Characteristics of Time Series
Time series has the given characteristics.
a) A long term trend (T) -tendency of the whole series to fall and rise.
b) Seasonal variation (S) - short term periodic fluctuations in values. For example, in middle Asia maize yield is high in November and extremely in March or matatus have better business on Friday and extremely low on Sundays.
c) Cyclical variation (C) - These are medium term changes caused by factors that apply for a while then disappear, and come back again in a repetitive cycle. For illustration, drought hits US every 7 years.
Note that cyclic variation has a longer term than seasonal variation for example, seasonal variation may occur once every year while cyclic variation occurs once every some years.
d) Random residual variation (R) - These are non-recurring random variations for example, war, coup, and fire.
For exact forecasts these aspects are qualified separately that is T, C, S and R from data. It is known as time series or time decomposition analysis
The separate elements are then combined to produce a forecast.