Time Series Analysis – ACCA Management Accounting (MA)
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Thank you John for the lecture, when you said in the lecture that if we “forecast the trend then adjust by relevant seasonal variation” what would we be trying to achieve? Would we be trying to also forecast what the actual sales would be?
Also when referring to the multiplicative model as an alternative to the addictive model, you made mention of a hypothetical sales increasing and it being ten times higher at the end as compared to the beginning, by that do you mean ten times sales increase when we compare the difference between the sales figure at the beginning of the tenth year as against the sales figure at the end of the tenth year? Or ten times sales increase when we compare the difference between the sales figure at the beginning of the first year as against the sales figure at the end of the tenth year.
Sorry for the long question I have been on this topic for some days now and I can’t help but ask for clarity
Yes, we would be trying to forecast what the actual sales would be in the particular period.
If the sales are increasing then it would be reasonable to expect that the seasonal variation would increase as well. The additive model has the same seasonal variation whatever the underlying level of sales is. The multiplicative model means that with higher underlying sales we will adjust for a higher seasonal variation.
Thank you John, well understood
Great 馃檪
you are so good at explaining from the bottom to the top it immensely helps in clearing my doubts and so thank you very much
Thank you 馃檪
Great. Explained very well.
Thank you for your comment 馃檪
The formula to find out the Average trend is:
(Last trend – first trend) / (no. of set of data – 1)
I want to understand why we minus by 1.
Don’t rely on learning formulae for this exam.
Suppose there are four observations: 1, 2, 3 and 4
There are three differences 1 to 2; 2 to 3, and 3 to 4.
Thanks sir for the logic. This is what I was looking for.
what is the reason the average needs to be brought down to zero? I don’t understand this area.
Some quarters are above the average and some are below the average. Since the average is in the ‘middle’ the total of the differences above the average must be the same as the total of the differences below the average – so they should add up to zero.
when you say “some quarters are above the average and some are below the average” which average are you referring to?
Under Multiplicative model, I think there is an error under 2000 q3. shouldn’t it be 95.35% instead of 91.35%
Yes it should – it is a silly mistake of mine. However the printed answer in the lecture notes has it correct 馃檪
Hi John,
If using the results of example 1 to forecast using regression analysis, which sets of figures would be considered X and which would be Y?
Many thanks,
Y would be the sales, and X would be the quarters (numbered consecutively).
Thank you, John, for the lecture. Why it is 400, where this number comes from?
I assume you mean the total of the seasonal variations. Each of them are a little above or a little below 100%. The average of all of them should be 100% and therefore the total of 4 of them should be 400%
Thank you so much. I understand know.
You are welcome 馃檪
I don’t understand why the sum of the averages have to add up to 0
It is not the averages that add up to zero. It is the differences from the averages that should add up to zero – some are below the average and some are above the average, but the average is in the middle.
Thank you so much. This lecture really simplified this for me.
Hi
I don’t understand why the centred average of 86 is said to be near quarter 3 than 2?
Please could you explain to me
The 4-quarter average of the first four quarters is in the middle – so is in between quarters 2 and 3.
Similarly the 4 quarters average of the next four quarters is in the middle – so is between quarter 3 and 4.
When we centre them we take the average of the middle of quarters 2 and 3 and the middle of quarters 3 and 4, and this then corresponds to quarter 3.
Hi,
In the multiplicative model, the total averages arrives to 400.26%,so do we need to reduce the .26% to arrive at 400%??
Yes 馃檪
OK, thank you 馃檪
You are welcome 馃檪
Hi, I don’t understand why total +0.69 must be substracted until it become zero? Where do -0.17 and -0.18 come from?
The differences are all differences about an average – some are above the average and some are below the average but because they are all difference about an average the net figure should be zero. As I explain in the lecture, the reason they don’t exactly add up to zero is because the first two and the last two observations have nothing to compare with.
At the moment they add up to a total of +0.69, so to make the total add up to zero we need to subtract 0.69. We subtract an equal amount from each of the 4 quarters. However because 0.69/4 = 0.1725 and we are only working to 2 decimal places, we subtract 0.18 from one of them and 0.17 from the others (and it does not matter at all which one you subtract 0.18 from).
How do you calculate average change in the trend?
The only reason for wanting to know the average change in the trend would be for forecasting for the future. To forecast the trend we would take the total change for the periods given in the question and divide by the number of periods to get the average change per period.
I was able to find them….
?
The calculated percent of the 3rd quater of year 2000 is 95.35 but while taken down to calculate the average percent it was entered as 91.35. Therefore the average percent of the 3rd quater should be 95.38 and there should be a difference of 2 ?
Thanks. I will check and if I have made a mistake I will correct it.
However the idea should still be clear (and I think the printed answer in the notes is still correct 馃檪 )
For additive model, it should add up to 0 because the variations are above or less than 0?
Correct 馃檪
will all of the above be required in the exam?
Not the whole exercise – just extracts from it (but you need to understand the whole exercise to be able to be able to attempt extracts).
You will find plenty of examples of how it can be asked in your Revision Kit (you must buy a Revision Kit from one of the ACCA approved publishers, because they have lots of exam-standard questions for you to practice).
Hi I think there is an error in the video, when calculating the Multiplicative Model quarterly average the Q3 amount was written as 91.35% and not 95.35%, just want to know if i miss understood.
Yes – you are correct. Sorry 馃檨
The answer at the back of the free lecture notes is correct 馃檪
Have the videos been updated?? I see a few differences compared to the videos that I saw last week……
You can’t have, because nothing has changed since last week 馃檪
The reason I am asking is because the comments have disappeared from all the video lectures and there is a slight tuning prior to the point in the video where they say “This is a lecture from open tuition…….” and also the headings to all chapters are printed in red (or blue I am guessing) and not written with the black marker like it was previously…..?
I don’t understand. The lectures have not changed, and all the comments are still here 馃檪
Why is it that the actual value (when calculating seasonal variation) is taken from the third quarter; why is it that the first two quarters of the year 2000 are not considered?
Because (as I do explain in the lecture) there is nothing to compare the first two (and the last two) quarters with.
Ohh I get it now…makes sense thank you!
Great 馃檪