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Time
Series Forecast
Description
The
Time Series Forecast indicator is based on the
trend of a security's price over a specified time
period. The
trend is determined by calculating a linear
regression trendline using the "least squares
fit" method. The
least squares fit technique fits a trendline to
the data in the chart by minimizing the distance
between the data points and the 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. This
differs slightly from the
Linear Regression indicator in that the Linear
Regression indicator does not add the slope to the
ending value of the regression line.
This makes the TSF a bit more responsive to
short term price changes.
If you plot the TSF and the Linear
Regression indicator side-by-side, you’ll notice
that the TSF hugs the prices more closely than the
Linear Regression indicator.
Rather
than plotting a straight Linear Regression
trendline, the Time Series Forecast indicator
plots the ending values of multiple Linear
Regression trendlines.
The resulting Time Series Forecast
indicator is sometimes referred to as a
"moving linear regression" study or a
"regression oscillator."
Interpretation
The
interpretation of a Time Series Forecast is
similar to a moving average.
However, the Time Series Forecast indicator
has two advantages over moving averages.
Unlike
a moving average, a Time Series Forecast does not
exhibit as much "delay."
Since the indicator is "fitting"
a line to the data points rather than averaging
them, the Time Series line is more responsive to
price changes.
As
the name suggests, the indicator can be used to
forecast the next period's price.
This estimate is based on the trend of the
security's prices over the period specified (e.g.,
20 periods). If
the trend continues, the last point of the
trendline (the value of the Time Series Forecast)
is forecasting the next period's price. |
