Stocklytics Platform
Asset logo for symbol SURG
Surge Holdings
SURG64
$3.16arrow_drop_up3.45%$0.10
Penny Stock
Asset logo for symbol SURG
SURG64

$3.16

arrow_drop_up3.45%

Analyst Forecast

Period: Next 12 Months

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Analyst Ratings

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Surge Holdings (SURG) Stocklytics Forecast

Surge Holdings, Inc. (SURG) is a company that operates in the telecommunications and financial technology sectors. The company provides wireless, telecom, and fintech products and services to the underbanked and unbanked population. With a focus on low-income individuals and communities, Surge Holdings aims to bridge the digital divide and provide accessible and affordable solutions.
When it comes to predicting the stock price of Surge Holdings, Inc. (SURG), there are several factors to consider. While AI and machine learning technologies have made significant advancements in the field of stock price prediction, it is important to note that these predictions are not foolproof and should be taken with a grain of salt.
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Frequently Asked Questions

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What is the analyst price prediction for Surge Holdings (SURG) stock?

Analysts have set a target price of $8.5 for Surge Holdings (SURG), based on forecasts from 3 analysts. The predicted price range extends from a high of $10 to a low of $6. This represents a potential increase of up to 216.46% and a decrease of 89.87% from the current price of $3.16. These forecasts are as of 2012 Mar 14.
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What are the analyst ratings for Surge Holdings (SURG) stock?

The analyst ratings for Surge Holdings (SURG) are distributed as follows: 1 analysts recommend buying, 1 have a neutral stance, and 0 suggest selling. There is a split consensus, with equal support for two of the rating categories. These ratings indicate the general sentiment among the analysts covering Surge Holdings.
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What is the AI price prediction for Surge Holdings (SURG) stock?

At present, there is no AI or machine-learning-based price prediction available for Surge Holdings (SURG) 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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