The Time Series Forecast
indicator shows any statistical trend in a stock's price over a
time period of length 'n' using linear regression analysis techniques.
Interestingly, the Time Series Forecast generates the last point
of several simultaneous linear regression trends. The resulting
Time Series Forecast indicator is also called the 'moving linear
regression' indicator and sometimes the "regression oscillator".
Day trading masters may find a use for this indicator in order to
give themselves a 'flavour' of what tomorrow's action mightbe, although
most prefer established techniques such as volatility analysis.
The forecast is traded
like any other moving average, but the fact that multiple Time Series
are used gives it a couple of advantages over 'ordinary' MAs, principly
the lack of a delay when prices change rapidly. This, of course,
is because the Time Series Forecast 'fits' itself to the underlying
price data instead of averaging them, making it more responsive
to price changes. Basically, if the current trend remains in place,
the Time Series Forecast is a forecast of the next period's price
To calculate the Time
Series Forecast you have to use a "least squares fit" technique
to calculate a linear regression trendline, which attempts to fit
a trendline to the price data by minimizing the distance between
the price points and the linear regression trendline itself.