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Takeaway:
(IT.N) is showing mixed signals with recent price gains of 5.13%, but technical indicators remain bearish and fundamentals underperforming. Stance: Cautious.Recent news affecting the broader market includes:
Gartner has drawn mixed opinions from top analysts in the last 20 days. The simple average rating is 3.12, while the historical performance-weighted rating is slightly lower at 2.72. These scores suggest a cautious stance overall. Ratings are not consistent, with a mix of "Buy," "Strong Buy," "Sell," and "Neutral" calls.
Analysts from Barclays (Manav Patnaik) and Wells Fargo (Jason Haas) stand out for higher historical win rates (80.0% and 57.1%, respectively), but recent signals show conflicting directions—Haas recommends "Sell," while Patnaik calls "Buy."
The fundamental score is 3.33 (on a 10-point scale), suggesting the company is below average in key financial metrics, especially in liquidity and profitability. The stock appears to be in a weak financial position, with low cash availability and high leverage.
Big money is flowing out of Gartner as of late. The fund-flow score is 7.62 (internal diagnostic score), labeled "good," but the overall inflow ratio is 46.39%, with negative trends in all categories, from small to extra-large investors. Big institutions are also pulling back, with a block inflow ratio of just 45.90%.
Technical analysis remains bearish for Gartner:
Recent patterns by date:
This pattern mix indicates a weak technology setup with no clear momentum. The technical score is 4.31 (out of 10), which aligns with a weak trend and high caution.
Given the mixed analyst views, weak fundamentals, and bearish technical signals, investors should take a cautious approach with Gartner (IT.N). The price has risen 5.13% recently, but this appears to be at odds with the broader trend. Consider waiting for a pull-back before entering a position, and keep a close eye on upcoming earnings and macroeconomic data that may shift the balance.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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