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Background:

I have an overall time series of close to 3 years of data. I need to forecast for different slices of data. When I slice the data, some slices results in a shorter time series. We go with the assumption that the slices of data will have the same seasonality as in the aggregated time series across all series.

For the shorter time series, I plan to use some simple methodologies like exponential smoothing and then use the overall seasonality factor and adjust the forecast.

Problem:

Is there any simple methodology to extract the monthly seasonality factors in a time series (Assuming that the data is of monthly granularity). Say, will a simple linear regression on the response variable with dummy month variables etc. Is there any better/robust methodology which gives the seasonality factors for each month of the year from the data given ?

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