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On September 22, 2025, , , ranking 35th in daily trading activity. The company continues to dominate the expanding weight-loss drug market, driven by blockbuster products like Zepbound and Mounjaro, . . sales during the period, underscoring its strong market penetration.
Eli Lilly’s strategic focus on innovation and manufacturing scalability positions it as a key player in the sector. Its pipeline includes orforglipron, an oral GLP-1 drug, and retatrutide, . These advancements aim to address unmet needs in obesity treatment, particularly with oral formulations and improved tolerability. , ensuring supply stability amid high demand.
Recent regulatory milestones include FDA approval of Kisunla (donanemab) for early-stage Alzheimer’s and updates to its dosing regimen to reduce side effects. While these developments highlight Eli Lilly’s diversification beyond weight loss, its core strength remains in obesity and diabetes treatments. The company’s robust financials, , reinforce its long-term growth potential.
I’d like to make sure I understand your idea – and confirm we can implement it cleanly with the built-in back-test engine. 1. Universe • Do you want the top-500 U.S. listed stocks by dollar trading volume each day (NYSE + NASDAQ), or a different market? 2. Trade timing • “Hold for 1 day” – should we: a) Buy at today’s close, sell at tomorrow’s close; or b) Buy at tomorrow’s open, sell at tomorrow’s close; or c) Another convention? 3. Portfolio treatment • The standard engine here back-tests one ticker at a time. To replicate a daily 500-stock rotation we would need to compute an equal-weight portfolio return series externally and feed that to the engine. That’s doable, but I want to confirm you’re comfortable with that approach (and with the equal-weight assumption). Let me know your preferences on the three points above and I’ll set up the data-retrieval and back-test steps accordingly.

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