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Time Series Forecast & Analysis: How To Read The Charts
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Last Updated on May 6, 2020
The Time Series Forecast uses Linear Regression to calculate a best fit line over a designated time period; this line is then plotted forward a userdefined time period.
The chart below of the miniDow Futures contract shows the Time Series Forecast indicator:
The chart above illustrates how the Time Series Forecast line has been plotted forward (in the example above, 7 days).
Generally, traders might expect price to return back to the Time Series Forecast line when prices have strayed. Therefore, a vague potential buy signal could occur when price is below the line and a potential sell signal could occur when price is far above the line. However, how far price needs to vary from the line is very subjective.
A similar and arguably superior technical indicator, is the Linear Regression Curve (see: Linear Regression Curve).
Time Series Forecast Indicator Settings, Trading Strategy
The Time Series Forecast indicator (TSF) shows the statistical trend of a security’s price over a specified time period. This indicator is referred to as a moving linear regression that is similar to a moving average. The Time Series Forecast (TSF) indicator is based upon a regressionbased forecast model. It predicts future price action based on past events.
Top FAQs about Time Series Forecast Indicator
The Time Series Forecast indicator basically reflects the statistical trends over a specific period of time. And it can give an indication of the current trend continuation. The indicator fits itself to the underlying price data instead of average prices. Therefore, tends to be more responsive to sudden changes in price compared to a moving average.

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The usage of the Time Series Forecast Indicator is straight. When the Price moves above the TSF line this determines a bullish trend. On the other side, when the Price falls below the TSF line, this indicates a bearish trend. This is the basic strategy. Apart from this, there are many useful ones that are described later in this article.
The Time Series Forecast or TSF indicator is a linear regression calculation. It plots each bar’s current regression value by using the least square fit method.
How To Attach Time Series Forecast Indicator for Technical Analysis?
Traders can know more about the Time Series Forecast (TSF) indicator, then they can find it in the STUDIES section of Zerodha Kite. It is also available in Kite mobile App. The default Period is 14. The default Field is close. You can set the value of it to open, high, low, close or hl/2, hlc/3, hlcc/4, and ohlc/4. Traders can use this indicator on any time frame charts likes daily, weekly, monthly or intraday. You can also check the image below to understand how to attach the TSF indicator in the HDFC Bank share price chart.
Here, is the next example, Upstox Pro. Here, just open a chart and search for the indicator. After that, click on apply. After clicking on the apply, the TSF comes over the price chart.
Key Points on Time Series
 Traders can interpret the Time Series Forecast indicator in the same way as other moving averages.
 This indicator is useful for smoothing noise out of the price movements with the analysis of moving averages traders can gain a general idea of where the underlying trend is headed.
 TSF formula creates a visual display of the statistical trend of the stock price over a specified time period.
 Where the simple moving average is the trend of historical closing prices for a time period.
 The TSF is the trend of stock prices based on the linear regression of closing prices.
 The TSF does not create a straight linear regression trend line. Rather the TSF plots the last point of multiple linear regression trend lines.
Conclusion
An indicator is an interesting tool for traders who are tired of trading lag between the underlying prices of a stock and the moving average. This is differentiated moving averages by not only be more responsive to price changes but also forecasting future price changes. This is depending on the traders’ trading strategy in using the leastsquares regression technique. Compare to all trading indicators, we always suggest that the trader experiment with different time frames to find the one that suits traders’ trading and risk profile. Also, traders can use multiple indicators to provide confirmation for buy and sell signals.
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Author: Ankita Sarkar
Ankita is a graduate in English language and she has also done her MBA from the Calcutta University. She has a high knack in the stock markets. She is a NISM certified Research Analyst. An experienced stock market content writer Ankita is also trading successfully on her own account. View all posts by Ankita Sarkar
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Technical Analysis from A to Z
by Steven B. Achelis
TIME SERIES FORCAST
The Time Series Forecast indicator displays the statistical trend of a security’s price over a specified time period. The trend is based on linear regression analysis. Rather than plotting a straight linear regression trendline, the Time Series Forecast plots the last point of multiple linear regression trendlines. The resulting Time Series Forecast indicator is sometimes referred to as the “moving linear regression” indicator or the “regression oscillator.”
The interpretation of a Time Series Forecast is identical to a moving average. However, the Time Series Forecast indicator has two advantages over classic moving averages.
Unlike a moving average, a Time Series Forecast does not exhibit as much delay when adjusting to price changes. Since the indicator is “fitting” itself to the data rather than averaging them, the Time Series Forecast is more responsive to price changes.
As the name suggests, you can use the Time Series Forecast 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 days). If the current trend continues, the value of the Time Series Forecast is a forecast of the next period’s price.
The following chart shows a 50day Time Series Forecast of Microsoft’s prices.
I’ve also drawn three 50day long linear regression trendlines. You can see that the ending point of each trendline is equal to the value of the Time Series Forecast.
The Time Series Forecast 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. Click here to go to the formula for a linear regression trendline.

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