Time series analysis: please note that this lecture relates to Chapter 12 of the Course Notes (and not Chapter 11 as stated in the lecture)
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Since this time series analysis is not in the syllabus, should I forget about? I don’t really like what happened in the last December questions on the areas of concentration and the rest given.
Thank you
Time series is still examinable because it is assumed knowledge from Paper F2.
However the examiner will not ask for any calculations. It is unlikely that anything will be asked, but you are expected to know the idea.
Please be aware that Time Series is no longer in the syllabus
It has been removed from the syllabus as it will be assumed knowledge from F2 syllabus, so it is still examinable.
amazing
made it so easy 
hello i have problem with the question that came in the June 2012 exam. i have problems with this bit
The average seasonal variations can now be calculated to see whether any adjustment to the percentages is required, since
they must be 4•0 in total.
Since the averages total 4•0057, each one needs to be reduced by 0•0016
Q1 Q2 Q3 Q4
2010 0•9080 1•0820
2011 1•1228 0•8989 0•9032 1•0777
2012 1•1256 0•8932
Total 2•2484 1•7921 1•8112 2•1597
––––––– ––––––– ––––––– –––––––
Average 1•1242 0•8960 0•9056 1•0799 4•0057
––––––– ––––––– ––––––– –––––––
Rounded 1•1228 0•8946 0•9042 1•0785 4•0001
The difference of 0•0001 is due to rounding and can be ignored.
The average trend of the centred moving averages is (1,287•5 – 1,068•75)/5 = 43,750 units.
Therefore forecast centred moving average for Q3 in 2012 = 1,287,500 + 43,750 = 1,331,250.
Adjusted for seasonal variation: 1,331,250 x 0•9042 = 1,203,716•25 units.
Forecast centred moving average for Q4 of 2012 = 1,287,500 + (2 x 43,750) = 1,375,000.
Adjusted for seasonal variation = 1,375,000 x 1•0785 = 1,482,937•5 units.
can you help explain it to me please
@chiclarence, I am not sure which bit you are having problems with.
Are you happy with the way that the seasonal variations have been calculated?
In each case it is actual divided by the trend.
Since some variations are more than 1 and some are less than 1, they should add up to 4. They never will because the first two seasons and last two seasons were used in calculating the trend, but could not be used in calculating the seasonal variations.
So, because the total is not 4 then have all be adjusted by one quarter of the difference so that they do add up to 4.
The trend has been forecast assuming it is linear. (The trend is the centred moving average). So because on average it has increased by 43,750 the future forecasts have been made by adding on 43,750 each quarter.
Because those are forecasts of the trend, it is then necessary to adjust by the seasonal variation to arrive at a final forecast. Since on average the seasonal variation for quarter 3 is 0.9056, the actual forecast is 0.9056 of the trend forecast.
Have you watched my lecture on time series?
@johnmoffat, jes John i have watched the video and i am comfortable with the way the average seasonal variations have been calculcated: i know the actual has to be divided by the trend in the multiplicative model but i am not comfortabel with this
Since the averages total 4•0057, each one needs to be reduced by 0•0016
where is the 0.0016 from
secondly i dont understand this bit
Total 2•2484 1•7921 1•8112 2•1597
––––––– ––––––– ––––––– –––––––
Average 1•1242 0•8960 0•9056 1•0799 4•0057
––––––– ––––––– ––––––– –––––––
Rounded 1•1228 0•8946 0•9042 1•0785 4•0001
precise ly i dont understand how the rounded figurs came from:
also theis line
The average trend of the centred moving averages is (1,287•5 – 1,068•75)/5 = 43,750 units.
Therefore forecast centred moving average for Q3 in 2012 = 1,287,500 + 43,750 = 1,331,250.
where is the (1287.5-1.068.75)/5 from and the figure of 1287500 is for which quarter that is being adjusted
cheers
@chiclarence, Since the averages total 0.0057 more than they should do, each of them has been reduced by one quarter of this. (0.0057 /4 = .0014). The 0.0016 is a typing error – if you check you will see that in fact each of them has been reduced by 0.0014.
The first centred moving average (trend) in the question is 1068.75 and the last one is 1287.5. So over 5 quarters it has increased by 1287.5 – 1068.75 = 218.75. Since this os over 5 quarters, the average increase per quarter is 218.75 / 5 = 43.75 (or 43,750).
For forecasting it is assumed therefore that it continues to increase by 43.75 per quarter, as explained in my previous answer.
is this lecture available on youtube channel??
No it is not
Could you not just work out the moving average over 3 quarters instead of 4 and then it’s already centred albeit with slightly different figures?
It’s still a consistently upward trend although it’s not quite so smooth.
thanks
@andreasmacfarlane, No. The reason is that the seasonality is occurring over a year, and so it is necessary to take the averages over a twelve month period each time.
@johnmoffat, Thanks John. That makes sense now.
Hello,
I have a question about example2 of the Course notes(page 61, chapter12). We divide the number of units by 100 just to be easier to make the calculations, but why do we divide the costs by 1000 and not by 100(the answer is on page 118)?
Thanks.
@mdmkd, It does not matter. You do not have to divide the costs and the units by the same number. All that matters is that you divide all the units by the same number; and that you divide all the costs by the same number.
i couldnt find consolidation lecture!!!!!!!!help me to find the link plz
@anatuly007, Consolidations are not in Paper F5
Depending on which accounting paper you are taking, you should look at the F3 pages or the F7 pages.
Once again exquisite.
Can i ask a question please? why in the multiplicative model of average seasonal variations the figures don’t have a + or – sign in front of them please? for eg in the additive model when we deducted trend from sales, if trend was higher than that had a – sign.
@eley, It is because the multiplicative method is showing the actual as a percent of trend.
If the actual is less than the trend then it will be less than 100% (not negative)
If the actual is more than the trend then it will be more than 100% (not positive),
Nice one and a very amazing way of explanation
I have the same problem locating F2 Regression Analysis ! can anyone help to get the name of the lecture or please post link here??
Thanks.
@mansikhusi, If I am not late to reply for your query ,Regression Analysis Leture is found in ACCA F2 Chapter 17 Semi- Variable Costs(Business Mathematics) .Very interesting lecture by John Moffat.
Best of Luck
@Et, hello! and in which particular lecture of chapter 17 F2? there are 4 videos there.. or is that better to study all 4 lectures?
thank you in advance
best wishes for the exam!
@Evgenia, Come on Evgenia …. If I were you I would have given it a glance before I post a query. To my knowledge all 4 are important(really are) as they are also in F5 syllabus.High low,Regression analysis( which is in part C) and Time Series.
I Hope this helps
I cant locate the F2 Regression Analysis lecture that you recommended, can you advise what the name of this lecture is?
@sheila01, If I am not late to reply for your query ,Regression Analysis Leture is found in ACCA F2 Chapter 17 Semi- Variable Costs(Business Mathematics) .Very interesting lecture by John Moffat.
Best of Luck
Thanx alot
Thanx Alot
I enjoyed the lecture. Well taken
very comprehensive