Stocklytics Platform
Asset logo for symbol NI
NiSource
NI60
$30.49arrow_drop_down0.58%-$0.18
S&P500
Asset logo for symbol NI
NI60

$30.49

arrow_drop_down0.58%

AI Deep-Learning Forecast (NI)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

NiSource (NI) Stocklytics Forecast

NiSource Inc (NI) is a leading natural gas and electric utility company operating in the United States. The company has a strong track record of delivering reliable and affordable energy to its customers. As an investor, you may be interested in understanding the future prospects of NI stock. In this forecast, we will look at the stock price prediction for NiSource Inc and analyze the factors that may influence its performance.

Forecasting stock prices is a complex task that involves analyzing various factors such as market trends, financial performance, industry outlook, and investor sentiment. While it is impossible to predict the future with certainty, financial analysts and experts use different methodologies to estimate the potential price movements of a stock.

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Frequently Asked Questions

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What is the analyst price prediction for NiSource (NI) stock?

Analysts have set a target price of $29.95 for NiSource (NI), based on forecasts from 21 analysts. The predicted price range extends from a high of $35 to a low of $25. This represents a potential increase of up to 14.79% and a decrease of -18.01% from the current price of $30.49. These forecasts are as of 2020 Jul 21.

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What are the analyst ratings for NiSource (NI) stock?

The analyst ratings for NiSource (NI) are distributed as follows: 6 analysts recommend buying, 8 have a neutral stance, and 0 suggest selling. The prevailing sentiment among the total of 14 analysts leans towards a neutral rating. These ratings indicate the general sentiment among the analysts covering NiSource .

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What is the AI price prediction for NiSource (NI) stock?

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