Time series are comprised of four components: trend, cyclical, seasonal, and irregular. The cyclical component consists of long-term fluctuations that repeat over intervals greater than one year, while the seasonal component refers to regular patterns within a year. The irregular component represents random variability remaining after accounting for the other three components, resulting from short-term, unpredictable factors.

1. Explain components; seasonal, irregular, trend, cyclical. Why are they so important
Solution
Time series are comprised of four separate components: trend component, cyclical component,
seasonal component, and irregular component. These four components are viewed as providing
specific values for the time series when combined.
Any recurring sequence of points above and below the trend line that last more than a year is
considered to constitute the cyclical component of the time series—that is, these observations in
the time series deviate from the trend due to cyclical fluctuations (fluctuations that repeat at
intervals of more than one year). The time series of the aggregate output in the economy (called
the real gross domestic product) provides a good example of a time series that displays cyclical
behavior
The seasonal component is similar to the cyclical component in that they both refer to some
regular fluctuations in a time series. There is one key difference, however. While cyclical
components of a time series are identified by analyzing multiyear movements in historical data,
seasonal components capture the regular pattern of variability in the time series within one-year
periods.
The component of the time series that captures the variability in the data due to seasonal
fluctuations is called the seasonal component.
The irregular component of the time series represents the residual left in an observation of the
time series once the effects due to trend, cyclical, and seasonal components are extracted. Trend,
cyclical, and seasonal components are considered to account for systematic variations in the time
series. 'h e irregular component thus accounts for the random variability in the time series. The
random variations in the time series are, in turn, caused by short-term, unanticipated and
nonrecurring factors that affect the time series. The irregular component of the time series, by
nature, cannot be predicted in advance.