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Takeaway: The technical side of Stanley Black & Decker (SWK) is weak, with bearish signals dominating, and our internal diagnostic score stands at 3.1/10 — suggesting caution for traders.
Analysts are split on SWK. The simple average rating is 3.33 (on a 1-5 scale), while the performance-weighted rating is just 1.60. The lack of consensus and the poor historical performance of some analysts raise questions about the reliability of recent calls. For instance:
Meanwhile, the stock has risen by 7.06% recently — a trend that doesn’t align well with the market's generally pessimistic expectations.
Fundamental Highlights:
While some fundamental factors show explosive growth, the low scores suggest these may not be sustainable or well-supported by market dynamics.
Big money is showing mixed signals. Large and extra-large funds are trending negative, while retail investors (small investors) are showing positive inflows. The overall inflow ratio is 0.4999, just below a neutral 0.50 — and our internal diagnostic score for fund flows is 7.78/10, which we consider “good.”
This suggests a tug-of-war between retail and institutional sentiment — with no clear direction.
Technically, the story is bearish. One bearish indicator is in play (Bearish Engulfing), and four recent overbought WR signals have appeared over the past five days. The WR Overbought indicator has a 2.13/10 internal diagnostic score, while Bearish Engulfing has a slightly better 4.07/10.
From August 15 to August 22, key patterns included:
Overall, momentum is weak and the technical signals are inconsistent — another reason to proceed with caution.
Stanley Black & Decker is showing strong fundamentals but weaker technicals and mixed analyst signals. With a technical score of 3.1/10 and a fund-flow score of 7.78/10, the market is caught between optimism and caution.
Actionable Takeaway: Consider waiting for a pull-back before entering a position. Keep an eye on the next earnings report and whether the overbought WR patterns hold or reverse — it could signal a turning point.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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