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Takeaway:
(DE) is showing mixed signals with weak technical indicators, but decent money flows offer some support. Current price is down -1.70%, and analysts remain divided.Recent news has included developments across agriculture, tech, and geopolitics:
Analysts are split, with a simple average rating of 4.00 and a performance-weighted average of 2.84. There are five institutions involved, with ratings ranging from “Underperform” to “High quality institutions,” indicating a clear dispersion of views. The current price trend is negative (-1.70%), but the market's neutral expectations align with the price direction.
Key fundamentals:
Big-money flows are currently negative, with large and extra-large investors pulling back. The block inflow ratio is at 48.78%, indicating cautious sentiment among institutional players.
On the positive side, retail flows are positive, with the Small_inflow_ratio at 50.33%. This suggests retail investors are still optimistic, even as big money remains bearish. The fund-flow score is 7.78 (good), indicating decent overall support despite the mixed institutional signal.
Technical indicators for Deere over the last 5 days are mixed, with 2 bull and 2 bear signals, leading to an internal diagnostic score of 4.18, indicating “Weak technology, need to be cautious.”
Recent chart patterns (by date):
Overall, the momentum is unclear. While some reversal patterns like the Inverted Hammer suggest a potential bottom, the bearish signals and volatility remain a concern.
Deere remains in a volatile, directionless phase with mixed signals from analysts and technical indicators. While fundamentals remain strong in some areas, the recent price decline and bearish technical indicators warrant caution. Consider waiting for a clearer breakout or retest of key levels before taking a position. Keep a close eye on upcoming earnings and any follow-up to the recent dividend announcement for guidance on potential short-term moves.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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