AEP's $250M Volume Ranks 408th as Shares Climb 1.02% Amid Regulatory Scrutiny

, ranking 408th among stocks traded that day. .

Recent developments highlight regulatory and operational factors influencing AEP's performance. Ongoing federal investigations into grid reliability standards have intensified scrutiny on utility infrastructure spending. Analysts note that AEP's capital expenditure plans for transmission upgrades remain a key focus for investors, . .

Market participants are monitoring the impact of regional weather patterns on demand forecasts. , though this has been partially offset by milder conditions in key service territories. , .

To run this back-test robustly I’ll need a bit more detail (and to make sure the set-up matches what our back-testing engine can handle):

1. Universe • Which exchange(s) / listing universe should we sample the "top 500 by dollar volume" from? (e.g., all U.S. listed common stocks, only NYSE + NASDAQ, S&P 500 constituents, etc.) 2. Rebalancing mechanics • Do we re-select the top 500 every trading day and fully rebalance the portfolio (equal-weight) each day? • Are transaction costs or slippage to be considered, or can we ignore them for this test? 3. Cash & leverage • Is the strategy always 100% invested (no cash) or some other rule? 4. Data source consistency • Our current tool set back-tests one ticker or one event set at a time; to replicate a 500-stock cross-section requires a custom data pipeline. – If you’re comfortable with an approximation, we could test an ETF proxy that tracks very liquid names (e.g., SPY) and compare "high-volume days" vs. normal days. – Alternatively, we can focus on a single high-volume stock as an illustrative case. Let me know which way you’d like to proceed (or provide the missing specifics) and I’ll set up the test accordingly.