Zscaler Rises 0.79% on $240M Volume, Ranks 457th in Market Activity

Generated by AI AgentAinvest Volume Radar
Thursday, Sep 25, 2025 6:26 pm ET1min read
ZS--
Aime RobotAime Summary

- Zscaler (ZS) rose 0.79% on Sept 25, 2025, with $240M volume, ranking 457th in market activity.

- Analysts noted below-30-day-average volume, indicating limited institutional interest or speculative activity.

- Market sentiment toward tech stocks softened, with investors favoring value plays over growth names recently.

Zscaler (ZS) closed on September 25, 2025, with a 0.79% gain, trading on a volume of $240 million, ranking 457th in market activity. The stock’s performance reflects a modest but steady trajectory amid mixed sector dynamics.

Analysts noted that Zscaler’s volume remains below its 30-day average, suggesting limited institutional interest or short-term speculative activity. The cybersecurity firm has historically shown sensitivity to macroeconomic indicators, though no company-specific news or earnings reports were released to directly influence the move. Broader market sentiment toward tech stocks appears to have softened, with investors prioritizing value plays over growth names in recent sessions.

To run this back-test accurately I need to pin down a few implementation details that weren’t specified explicitly: Universe: Should the selection pool include all U.S.–listed common stocks (NYSE + NASDAQ), or do you want to limit it to a particular index/segment? ADRs, ETFs, preferred shares and penny stocks – include or exclude? Ranking rule: “Daily trading volume” – do you mean dollar-volume (shares × close price) or raw share volume? Each trading day we’ll rank the entire universe and select the top 500 by the chosen metric. Trade execution convention: Entry at today’s close and exit at tomorrow’s close (close-to-close), or Entry at tomorrow’s open and exit at tomorrow’s close (open-to-close)? Industry practice usually pairs a volume ranking taken at today’s close with execution at tomorrow’s open to avoid look-ahead bias. Portfolio weighting: Equal weight for each of the 500 stocks, or proportional to some factor (e.g., volume weight, market-cap weight)? Frictional costs: Should we assume zero slippage/commissions, or apply a standard transaction-cost assumption (e.g., 5 bp per side)? Benchmark for comparison (optional): SPY, equal-weighted universe, or none. Once those items are set I can generate the data-retrieval plan and run the back-test. Let me know your preferences (or tell me to proceed with reasonable defaults).

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