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Headline Takeaway:
(SNPS) faces a weak technical outlook with a score of 2.97 (internal diagnostic score, 0-10), suggesting caution for investors.Analysts are mixed in their outlook for Synopsys. The simple average rating is 4.50, while the performance-weighted rating is 2.58. This disparity indicates low rating consistency, with two recent ratings of 'Buy' and 'Strong Buy' clashing with a recent price decline of -2.85%.
On the fundamentals, the model assigns an overall score of 7.46 (internal diagnostic score, 0-10), with the following key values:
Though fundamentals suggest a reasonably healthy balance sheet and profitability, recent performance and valuation indicators show signs of pressure.
Big money is showing caution, with negative overall trends in fund flows. Institutional and large investors have seen inflow ratios hovering around 49.8% (Large) to 46.7% (Extra-large), suggesting a mixed sentiment.
On the retail side, Small and Medium trends are negative with inflow ratios of 49.6% and 49.8%, respectively. The overall inflow ratio for the stock is 47.8%, indicating limited retail participation and a cautious market environment.
Technically, the stock is weak. The model assigns it a score of 2.97 (internal diagnostic score, 0-10) based on the following indicators:
Recent chart activity includes a MACD Death Cross on August 6, 2025, and a WR Oversold signal on August 11, 2025. However, bearish indicators continue to dominate the recent 5-day period.
Synopsys remains under technical pressure, with three bearish signals outweighing any bullish ones. While the fundamentals remain reasonably solid, the recent negative price trend and weak technical setup suggest investors should consider avoiding new entries and instead wait for a clearer signal of recovery. With regulatory headwinds still in place, monitoring upcoming earnings and potential policy shifts could offer better insight into the stock’s near-term direction.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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