Seasonality

A characteristic of a time series in which the data experiences regular and predictable changes which recur every calendar year. Any predictable change or pattern in a time series that recurs or repeats over a one-year period can be said to be seasonal.

Note that seasonal effects are different from cyclical effects, as seasonal cycles are contained within one calendar year, while cyclical effects (such as boosted sales due to low unemployment rates) can span time periods shorter or longer than one calendar year.

Seasonality can be seen in many time series, and it's more common than you might think. For example, if you live in a climate with cold winters and warm summers, your home's heating costs probably rise in the winter and fall in the summer. You would reasonably expect the seasonality of your heating costs to recur every year. Similarly, a company that sells sunscreen and tanning products would see sales jump up in the summer, but drop in the winter. Companies that understand the seasonality of their business can time inventories, staffing and other decisions to coincide with the expected seasonality.

It's important to remember the effects of seasonality when analyzing stocks from a fundamental point of view. For example, if you assumed a sunscreen company was going to earn as much in the next three quarters as it did during the recent summer quarter, your earnings estimates would likely be way off the mark!