Quote
397.38
+0.21 (+0.05%)
We have scored 86 news catalysts on SNPS (SNPS) over the past 12 months. Coverage across the window leans mixed (average ticker sentiment +0.01). Most of the impact sits in sector technology and price momentum.
Market cap
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P/E
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EPS
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Beta
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52W range
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Day range
394.25–400.83
Open
399.50
Prev close
397.17
Volume
1.2M
Avg volume
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Dividend
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IPO
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No scored news tagged SNPS or its network in the window yet.
Show more SNPS articles →Analysts publish price targets on SNPS, and they disagree. Where the share price actually sits among them shows which of their arguments the market is buying — and which it is ignoring.
13 analyst price targets from $450 to $633
as of 2026-09-10
The market is 29% below the median target — more cautious than the analysts.
The reconstruction
Daily OHLCV with SMA overlays and session pivots. Draw your levels and trendlines on it, or ask the AI analyst what the price is reacting to.
Suppliers, customers, partners and competitors, derived from what the news actually says about SNPS — not a sector bucket. Click an edge to see the articles that established the link.
Suppliers, customers, partners and competitors of SNPS, taken from what the news actually said about them rather than from a sector bucket. The count is how many articles established each link.
Latest scored catalyst for SNPS: .
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The price at $397 sits at the absolute floor of the published analyst range and is 29% below the median target, meaning the market has heard the bull case for AI-driven acceleration but actively refuses to pay for it.
What the disagreement turns on
Can Synopsys actually accelerate its top-line growth to a sustained 20%-plus rate using AI and integrated design tools, or is the recent 42% quarterly surge a temporary anomaly from the Ansys acquisition? The wired data can track segment revenue history to see if this acceleration persists quarter after quarter, but it cannot measure the pricing power or adoption rate of the new AI agent tools themselves.
The price pays for
It declines to pay for
Written by a language model from the published models, the reported segments and a reverse-DCF — not a recommendation, and not a house view.
Claim by claim
