Fortinet Surges 3.13% as Volume Spikes 77.23% to 830 Million Climbs to 119th in Market Activity

, 2025, , ranking 119th in market activity. . The stock’s rally followed a confluence of signals including a bullish crossover, divergence from oversold levels, . compression and volume expansion above average levels further reinforced potential for a near-term reversal.

. near this level since early September, coupled with higher lows, suggested buying pressure. , , indicating structural weakness. diverged from price, .

Volume analysis confirmed conviction behind the rally, . The surge followed a on September 2, . Subsequent higher closes on increasing volume supported reversal potential. , creating a high-probability target zone if the sustains. However, .

To set up this back-test rigorously I need to pin down a couple of practical details about the trading rule and the data universe: 1. Market universe • Should we screen all U.S.–listed common stocks (NYSE + NASDAQ + AMEX) each day, or limit it to a specific index (e.g., , , etc.)? • , and preferred shares: include or exclude? 2. Ranking and execution timing • Volume ranking is taken from which session? – : Rank on today’s end-of-session volume, buy at that same close, sell at tomorrow’s close. – : Rank on yesterday’s volume, buy at today’s open, sell at tomorrow’s open. • Which of these reflects your intent (or another variant)? 3. Transaction-cost assumptions • If you would like commissions and/or slippage modelled, please specify; otherwise I’ll run the back-test gross of costs. 4. for entry/exit • Close-to-close (default if you have no preference) • Open-to-open • Another choice? Once I have these details I can fetch the appropriate daily price and volume data, generate the daily portfolios, and compute the strategy performance from 2022-01-03 (first trading day of 2022) through today.