Greetings,
I will be forecasting data that ****fts direction at points due to
changes in business decisions. I would like to get an idea of the best
forecasting model to use for extrapolating future results.
Basically, numbers may have gone up for 6 months are a relatively
steady rate, and then due to a ****ft in the business, they went down
at a relatively steady rate for 9 months. I would like to use a
forecasting model that will essentially "discard" the 6 months of
increases, and consider what appears to be the current trend of 9
months of decreases.
I am currently using a weighted moving average, giving weight to more
recent numbers, but that works better for data with changes in trends
further in the past. If instead of 9 months of steady decreases, there
were only 3 months of steady decreases, the model would not be as
good, since the period of increases would have a greater effect.
Is there a method that will identify those ****fts in direction, and
ignore or minimize the effect of previous trends?
Thanks,
N. Lee
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