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Asset logo for symbol SNPS
Synopsys
SNPS83
$522.53arrow_drop_down1.04%-$5.52
High Quality
S&P500
Asset logo for symbol SNPS
SNPS83

$522.53

arrow_drop_down1.04%

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Synopsys (SNPS) Stocklytics Forecast

Synopsys Inc (SNPS) is a leading provider of electronic design automation (EDA) software and services. The company has a strong track record of delivering innovative solutions to its customers and has established itself as a key player in the semiconductor industry. With its broad portfolio of products and services, Synopsys is well-positioned to benefit from the growing demand for advanced semiconductor technologies.
In terms of stock price prediction, analysts have a positive outlook on Synopsys Inc. They expect the stock to continue its upward trend in the coming years. According to the latest forecasts, the stock price is projected to reach new highs by 2023. The average price target for Synopsys Inc is also expected to increase significantly by 2023, indicating potential upside for investors.
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Frequently Asked Questions

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What is the analyst price prediction for Synopsys (SNPS) stock?

Analysts have set a target price of $619.29 for Synopsys (SNPS), based on forecasts from 24 analysts. The predicted price range extends from a high of $675 to a low of $485. This represents a potential increase of up to 29.18% and a decrease of -7.18% from the current price of $522.53. These forecasts are as of 2023 Aug 23.
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What are the analyst ratings for Synopsys (SNPS) stock?

The analyst ratings for Synopsys (SNPS) are distributed as follows: 20 analysts recommend buying, 3 have a neutral stance, and 0 suggest selling. The prevailing sentiment among the total of 23 analysts leans towards a buy rating. These ratings indicate the general sentiment among the analysts covering Synopsys .
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What is the AI price prediction for Synopsys (SNPS) stock?

At present, there is no AI or machine-learning-based price prediction available for Synopsys (SNPS) stock. The lack of a forecast could stem from various factors, such as inadequate data or the necessity for model recalibration.

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