Sir, am I correct in understanding that the trend line calculated using moving averages is not a linear trend and that is why a line of best fit must be estimated?
Given that they are all variations about the average then automatically they must add up to zero (some are below average and some are above average). They cannot possibly all be positive!!!
In the multiplicative model, I understood where you take the total of average figures for each quarter. But where did 400.00 come from?
In additive model, to make the total of seasonal variations “zero” we deducted the same figure,isn’t it? And then took the average so as to distribute among the 4 quarters.
Each season is a bit more or a bit less than 100% – if there was no seasonality then they would all equal 100%. So since there are 4 of them, they should add up to 4 x 100 = 400%
It was quarter 4, not quarter 3. I divided 0.69 by 4, which strictly means subtracting 0.1725 from each quarter. However to stick to 2 decimal places I subtracted 0.17 from 3 of them and 0.18 from the other.
Sir i really do not understand the averaging part, i am trying so hard to see what point am i missing but i do not, why do not we find the average of each year individually instead for example we are taking the second quarter of the first year and the first quarter of second year and finding their average and so on… Also the moving average part.
why didnt we find the next 4 moving average of the moving averages to find the Trend but rather find the average of 2 moving averages. If the trend find is to be plotted on a graph, the line is not perfectly straight, so can one continue to average the and if yes will it be average of 2 of the trend figures or what?. I realised that if the sales is averaged on every 4 sales basis throughout until two point are gotten, the line will be straight. Can it be done practically and academically?
The 4 quarter moving average was to get the average sales per quarter. The only reason for centering it is because the middle quarter did not coincide with any one actual quarter. After centering it, we can then compare the actual sales in a quarter with the ‘average’ sales in the quarter.
There would be no point in keep averaging. The only point is to average out the seasonality. In practice, the trend may be a smooth pattern (either linear or curved) and would be easier then to forecast than the actual sales which keep going up and down because of the seasonality.
You only need to centre the average if it is an even number of periods. If it is an odd number of periods then the moving average already corresponds to one of the periods.
Sir, am I correct in understanding that the trend line calculated using moving averages is not a linear trend and that is why a line of best fit must be estimated?
Correct 🙂
Sir, why must the average seasonal variations cancel each other out? (add up to 0) What if they were all positive variations?
Given that they are all variations about the average then automatically they must add up to zero (some are below average and some are above average). They cannot possibly all be positive!!!
Thank you. I find your lectures very clear and informative
You are welcome 🙂
In the multiplicative model, I understood where you take the total of average figures for each quarter. But where did 400.00 come from?
In additive model, to make the total of seasonal variations “zero” we deducted the same figure,isn’t it? And then took the average so as to distribute among the 4 quarters.
Kindly explain me about the 400 part.
Thank you.
Each season is a bit more or a bit less than 100% – if there was no seasonality then they would all equal 100%. So since there are 4 of them, they should add up to 4 x 100 = 400%
Sir will they be telling us in the exam to calculate the trend based on how many periods/ months/ seasons moving average ?
For example – will they be mentioning like this – ‘calculate the trend line based on a three month moving average’
If not, how will we know how many periods to take ?
It will be made clear in the exam 🙂
Hi,
Just wondering why is the average of 84.75 right in the middle of Q2 and Q3 ? could it not be between Q1 and Q2 also ?
Thanks
No. We averaged Q’s 1 to 4, and the ‘middle’ of those 4 is effectively the ‘middle’ of Q’s 2 & 3.
Perfect thanks
You are welcome 🙂
hello,
in quater 3 (time 24:31) why you took 0.18 and how?
It was quarter 4, not quarter 3. I divided 0.69 by 4, which strictly means subtracting 0.1725 from each quarter. However to stick to 2 decimal places I subtracted 0.17 from 3 of them and 0.18 from the other.
Multiplicative Q3 Table .. it was 95.35% , in the table u wrote 91.35 and solve it for 91.35%
im really benefiting from ur lectures but this one is a bit too long , would be better if u hinted out at the question areas
Thanks alot
Mr. John, the lecture was delivered very well.
I want to clear my doubt why you have shown the final result zero in the additive model?
What is the advantage of using Multiplicative model over the additive model and how we would come to know which methods is feasible to use?
Thank you
very thankful to you sir.. now i am able able to understand it well
Thank you for the comment 🙂
welcome 🙂
great thanks sir i really understand now
I am pleased 🙂
Sir i really do not understand the averaging part, i am trying so hard to see what point am i missing but i do not, why do not we find the average of each year individually instead for example we are taking the second quarter of the first year and the first quarter of second year and finding their average and so on…
Also the moving average part.
now I am getting there thank you Lecturer
why didnt we find the next 4 moving average of the moving averages to find the Trend but rather find the average of 2 moving averages.
If the trend find is to be plotted on a graph, the line is not perfectly straight, so can one continue to average the and if yes will it be average of 2 of the trend figures or what?. I realised that if the sales is averaged on every 4 sales basis throughout until two point are gotten, the line will be straight. Can it be done practically and academically?
The 4 quarter moving average was to get the average sales per quarter.
The only reason for centering it is because the middle quarter did not coincide with any one actual quarter. After centering it, we can then compare the actual sales in a quarter with the ‘average’ sales in the quarter.
There would be no point in keep averaging. The only point is to average out the seasonality. In practice, the trend may be a smooth pattern (either linear or curved) and would be easier then to forecast than the actual sales which keep going up and down because of the seasonality.
This Q&A also solved my problem, thanks a lot.
You are welcome 🙂
thank you sir,i realy loved your lecture.very clear and easy to understand,
Also why are the first two left out?
Because there is no average to compare them to.
(They are not left out in calculating the moving averages)
How do know that the centered average is for a certain month in case of even or odd number of total periods?
You only need to centre the average if it is an even number of periods. If it is an odd number of periods then the moving average already corresponds to one of the periods.
I am really thanksfull for Opentition.com site for real free accounting resources.
very helpful!
Great!
Impressive!