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Takeaway:
(IR) is currently showing technical weakness with a score of 4.06 (internal diagnostic score, 0-10), while fundamentals and analyst ratings remain mixed. The stock has fallen 1.08% recently, diverging from the market’s optimistic bias.Analysts remain divided in their outlook for Ingersoll Rand. The simple average rating is 4.00, while the performance-weighted rating is 4.40. This suggests a generally positive bias when factoring in the historical success of the analysts.
However, the ratings are not consistent, with recent 20-day ratings including "Strong Buy," "Buy," and "Neutral." This divergence indicates uncertainty among analysts about the stock’s direction.
The stock’s price has fallen 1.08% recently, which contrasts with the overall optimistic analyst bias. This mismatch suggests caution for potential buyers.
Money-flow patterns show a negative trend overall, with large and extra-large investors pulling back. The inflow ratios, however, are relatively balanced across different investor sizes:
Despite the negative trend, the fund-flow score is 7.72 (internal diagnostic score, 0-10), indicating good liquidity and investor confidence at the retail level.
Technically, Ingersoll Rand is showing weakness, with 3 bearish indicators and only 1 bullish indicator in the recent 5-day analysis. The technical score is 4.06 (internal diagnostic score, 0-10).
Key dates and patterns include:
Insight: The technical signals are mixed but bearish overall. The market appears to be in a consolidation phase with no clear trend. Traders should be cautious and watch for a breakout or breakdown.
Ingersoll Rand is in a period of technical consolidation with a low technical score of 4.06 (internal diagnostic score, 0-10). While fundamentals remain stable and analysts are generally positive, the recent price action diverges from these expectations.
Actionable Takeaway: Consider waiting for a clearer trend or a pullback before entering long positions. Investors should monitor earnings and macroeconomic developments, especially in the machinery and industrial sectors, for potential catalysts.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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