Stocklytics Platform
CHE
Chemed
CHE62
$585.46arrow_drop_up1.02%$5.96
CHE
CHE62

$585.46

arrow_drop_up1.02%

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Chemed (CHE) Stocklytics Forecast

Chemed Corp (CHE) is a leading healthcare services company that operates through its two subsidiaries: VITAS Healthcare and Roto-Rooter. With a strong presence in the end-of-life care market and plumbing and drain cleaning services, Chemed Corp has established itself as a reliable and innovative organization. As investors and analysts closely monitor the company's performance, there is increasing interest in predicting Chemed Corp's stock price and forecasting its future prospects.
While it is impossible to predict the exact future stock price of any company with complete certainty, experts and AI-powered predictions provide valuable insights. According to AI-based price predictions for CHE, the stock is expected to exhibit positive growth in the coming years. Machine learning algorithms analyze a variety of historical data, market trends, and key performance indicators to generate these predictions. Considering the strong market position of Chemed Corp and its consistent growth, it is reasonable to anticipate a positive stock price forecast for CHE.
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Frequently Asked Questions

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What is the analyst price prediction for Chemed (CHE) stock?

Analysts have set a target price of $560.53 for Chemed (CHE), based on forecasts from 15 analysts. The predicted price range extends from a high of $625 to a low of $225. This represents a potential increase of up to 6.75% and a decrease of -61.57% from the current price of $585.46. These forecasts are as of 2013 Jun 11.
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What are the analyst ratings for Chemed (CHE) stock?

Currently, there are no analyst ratings available for Chemed (CHE), possibly due to insufficient coverage or recent updates.
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What is the AI price prediction for Chemed (CHE) stock?

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