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I am new to time series and therefore trying to feel my way around. I am required to do some analysis and possibly come up with a model. However, I have at most 2 years worth of quarterly data (at most 8 datapoints). Can I build any meaningful model based on the data? What possible model apart from linear regression with time as regressor can be built?

Thanks

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    $\begingroup$ Not really. Eight data points wouldn’t even be enough for simple ordinary least squares regression, or even a t-test. I’d like to ask, what is it that you are trying to accomplish? What is your research question? $\endgroup$
    – Jon
    Aug 2, 2018 at 5:20
  • $\begingroup$ A graph would be useful (no need of the units). If you follow Tuker's advice, data visualization should become an automatic reflex. $\endgroup$
    – AlainD
    Aug 2, 2018 at 11:05

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There is no valid answer. If you have a stationary process with 0 variance, then the forecast horizon has no limit.

More realistically, you have the follow rule of thumb (which is totally from experience with absolutely no theoretical base): the horizon forecast may be half the historical base. You have 8 data points, so you can forecast 4 points. You have 2 years, so you can forecast 1 year.

The key point is : check this after your forecast is done.

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  • $\begingroup$ Is there any mathematical proof for ´the horizon forecast may be half the historical base´or it is just based on experience? $\endgroup$
    – Carlos Mougan
    Jan 4, 2020 at 16:19
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    $\begingroup$ A. Debcker, T. Modis, Determination of the uncertainties in S-curve logistic fits, Technological Forecasting and Social Change Volume 46, Issue 2, June 1994, Pages 153-173 $\endgroup$
    – AlainD
    Apr 4, 2020 at 8:11
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As far as the time evolution model is concerned, you have:

  • A linear growth/decline. You increase/decrease of a constant value (in units, dollars,...)

  • A exponential growth/decline. You increase/decrease of a constant rate (in %)

  • A logistic growth/decline. You are filling a limited niche, and the increase in % is proportional to what remain to be filled.

  • Higher level of model (Bass-diffusion models,...), approximations (polynomials,...) or adaptive methods (moving average, exponential smoothing, ARIMA,...)

You can easily test exponential growth by fitting the log of your data on a linear regression, but other models require more sophisticated techniques.

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    $\begingroup$ Why do you not combine your two answers into one, e.g. using two heading, if you are making two different points? $\endgroup$
    – n1k31t4
    Aug 2, 2018 at 11:03
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I would start playing around with the prophet library for python, you can still make predictions with 8 datapoints, the accuracy is going to depend on a lot of things especially the variance in the points.

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    $\begingroup$ Suggesting someone try a statistical package does not address the issue of data quality/quantity which is OPs concern. $\endgroup$
    – Jon
    Aug 2, 2018 at 5:21

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