Linear regression is a common statistical technique used to identify the strength
and direction of a dominant market trend. Linear Regression Slope is one of the
indicators calculated by using the Linear Regression technique. This technique is
applied in technical analysis to determine if the market trending up or down and
what is the intensity of the rise or fall, given the past trend of prices.
The Linear Regression Slope is a centred oscillator type of indicator that is similar
to momentum indicators. As indicated by the name of the type of indicator, it “oscillates”
or fluctuates above and below a central line drawn at 0. In general, the momentum
is positive when the Slope is above 0 and negative when it is below 0. It can be
used to measure the strength or weakness and direction of the momentum.
Calculation of Linear Regression Slope
The Linear regression statistical technique is used for calculating the value of
one dependent variable when one has the values of independent variable or variables
M. This is in the form of a straight line which “best fits” the data
points of prices available, using the least squares technique. The Linear Regression
Slope is derived by calculating the slope value of linear regression lines for a
defined number of days (X) at each bar using the values for that bar and the previous
X-1 days. This is an intense calculation process as it involves calculation of regression
lines and their slope value at each bar. It is used to analyse when the market is
deviating from the trend. The Slope is typically drawn as a line chart or a histogram
below the price chart and is not overlaid on the chart itself. The Linear Regression
Slope thus drawn illustrates the trend of the prices and direction and strength
of the trend.
The prices used for calculating the regression can optionally be smoothed using
a moving average calculation. If the prices are not smoothed, then the actual price
can be used. In addition, a forecast for a certain period can also be calculated
and used. The slope of each such regression line calculated is used as the value
for that bar.
The slope is usually normalized to show percentage change at each bar by multiplying
the value by 100 and dividing it by the price. Without normalization, the Slope
would show absolute price change calculated using Regression. Normalizing allows
for comparison of the Regression Slope of different securities trading in different
price ranges. For example one stock may be trading at 100 and the other at 200.
The Slope value of 1 with normalization is 1 in the first case and .5 in the second
This is calculated as follows:
Slope = Change in Price / Bar
Normalized Slope = % Change in Price / Bar
Usually the slope indicator can be used in conjunction with other indicators such
as Linear Regression Forecast or Simple Linear Regression along with the Regression
channels, which are overlaid on the price chart by drawing the Upper and Lower bands.
Regression Slope is also used with momentum oscillators such as Williams %R.