Stocklytics Platform
Asset logo for symbol EVR
Evercore
EVR68
$240.50arrow_drop_down0.53%-$1.29
High Growth
Asset logo for symbol EVR
EVR68

$240.50

arrow_drop_down0.53%

AI Deep-Learning Forecast (EVR)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Evercore (EVR) Stocklytics Forecast

Evercore Inc (EVR) is a leading global independent investment banking advisory firm. The company provides a range of services, including strategic advisory, financial restructuring, and capital markets execution. With its strong track record and expertise, Evercore has become a trusted advisor to many of the world's largest corporations, financial institutions, and governments.

Looking ahead, the stock price forecast for Evercore Inc (EVR) appears promising. Analysts expect continued growth and positive performance in the coming years. The company's solid financial position and strategic initiatives position it well for success. Furthermore, Evercore's strong client relationships and global network provide a competitive edge in the investment banking industry.

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Frequently Asked Questions

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What is the analyst price prediction for Evercore (EVR) stock?

Analysts have set a target price of $131 for Evercore (EVR), based on forecasts from 26 analysts. The predicted price range extends from a high of $193 to a low of $85. This represents a potential increase of up to -19.75% and a decrease of -64.66% from the current price of $240.51. These forecasts are as of 2022 Jan 06.

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What are the analyst ratings for Evercore (EVR) stock?

The analyst ratings for Evercore (EVR) are distributed as follows: 3 analysts recommend buying, 5 have a neutral stance, and 0 suggest selling. The prevailing sentiment among the total of 8 analysts leans towards a neutral rating. These ratings indicate the general sentiment among the analysts covering Evercore .

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What is the AI price prediction for Evercore (EVR) stock?

At present, there is no AI or machine-learning-based price prediction available for Evercore (EVR) 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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