Used to determine the direction of a trend, a Linear Regression Line runs through a set of prices so that the smallest amount of space exists between all of the price points and the Linear Regression Line. Instead of a price chart with scattered price points, the Linear Regression Line allows you to clearly see whether prices are trending upward, downward or sideways.
Prices tend to move above and below the Linear Regression Line. As a result, when prices are below the line, analysts typically predict prices will rise, and when they're above the line, prices are predicted to fall back toward the Linear Regression Line.
Some analysts also plot Linear Regression Channel Lines, which are lines that run parallel and equidistant from the central trend line. The channel lines are plotted based on the furthest closing points - both high and low - from the Linear Regression Line. Plotting these lines can provide a visual representation of the trend as well as the range where you can expect trading to occur. While the middle line may help you predict a security's likely price, the bottom line shows the security's support level, and the top line quantifies the resistance level.
Linear Regression Lines are created using a complex calculation called the least squares method.
The Linear Regression indicator is calculated by fitting a linear regression line over the values for the given period, and then determining the current value for that line. A linear regression line is a straight line that is as close to all of the given values as possible.
Unlike a Moving Average, the Linear Regression Indicator does not exhibit as much delay. As the Linear Regression Indicator is fitting a line to the data points rather than simply averaging them, the Linear Regression line becomes more responsive to changes in prices.
When prices are persistently higher or lower than the forecasted price, you can typically expect them to return to more realistic levels. The Linear Regression Indicator shows where prices should be trading on a statistical basis and any excessive deviation from the regression line is likely to be short-lived.
The strategies described in this article are for information purposes only, and their use does not guarantee a profit. None of the information provided should be considered a recommendation or solicitation to invest in, or liquidate, a particular security or type of security. Investors should fully research any security before making an investment decision. Securities are subject to market fluctuation and may lose value.