Intuit Falters Amid Macroeconomic Pressures as $1.6B Trade Volumes Rank 46th

On September 23, 2025, , , . The stock's performance followed mixed signals from recent earnings and strategic updates. .

Analysts noted that Intuit's shares underperformed despite strong product adoption metrics, as investors focused on its reduced market share in the small business software segment. Competitor advancements in AI-driven accounting tools and pricing pressures in the self-employed tax filing category were cited as key concerns. , reflecting ongoing bearish positioning.

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To run this back-test rigorously I need to pin down (or assume) a few practical details: 1. Market universe • Default I would use all U.S. listed common stocks that had an active daily quote during the test window (01-Jan-2022 to today). • If you prefer another universe (e.g. only S&P 500 constituents, only NYSE, only large-caps, a different country, etc.) please let me know. 2. Ranking and execution convention • I plan to rank stocks by that day’s total trading volume (shares, not dollars) using the official close. • The portfolio would be formed at the same close and liquidated at the next day’s close (i.e. 1-day holding period). • Positions would be equal-weighted across the 500 names selected each day. • Slippage/commissions: assumed zero unless you specify otherwise. 3. Output metrics • Aggregate daily portfolio return series, CAGR, annualized volatility, Sharpe ratio, max drawdown, and an equity-curve chart. • I will also compare the strategy to SPY as a passive benchmark unless you prefer a different yardstick. 4. Tool / engine note • Our built-in back-test engine handles one ticker at a time, so a 500-stock portfolio must be simulated explicitly from raw price & volume data. I will do that by fetching the full universe’s daily data, constructing the portfolio weights each day, and then computing the composite return series before feeding it into the visualization module.