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On September 29, 2025,
(AEP) traded with a volume of $0.31 billion, ranking 370th in market activity. The stock closed up 0.59%, reflecting strong demand amid sector-wide momentum driven by energy infrastructure upgrades and AI-driven data center expansion. Analysts at Jefferies highlighted a "Golden Age of Utilities," citing surging capital expenditures by tech giants and regulatory tailwinds for regulated utilities. AEP's regulated electric operations in 11 U.S. states position it to benefit from grid modernization and renewable energy integration.Recent sector analysis underscores utilities' defensive appeal as interest rate cuts loom, with AEP's 58.7 billion market cap and 3.87% sector weightage indicating robust institutional support. The company's exposure to transmission projects through Transource Energy, a joint venture with
Transmission Holding, aligns with infrastructure spending trends. Jefferies' report emphasized data center developers' $417 billion 2025 capex plans, directly boosting demand for reliable power infrastructure like AEP's regulated networks.Technical momentum remains intact as AEP outperformed the S&P 500 utilities index, which gained 0.53% on the day. The stock's 19.03% year-to-date return contrasts with broader market volatility, supported by its "Hold" rating from analysts and consistent dividend yields. With summer heat driving electricity consumption and AI infrastructure expansion accelerating, AEP's regulated utility model offers predictable cash flows amid macroeconomic uncertainty.
To run this back-test accurately I need to pin down a few practical details and make sure the scope matches what our back-testing engine can handle. 1. Investment universe • Do you want all U.S. listed common stocks (NYSE + NASDAQ) as the pool from which the daily “top-500-by-volume” list is drawn? • Or do you prefer a different universe (e.g., S&P 500 constituents, Russell 3000, a particular exchange, etc.)? 2. Trade execution convention • Buy at today’s close, sell at tomorrow’s close (1-day holding period), or • Buy at tomorrow’s open, sell at tomorrow’s close? 3. Portfolio construction • Equal-weight each of the 500 stocks for that single day’s holding period? • Any minimum price or liquidity filter you’d like to add (to avoid sub-$1 “penny” stocks, for example)? 4. Practical implementation note Our current back-testing engine handles one price series per run. For cross-sectional strategies (500 tickers a day) I’ll aggregate the daily P&L of the equal-weighted basket into a single portfolio return series before feeding it to the engine. This is standard practice, but let me know if you’d prefer a different approach. Once I have those details I can generate the data-retrieval plan and launch the back-test from 2022-01-03 (first trading day of 2022) through today.

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