Page 245 - DCOM203_DMGT204_QUANTITATIVE_TECHNIQUES_I

Quantitative Techniques – I

Notes Merits and Demerits
This method assumes that all the four components of a time series are present and, therefore,
widely used for measuring seasonal variations. However, the seasonal variations are not
completely eliminated if the cycles of these variations are not of regular nature. Further, some
information is always lost at the ends of the time series.

Link Relatives Method

This method is based on the assumption that the trend is linear and cyclical variations are of
uniform pattern. As discussed in earlier unit, the link relatives are percentages of the current
period (quarter or month) as compared with previous period. With the computation of link
relatives and their average, the effect of cyclical and random component is minimised. Further,
the trend gets eliminated in the process of adjustment of chained relatives. The following steps
are involved in the computation of seasonal indices by this method:
1. Compute the link relative (L.R.) of each period by dividing the figure of that period
with the figure of previous period. For example, link relative of 3rd quarter
figure of 3rd quarter
100
figure of 2nd quarter
2. Obtain the average of link relatives of a given quarter (or month) of various years. A.M. or
M can be used for this purpose. Theoretically, the later is preferable because the former
d
gives undue importance to extreme items.
3. These averages are converted into chained relatives by assuming the chained relative of
the first quarter (or month) equal to 100. The chained relative (C.R.) for the current period
C.R. of the previous period L.R. of the current period
(quarter or month)
100
4. Compute the C.R. of first quarter (or month) on the basis of the last quarter (or month).
C.R. of last quarter (or month) average L.R. of 1st quarter (or month)
This is given by
100
This value, in general, be different from 100 due to long term trend in the data. The
chained relatives, obtained above, are to be adjusted for the effect of this trend. The
1
C
R
adjustment factor is d New . . for 1st quarter 100 for quarterly data and
4
1
d New . . for 1st month 100 for monthly data.
C
R
12
On the assumption that the trend is linear, d, 2d, 3d, etc., is respectively subtracted from
the 2nd, 3rd, 4th, etc., quarter (or month).
5. Express the adjusted chained relatives as a percentage of their average to obtain seasonal
indices.
6. Make sure that the sum of these indices is 400 for quarterly data and 1200 for monthly data.

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