Linear Regression Channels

Linear Regression Channels represent a method for computing a mean line which forms the best fit to a given set of data points and two parallel lines above and below the mean line which provide resistance and support respectively.

Linear Regression Channels

Linear Regression Channels represent a method for computing a mean line which forms the best fit to a given set of data points and two parallel lines above and below the mean line which provide resistance and support respectively.

There are several types of Linear Regression Channels including Breakout Standard Regression Channel,   Classic Standard Regression Channel and Raff Regression Channel.

Linear Regression Channels Calculation

Linear Regression Channels are started by first plotting the (middle) baseline channel using the first 'n' points in a chart.  The baseline channel is extended until the price breaks out of the channel and then a new channel computation begins.  The upper and lower lines are dependent upon the type of Linear Regression Channel to be drawn.

Linear Regression Channels Interpretation

Linear Regression Channels are a means for computing a line which forms the best fit to a given set of data points and two parallel lines above and below the mean line which provide resistance and support respectively.  Multiple regression channels are drawn because the high or low price may break the trend of the previous regression channel over the course of time.

The Linear Regression Channel is drawn using lines that are spaced a number of standard deviations above and below the (middle) linear regression line.