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Takeaway:
(TER) is showing mixed signals with a recent 4.03% price rise but faces a weak technical outlook. Analysts remain optimistic, but internal diagnostic scores suggest caution from a chart pattern perspective.Analysts are generally bullish on Teradyne. The simple average rating is 3.80, while the performance-weighted rating is 4.62, indicating strong alignment between analyst expectations and past performance. However, the ratings are not consistent — there are 3 “Neutral” and 2 “Strong Buy” ratings in the last 20 days, showing some dispersion among professionals.
The current price trend (4.03% rise) matches the weighted expectations of analysts, who appear to be optimistic about the company's medium-term outlook. The internal diagnostic fundamental score is 5.85 (of 10), reflecting solid cash flow and operational efficiency, but some pressure from declining margins and profit growth.
Big money is moving cautiously. The overall fund-flow score is 7.39 (good). Large and extra-large investors have a negative trend, while small and medium investors are positive. The block trend is negative, but the overall inflow ratio is 40.08%, suggesting modest net inflows despite some institutional caution.
Teradyne’s technical outlook is weak, with a technical score of 1.85 (of 10). The chart has shown more bearish than bullish signals in the last five days, and the overall trend is bearish. Here’s a breakdown of key indicators:
Recent patterns include:
Key Insights: Bearish signals dominate (3 to 0), and the market is currently in a weak technical state. Investors are advised to avoid Teradyne at this time based on chart behavior.
While Teradyne has a strong analyst rating and positive cash flow fundamentals, the technical picture is weak with internal diagnostic scores near the bottom of the 0-10 range. With a recent 4.03% price rise, the company is showing short-term momentum but faces conflicting signals. Investors should consider waiting for a pull-back or clearer technical confirmation before entering a position.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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