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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.
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