The Time Series Forecast (TSF)

“TSF” is a sequence of discrete -time data. This indicator is mainly effective to predict future values based on previously observed values.


How does it work?

TSF indicator is also termed as moving linear regression which is identical to a moving average. TSF is a linear regression calculation that plots each bar’s current regression value using the least square fit method.

Example: The TSF value that covers 15 days will have the same value as a 15-day Time Series Forecast. The slight difference from the Linear Regression indicator is that, the Linear Regression indicator does not add the slope to the ending value of the regression line.


The best fit line associated with the n points (x1, y1), (x2, y2), . . . , (xn, yn) has the form

y = mx + b


Slope =

Intercept =


The TSF fits itself to the underlying price data rather than averaging the prices unlike the moving averages.

The TSF is more responsive to sudden changes in price.

Bullish Trend: Whenever price rises above the indicator .

Bearish Trend: Whenever price falls below the indicator.


Buy Signal: When the price is below the line.

Sell Signal: When the price is far above the line.

How far the price needs to differ line is abstract.