JD's Trading Volume Plunges 31.65% to 540M as Stock Slides to 207th in U.S. Equities

On October 3, 2025, JD (NMS: JD) recorded a trading volume of $540 million, marking a 31.65% decline from the previous day. The stock ranked 207th in trading activity among U.S. equities and closed with a 1.61% decline.

It sounds like you’d like to create a daily-rebalanced, equal-weighted portfolio consisting of the 500 most-actively-traded U.S. stocks (ranked by dollar volume), hold that basket for one trading day, then repeat the process each day from 2022-01-03 through today. At the moment, the back-testing engine available in this workspace works on a single-ticker price series. To implement a cross-sectional strategy that changes its holdings every day we would need to: 1. Recompute the top-500 list for every trading day in the period. 2. Aggregate the one-day return of those 500 names into a single “portfolio return” series. 3. Feed that aggregated return series to the back-test engine (as if it were the price of a synthetic ticker). Our current tool set can handle Step 3, but Steps 1–2 require data gathering and processing that the tools here don’t directly expose. Two ways we can proceed: A. Approximation route • Use an existing index or ETF that already covers the largest-volume stocks (for example, SPY or another high-liquidity index) as a proxy. • Back-test the 1-day-hold strategy on that proxy. B. Custom data route (more accurate but more involved) • Retrieve the full daily trading-volume data for the entire U.S. equity universe. • Programmatically build the top-500 list and corresponding equal-weighted return series. • Back-test the resulting synthetic index. (This would require a multi-step data-engineering workflow that is beyond the one-ticker tools currently exposed.) Please let me know which path you’d like to take, or if you have another preference.