Calendarization for Comps Analysis

This video discusses what calendarization is, why its important to be done while conducting comps analysis or multiples valuation and how to do it. We also use the cases of Amazon and Walmart to illustrate how this is done using actual financial statements of these companies.

Hello and welcome to this session in the previous video we discussed that one of the most important inputs into a comparable company analysis or multiple evaluation is the ltm or last 12 month data computations we saw that the ltm data is not provided in the financial statements and we learned how to compute it using only one annual and one quarterly filings

So that is the ltm computations and if you have not watched it i have provided the link in the description so you can watch that one first and then come back and watch this video the main point of using the ltm data is to use the most currently available data in constructing the multiples there is another important method and data manipulation you may need to

Do before you actually start constructing your multiples and that method is called calendarization we need to calendarize the data in order to make sure that we are comparing companies for exactly the same period as it will be cleared soon the last 12-month numbers for two companies that are reporting financials based on two different cycles are not telling us

The relevant numbers for exactly the same periods for example assume that we are valuing amazon that reports for the fiscal year and the december 31st the same as calendar year also assume that as a comparable company you are using walmart that is fiscal year ends on january 31st instead of december 31st now let’s go and see if we compute the ltm data for these

Two companies what will happen let’s start with amazon which is the company we are valuing assume that we are now on december 2019 and the third quarterly filing for 2019 is out but of course not the annual filing yet to get the ltm data as discussed in the previous video we get the data for previous fiscal year that is coming from the most recent annual filing

And then we add the year-to-date data from the most recent quarterly filing and then deduct the year-to-date data for the prior year you see that the year-to-date data here are from january 1st to september 30th if we do that we get the ltm data that is associated with the period october 1st 2018 to september 30th 2019. as a side note you may wonder why when

We compute the ltm data we do not simply add the first three quarters of 2019 and the last quarter of 2018 to get the last 12 month data the reason is that it’s not common to have q4 results separately instead companies usually file the first three quarters and then an annual filing so you cannot typically get the q4 results directly and if you need it which

In fact sometimes you would need it for a calendarization for example you have to get the annual filings and then deduct the relevant q1 q2 q3 numbers to come up with the q4 results to summarize the way we compute the ltm data here requires only two financial statements whereas other possible ways would typically require in fact collecting more data from more

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Statements now let’s look at walmart the comparable company that has fiscal year ending january 31st instead of december 31st again remember that we are valuing these companies on december 2019 when the third quarterly filing for 2019 is out but not the annual filing note that here the year and the first quarter starts from february 1st whereas in case of amazon

The first quarter was starting from january 1st so now let’s continue to compute the ltm data for walmart i get the data for the last annual filing i add the year to date number for this year and deduct the year-to-date number from the prior year it gives me the last 12-month data but as you see it’s for the period november 1st 2018 to october 30th 2019 which is

Not exactly the same as the one from amazon although in both case we are computing the numbers for the past four quarterly filings the reason is exactly because these companies have different cycles for reporting for example the third quarter 2019 for amazon is reporting for july august and september while the q3 numbers for walmart is reporting numbers for august

September october so you may wonder if that could be an issue or not well it could be definitely an issue assume that month of october is a very important month for these companies and their earnings and assume that october 2018 was a really bad month but october 2019 was an extremely good month for these businesses your ltm number from amazon includes october

2018 which was the bad year and exclude october 2019 which was an extremely good year the opposite is true for walmart october 2018 which was a bad year is excluded from the ltm computation but october 2019 which was a good month is included in the computation so even if the earnings of the two companies are exactly equal to each other month by month the ltm

Numbers we will be computing would be different because they are for different periods to fix this issue we will have to calendarize the numbers calendarization would adjust financial ending dates for the comps to be consistent with that of the company you are valuing since we are valuing amazon here i would need to adjust the ending dates for walmart’s to be

Consistent and to be the same as amazon so again if you look at the details we see that for walmart’s the regular ltm data would be from november 1st 2018 to october 30th 2019 but i want to be from october 1st 2018 to september 30th 2019. how can we compute this i can get the last annual filings add to that the current year two september numbers so from february

1st to september 30th and then deduct the same period which is february 1 to september 30th of the last year this gives me an ltm number that is for the same period as the one computed for amazon so it’s the calendarized ltm number based on amazon fiscal year now the issue is how to compute numbers for february 1st to september 30th period well from the q3 filings

Or the third quarterly filings i have the year to date numbers that reports from february 1st to october 30th if i was given the data for october separately i could have deducted the month of october from the year to date number and get the data for the period from february to september unfortunately we do not get the data month by month so we have to find the

