|
Linear
Regression Trendline
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. |
