Stocklytics Platform
PepsiCo
PEP54
$148.34arrow_drop_up0.11%$0.17
NYSE - As of Mar 13, 5:41 PM EDT Market Closed
S&P500
PEP54

$148.34

arrow_drop_up0.11%

Analyst Forecast

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Analyst Ratings

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PepsiCo (PEP) Stocklytics Forecast

PepsiCo Inc (PEP) is a multinational food and beverage corporation with a strong presence in the global market. With a diverse portfolio of brands including Pepsi, Lay's, Gatorade, Tropicana, and Quaker, the company has consistently delivered solid financial performance. Investors are always interested in predicting the future stock price of PepsiCo Inc, and various methods like AI and machine learning are being used for this purpose.
The stock price of PepsiCo Inc is influenced by a multitude of factors, including consumer trends, competition, economic conditions, and the overall performance of the company. Analysts study these factors and undertake extensive research to make price predictions. However, it is important to note that predicting stock prices is inherently uncertain, and no method can provide a foolproof forecast.
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Frequently Asked Questions

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What is the analyst price prediction for PepsiCo (PEP) stock?

Analysts have set a target price of $189.45 for PepsiCo (PEP), based on forecasts from 29 analysts. The predicted price range extends from a high of $211 to a low of $170. This represents a potential increase of up to 42.24% and a decrease of 14.6% from the current price of $148.34. These forecasts are as of 2023 Jul 14.
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What are the analyst ratings for PepsiCo (PEP) stock?

The analyst ratings for PepsiCo (PEP) are distributed as follows: 9 analysts recommend buying, 13 have a neutral stance, and 1 suggest selling. The prevailing sentiment among the total of 23 analysts leans towards a neutral rating. These ratings indicate the general sentiment among the analysts covering PepsiCo .
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What is the AI price prediction for PepsiCo (PEP) stock?

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