Stocklytics Platform
Asset logo for symbol CTVA
Corteva
CTVA64
$55.39arrow_drop_up0.19%$0.11
High Growth
S&P500
Asset logo for symbol CTVA
CTVA64

$55.39

arrow_drop_up0.19%

AI Deep-Learning Forecast (CTVA)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Corteva (CTVA) Stocklytics Forecast

Corteva Inc (CTVA), a leading global agricultural chemicals and seeds company, has been gaining attention from investors who are looking to forecast the future price of its stock. The company was formed in 2019 as a result of the merger between Dow Chemical's agricultural division and DuPont's agriculture business. With a diverse portfolio of products and services, Corteva aims to meet the evolving needs of farmers worldwide.
When it comes to predicting the future stock price of CTVA, various methods can be employed. One approach is using artificial intelligence (AI), which utilizes complex algorithms to analyze historical data, market trends, and other relevant factors. AI-based predictions have become increasingly popular among investors due to their potential for accuracy and speed. Machine learning, a subset of AI, can also be employed to enhance the accuracy of predictions by continuously learning and adjusting based on new data.
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Frequently Asked Questions

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What is the analyst price prediction for Corteva (CTVA) stock?
Analysts have set a target price of $59.56 for Corteva (CTVA), based on forecasts from 28 analysts. The predicted price range extends from a high of $69 to a low of $2.59. This represents a potential increase of up to 24.57% and a decrease of -95.32% from the current price of $55.39. These forecasts are as of 2023 Nov 10.
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What are the analyst ratings for Corteva (CTVA) stock?
Currently, there are no analyst ratings available for Corteva (CTVA), possibly due to insufficient coverage or recent updates.
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What is the AI price prediction for Corteva (CTVA) stock?
At present, there is no AI or machine-learning-based price prediction available for Corteva (CTVA) 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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