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Intro To Linear Regressions Lines – Find Out How They Complement Other Indicators

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In this illustrated guide to understanding the Linear Regression Line, we’ll show you what this chart looks like, explain how to interpret it, and discuss caveats when using it.

What Is a Linear Regression Line?

A Linear Regression Line is a straight line that best fits the prices between a starting price point and an ending price point.

A “best fit” means that a line is constructed where there is the least amount of deviation between the price points and the actual Linear Regression Line.

What Is the Linear Regression Line Used For?

The Linear Regression Line is mainly used to determine trend direction. A chart of AT&T (T) stock is given below:

linear regression line shows the general trend of a stock over time

Interpreting the Linear Regression Line Chart

Traders usually view the Linear Regression Line as the fair value price for futures, stocks, or forex currency pairs.

When prices deviate above or below, traders may expect prices to move back towards the Linear Regression Line.

As a consequence, when prices are below the Linear Regression Line, this could be viewed as a good time to buy, and when prices are above the Linear Regression Line, a good time sell.

Caveats

Of course, the Linear Regression Line is a very simple test. Other technical indicators would be used to confirm these crude buy and sell signals.

A useful technical analysis charting indicator that uses a Linear Regression Line is the Linear Regression Channel, which gives more objective potential buy and sell signals based on price volatility.

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FAQ

Below we answer some common questions about Linear Regression Line indicators.

What does regression mean?

In statistics and technical charting, regression is a mathematical description of the relationship between an output variable (like stock price) based on any number of input variables (like dates). The word “regression” implies that the equation is “looking back” at previous prices as a means of predicting future price movements.

Further Reading

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