Friday, August 22, 2008

COMPONENTS OF TIME SERIES

The four components of time series are:

1.Secular trend
2.Seasonal variation
3.Cyclical variation
4.Irregular variation

Secular trend:A time series data may show upward trend or downward trend for a period of years and this may be due to factors like increase in population,change in technological progress ,large scale shift in consumers demands,etc.For example,population increases over a period of time,price increases over a period of years,production of goods on the capital market of the country increases over a period of years.These are the examples of upward trend.The sales of a commodity may decrease over a period of time because of better products coming to the market.This is an example of declining trend or downward trend.The increase or decrease in the movements of a time series is called Secular trend.  

Seasonal variation: Seasonal variation are short-term fluctuation in a time series which occur periodically in a year.This continues to repeat  year after year.The major factors that are responsible for the repetitive pattern of seasonal variations are weather conditions and customs of people.More woollen clothes are sold in winter than in the season of summer .Regardless of the trend we can observe that in each year more ice creams are sold in summer and very little in Winter season.The sales in the departmental stores are more during festive seasons that in the normal days.

Cyclical variations:Cyclical variations are recurrent upward or downward movements in a time series but the period of cycle is greater than a year.Also these variations are not regular as seasonal variation.There are different types of cycles of varying in length and size.The ups and downs in business activities are the effects of cyclical variation.A business cycle showing these oscillatory movements has to pass through four phases-prosperity,recession,depression and recovery.In a business,these four phases are completed by passing one to another  in this order.

Irregular variation: Irregular variations are fluctuations in time series that are short in duration,erratic in nature and follow no regularity in the occurrence pattern.These variations are also referred to as residual variations since by definition they represent what is left out in a time series after trend ,cyclical and seasonal variations.Irregular fluctuations results due to the occurrence of unforeseen events like floods,earthquakes,wars,famines,etc. 

26 comments:

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amitha udayakantha said...

What is the difference between moving Average and exponential smoothing method?

amitha udayakantha said...

What is the difference between moving Average and exponential smoothing method?

amitha udayakantha said...

Imagine that you are going to forecast a stationery time series using single exponential smoothing method.And the recent observations of the series are more reliable than fast observations.Then how to choose a suitable value for alpha?

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