Trading Volume Plunge Sends Stock to 312th Rank as Market Engagement Dips 58.62%

On September 22, 2025, , . , reflecting a significant reduction in market engagement.

Back-testing parameters for evaluating The’s performance require precise definitions to ensure methodological accuracy. Key considerations include the selection universe—whether all U.S.-listed stocks or a subset like the Russell 3000—and the exclusion criteria for instruments such as ADRs or ETFs. Rebalancing mechanics also demand clarity, including timing (close-to-close vs. close-to-open-to-close) and whether equal-weighting applies across 500 holdings.

Return aggregation poses additional complexity, as current systems assess single tickers rather than portfolio-level performance. Transaction costs, slippage assumptions, and price-type consistency (e.g., closing prices) must be explicitly defined to align with back-testing capabilities. Finalizing these parameters will enable a structured data-gathering plan and execution of the test.

To run this test robustly I need to clarify a few practical details and confirm that the approach aligns with the capabilities of the back-testing engine: 1. Universe • Are we selecting among all U.S.-listed stocks, or a narrower universe (e.g., constituents of the , S&P 1500, etc.)? • Do , ETFs or preferred shares need to be excluded? 2. Re-balancing mechanics • Do we rebalance at today’s close and exit at tomorrow’s close (), or buy at tomorrow’s open and exit at tomorrow’s close (close-to-open-to-close)? • each of the 500 names at entry? 3. Return aggregation • Our current back-test engine evaluates a single ticker at a time. If you want a portfolio-level (e.g., equal-weighting 500 symbols every day) we’ll need to build that in an external calculation layer. • Is a portfolio return series required, or do you want the individual stock-level statistics instead? 4. / slippage • Should we assume zero, or apply a fixed ? 5. Price type • Is “close” acceptable for both entry and exit? Once these points are confirmed I can lay out the exact data-gathering plan (volume ranks, daily rebalancing signals, etc.) and run the back-test.