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Second best solution in quarterly three filings we do get the data for the third quarter separately if so i can estimate the data for october to be one third of the q3 data i deduct that number from year to date data and it gives me an estimated number of the period from february 1st to september 30th i do the same for last year as well know that in this setup

I still only need one annual filing which is for the year 2018 and the q3 filings for each company for amazon it’s standard for the ltm numbers i only need the last annual data the current stop and the prior stop for walmart i need this data but in addition i would need data for q3 2019 and q3 2018 separately also now let’s go and get these numbers from the

Actual filings of the two companies and compute the calendarized ltm earnings per share for example let’s start with the easy one amazon i go to the annual filings for 2018 and find the reported financial statements diluted earnings per share is reported to be 2014 for the year 2018. i add this number uh in my excel sheet okay now i need year to date numbers

For 2019 and 2018 which should be in queue three filings of 2019 so here it is the current stop is reported to be 16 53 and the prior stop is 14 10. i copy these numbers as well in my excel sheet okay now i have all numbers i need to compute the ltm earnings per share for amazon now let’s go to walmart to compute both the ltm and calendarized ltm numbers as

Discussed we need not only the above three numbers but also q3 2018 and q3 2019 separately first i go to get the most recent annual filing which is for fiscal year ending january 31st 2019 i go to the income statements okay here it is diluted earning for sure for the last fiscal year is 226. you should be careful not to be confused by year mentioned above we

Get the number below 2019 but this is for fiscal year ending january 31st 2019 which is in fact reporting earnings of year mostly since this is reporting earnings from february 2018 to the end of january 2019. anyways the earnings per share for the most recent fiscal year is 226. i entered that in my excel file okay now i need to go to the q3 filings for 2019

There i can get both the year to date numbers for 2018 and 2019 and also q3 numbers for 2019 and 2018. okay here i have all the information i need first i needed the year to date numbers for 2019 and 2018 these are given in the last two columns and they are 374 and 1 0 1. okay i enter these numbers in my excel file as well the last two numbers i need are the

Earnings per share for q3 2019 and 2018 these are given in the first two columns respectively as you see diluted earnings per share numbers are 1 15 and point 58 for the last three months ended october 31st which is the q3 2019 for walmart i entered these numbers in excel 2 and now i am done with all the inputs i needed to compute the ltm earnings per share

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Numbers for amazon i start with the last annual filing add to it the year to date from 2019 and deduct the year to date number for 2018 and i get the ltm diluted earning per share of to 57 now let’s go to compute the ltm data for walmart the same way if i add the year-to-date numbers from 2019 to the prior annual number and deduct the year to date number for

2018 i get 499 as the ltm earnings per share again note that this is the number for the past four quarters based on walmart reporting cycle which is in fact giving us the number for the period november 1st 2018 to october 30th 2019 which is not the same as the one from amazon as you can see to calendarize this number we need adjustments to year to date numbers

For 2018 and 2019 specifically we needed to deduct from the year to date numbers one third of the q3 data both for 2018 and 2019. so let’s do that we get the calendarized year to date 2019 as the year-to-date number from 2019 minus one-third of the q3 2019. we do the same for 2018 it’s the year-to-date number from 2018 minus third of q3 2018. now i can use the

General formula that the ltm earnings per share would be equal to the last annual filings number plus the calendarized year-to-date number from 2019 minus the calendarized year to date number from 2018. this gives me calendarized diluted earning per share number for walmart that is 4.80 as you see the calendar rise earnings per share for walmart is less than its

Ltm number the reason is that as you see q3 2018 has been a bad year while q3 2019 has been a good year for walmart when we calendarize here we’re essentially pushing the numbers for walmart back on time and since q3 2018 was worse than q3 2019 by pushing backwards walmart’s earnings looks worse so you can test that if the q3 2018 number was the same as q3 2019

The ltm and calendarized ltm would have been the same as you can see with the similar logic if q3 2018 was higher than q3 2019 everything else equal we would have got a calendar as ltm number for walmart that is higher than its ltm number so all in all calendarization could make one company looks either better worse or not much different as a last note i suggest

Not to memorize any formula for calendarization try to understand the logic as i highlighted here and find a way to calendarize the numbers as we just did so to recap in case companies report their financial statements on different cycles it’s very important to categorize the numbers before constructing your multiples and comparing companies by calendarizing

The numbers we will be comparing data for exactly the same period across companies which is essential to do when you are conducting a multiple valuation i hope this session was useful for you and thanks for watching

Transcribed from video
Calendarization for Comps Analysis By Hamid Boustanifar