Ondas Holdings Surges 15.47% on $370M Volume Ranks 307th in Market Activity

, 2025, , ranking 307th in market activity. The stock's performance drew attention amid limited market commentary, as liquidity levels remained elevated despite mixed broader market conditions.

Backtesting parameters for volume-driven strategies indicate a standardized framework is required. A typical approach would focus on Russell 1000 constituents ranked by daily share volume, with positions initiated at day's close and exited at the next close. Transaction costs are typically excluded in such analyses to isolate pure volume-driven returns without frictional adjustments.

Implementation of this methodology requires defining key variables: universe scope (e.g., Russell 1000), ranking criteria (share volume vs. dollar volume), timing rules (close-to-close execution), and cost assumptions. These parameters directly influence the reliability of backtest results and should align with practical trading constraints.

To deliver a robust back-test we need to nail down a few practical details first: 1. Universe • “All U.S.–listed common stocks” can run into several thousand names each day and requires large-scale data pulls. • A workable alternative is to confine the universe to (a) S&P 500 constituents or (b) Russell 1000 constituents, both of which still give very liquid names. 2. Definition of “Top 500 by volume” • Absolute share volume each day, ranked within the chosen universe? • Or dollar-volume (shares × price)? 3. Trade timing and prices • Enter at today’s close and exit at tomorrow’s close (close-to-close return), or • Enter at tomorrow’s open and exit at tomorrow’s close (open-to-close return)? 4. Transaction frictions • Do we ignore commissions/slippage, or would you like to assume a flat cost (e.g., 2 bp each side)? Once we lock these in, I can generate the data-retrieval plan and execute the full back-test.