Linear Regression Trendline

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Description

Linear regression is a statistical tool used to predict future values from past values. In the case of security prices, it is commonly used as a quantitative way to determine the underlying trend and when prices are overextended.

A Linear Regression trendline uses the least squares method to plot a straight line through prices so as to minimize the distances between the prices and the resulting trendline.


Interpretation

If you had to guess what a particular security's price would be tomorrow, a logical guess would be “fairly close to today’s price.” If prices are trending up, a better guess might be “fairly close to today’s price with an upward bias.” Linear regression analysis is the statistical confirmation of these logical assumptions.

A Linear Regression trendline is simply a trendline drawn between two points using the least squares fit method. The trendline is displayed in the exact middle of the prices. If you think of this trendline as the “equilibrium" price, any move above or below the trendline indicates overzealous buyers or sellers.

A Linear Regression trendline shows where equilibrium exists. Raff Regression Channels show the range prices can be expected to deviate from a Linear Regression trendline.

The Time Series Forecast indicator displays the same information as a Linear Regression trendline. Any point along the Time Series Forecast is equal to the ending value of a Linear Regression Trendline plus its slope. For example, the ending value of a Linear Regression trendline (plus its slope) that covers 10 days will have the same value as a 10-day Time Series Forecast.

Linear Regression Trendlines is used to construct Raff Regression, Projection Bands, Projection Oscillator and the Linear Regression indicator.