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Webull (BULL) surged 3.55% on Sept. 26, 2025, with a trading volume of $530 million, marking a 50.74% increase from the previous day. The stock ranked 181st in volume among U.S. equities, reflecting heightened investor interest in the platform’s growth potential. Recent developments highlighted its expanding institutional partnerships and product innovations, which analysts suggest could drive further momentum in the coming quarters.
Back-test parameters for evaluating trading strategies involving
require precise definitions of stock universes, pricing rules, and cost assumptions. Key considerations include whether to focus solely on U.S.-listed common stocks, exclude ETFs or SPACs, and specify entry/exit timing using daily close prices. Position sizing methods, such as equal-weight allocations, and transaction cost models must also be standardized to ensure methodological consistency. These details will shape the accuracy of performance metrics across the 2022-2025 period.To set up this back-test rigorously, I need to pin down a few practical details of the trading rule and data universe: Stock universe • US-listed common stocks only (NYSE + NASDAQ), or a different market? • Should ETFs, ADRs, SPACs, etc. be excluded? Daily prices • Use the official daily close price to enter and exit, or the next day’s open? (Typical “hold 1 day” tests buy at today’s close and sell at tomorrow’s close, but some traders prefer open-to-open.) Position sizing • Equal-weight the 500 names each day (i.e., 0.2% of equity per position), or another weighting? Transaction costs / slippage • Do you want to include a per-trade cost assumption (e.g., 2 bp per side), or ignore trading frictions? Once these items are fixed, I can generate the data-retrieval plan, compute the daily “top-500-by-volume” lists, and run the portfolio back-test from 2022-01-03 through today.

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