Stocklytics Platform
Asset logo for symbol GME
GameStop
GME70
$32.73arrow_drop_up5.54%$1.71
Asset logo for symbol GME
GME70

$32.73

arrow_drop_up5.54%

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

GameStop (GME) Stocklytics Forecast

As investors eagerly await the future of GameStop Corp (GME) stock, price predictions and forecasts have become a hot topic. Many analysts and financial experts are attempting to gauge where the stock's value will be headed in the coming years, specifically in 2023. While it is important to note that financial predictions are speculative and not guaranteed, they can provide some insights into potential future trends.
GameStop Corp, being a popular gaming retailer, has recently experienced significant volatility in its stock price. The rise of digital gaming and the emergence of new competitors have posed challenges for the company's traditional brick-and-mortar model. However, the recent frenzy surrounding GameStop Corp, fueled by social media and retail investor activism, has generated renewed interest and attention.
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Frequently Asked Questions

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What is the analyst price prediction for GameStop (GME) stock?

Analysts have set a target price of $14 for GameStop (GME), based on forecasts from 20 analysts. The predicted price range extends from a high of $50 to a low of $5. This represents a potential increase of up to 52.77% and a decrease of -84.72% from the current price of $32.73. These forecasts are as of 2019 May 20.
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What are the analyst ratings for GameStop (GME) stock?

The analyst ratings for GameStop (GME) are distributed as follows: 0 analysts recommend buying, 0 have a neutral stance, and 1 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 GameStop.
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What is the AI price prediction for GameStop (GME) stock?

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