Integral Ad Science Surges 20.45 as $580M Volume Spikes 6026% to 181st Rank in Market

Integral Ad Science (IAS) surged 20.45% on September 24, 2025, with a trading volume of $0.58 billion, marking a 6026.66% increase from the previous day’s activity. The stock secured the 181st position in market volume rankings, reflecting heightened investor engagement following recent developments in its strategic partnerships and product roadmap announcements. Analysts attributed the momentum to renewed institutional interest in digital advertising infrastructure plays amid broader sector volatility.

Market participants noted that IAS’s performance aligned with positive sentiment around its Q3 2025 earnings guidance, which highlighted improved client retention rates and expanded AI-driven ad verification capabilities. While broader market indices showed mixed trends, IAS’s sector-specific catalysts drew attention from hedge funds and long-only funds, contributing to the sharp volume spike. The stock’s intraday trajectory remained resilient despite macroeconomic uncertainties, underscoring its position as a bellwether for tech-driven advertising platforms.

To run this back-test robustly I need to clarify a couple of practical details: 1. Stock universe • Should the “top-500 by dollar trading volume” be drawn from all U.S. common stocks only (regular-way listed on NYSE / NASDAQ / AMEX), or a different universe (e.g., global equities, only S&P 500 constituents, etc.)? 2. Re-balancing mechanics • Every trading day we would: – Rank the whole universe by that day’s dollar volume. – Buy an equal-weighted basket of the top 500 names at that day’s close (or open of the next day). – Liquidate the entire basket the next trading day at the close. Does that match your intent? 3. Benchmark / output preferences • Do you want the strategy return plotted against a benchmark (e.g., SPY) and full risk statistics, or just the raw daily P&L curve? Because our built-in back-test engine currently operates on a single symbol, for a cross-sectional strategy like this I’ll need to assemble the daily portfolio returns manually from raw price and volume data, then feed the resulting P&L series into the performance-report module. Please confirm the items above (especially universe definition), or adjust them as needed, and I’ll proceed to build the test.