MongoDB's $500M Volume Plummets 48.86% to 219th Ranking Amid Cautious Investor Sentiment

. 22, , . The stock's muted performance contrasted with broader market volatility, reflecting mixed investor sentiment toward its near-term trajectory.

Recent developments highlighted strategic shifts in enterprise adoption patterns, with analysts noting a growing emphasis on deployments. While MongoDB's database-as-a-service model remains competitive, market participants observed cautious positioning ahead of potential Q4 earnings guidance. Institutional holdings data showed reduced short-term speculative activity, though long-term holders maintained stable exposure levels.

Technical indicators suggested a consolidation phase, . , where previous attempts to break out had stalled. Market structure analysis indicated balanced buying and selling pressure, with no immediate catalysts identified to drive directional momentum.

To run this back-test accurately I need to pin down a couple of details that aren’t specified yet and make sure the approach matches what the platform can actually calculate. Universe • Which market’s “top-500 stocks” should be used? (e.g., all U.S. listed common stocks, all stocks in a specific index, a particular exchange, etc.) • If your universe is global or very broad, please confirm that an equally-weighted daily re-balance on 500 names is what you want. Weighting scheme • Equal weight each of the 500 names? (most common) • Or volume-weighted / market-cap-weighted? ? • Slippage/transaction cost assumptions: none unless you want them included. ? Once these points are clear I can generate the data-retrieval plan and run the back-test.