrieval plan and run the back-test for you.

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