regression may sound intimidating, but the mathematical concept is a
simple one. All this technique does is fit a straight line through a
finite number of data points by minimizing the sum of the squared vertical
distance between the line and each of the points. In our context, this
means that if time is represented by days on the horizontal axis and the
those days is plotted as dots on the vertical axis (a normal closing price
chart), then we try to fit a straight line through those closing-price
dots such that the total sum of the squared vertical distance between each
closing price and the line are minimized. This would then be our best-fit
channel Raff Regression Channels show the range prices can be expected to
deviate from a Linear Regression trend line. Developed by Gilbert Raff,
the regression channel is a line study the plots directly on the price
chart. The Regression Channel provides a precise quantitative way to
define a price trend and its boundaries. The Regression Channel is
constructed by plotting two parallel, equidistant lines above and below a
Linear Regression trend line.
between the channel lines to the regression line is the greatest distance
that any one high or low price is from the regression line.
Channels contain price movement, with the bottom channel line providing
support and the top channel line providing resistance. Prices may extend
outside of the channel for a short period of time. However, if prices
remain outside the channel for a long period of time, a reversal in trend
may be imminent.