Automotive 5 – PSA (Peugeot-Citroën)

Already the fourth company will be added to the graph! This time I wasn’t afraid to take a European company, although it meant I had to recalculate EUR to USD. Of course I had to extact the numbers from six Annual Reports first, but actually it was a pleasure to do so as these documents are well structured. Although the total set was way over a thouasand pages in total, a very good financial abstract was presented at the first pages after the introduction every time. The consolidated totals were taken, like the profit shown in the picture below.

Annual Report PSA

 

After this picture– probably boring for some people – it’s time for a legendary car from the PSA history.  (Photo by skylark on Pixabay) 2CV

 

Recalculating EUR to USD is always tricky. For the balance end of year rates will apply and for the revenue and profit the best option is the mid-year rate. I was a little bit lazy as I knew it was already done for another post some of the years. Then the missing years were derived from the same website with historical exchange-rates. Remember, I’m only showing the potential of our 3D-graph generator here, so don’t use my calculations for serious business purposes as you may have do it in a different way. Yet, the 3D-graph presented below will offer valuable insights.

(Photo by WikimediaImages on Pixabay) Peugeot Blue

One detail I have to share. On generating the new 3D-graph, with PSA in it, I forgot to adjust the number of companies – again! After correction, I noticed the order was not a nice one, as the large “buildings” made the others invisible from several angles. PSA is somewhere in between GM and Ford (more or less equal size) and Mitsubishi, so I changed the order to: Mitsubishi, PSA, Ford, GM. This way it’s easier to get a good overview. No need to show you all the steps this time. It will do to explain the procedure was similar to the one in previous blogs. For more details about the spreadsheet and its calculations, just mail me. Below a screenshot of the graph is shown.

(clickable – see below for instructions about how to manipulate the real 3D-graph that will appear) Automotive4 3D graph

All this was done in seconds by the way. Getting a nice picture of a relevant car takes more time than generating a new AnRep3D-graph! In this post I will present a couple of screenshots. Although you will be able to see the 3D-graph yourself, some explanation could be helpful.

Citroën Van (Photo by educnormandie on Pixabay)

The graph holds a legend (or key) also in 3D, showing the variables presented in different directions.Legend of 3D graph

 

The height of a building is the revenue and the green roof represents the profit. The thickness of the roof varies with the amount of profit and its relation to the total height gives an impression of the margin, e.g. 1%, 5% or 10% of the height of the building being roof. Of course profit could be negative (a loss) and in those cases the roof will be red. As the costs are higher than the revenue in these cases, the yellow part will show the revenue and the total height will represent the costs made to obtain this revenue. By the way: I was in a hurry when I entered Equity as just “Eq.”. This will be changed in an upcoming post.

Peugeot 402 1936

(Photo by MarkThomas on Pixabay)

If we wouldn’t take the net profit but e.g. the EBITDA, a larger part of the building would be coloured. The legend or key will show what is in the graph. Don’t forget tot put the right labels in and to take the same variables for all companies!

The width of a building represents its Equity in this case and the depth shows the total Assets. This means the ratio of the floor shows indicates the gearing (using the total Liabilities instead of the total Assets would even be better to judge the gearing of course). The height (thickness) of the roof versus the width represents the Return on Equity. Total height compared to the depth shows the ratio of the revenue to the total Assets and so on. Of course any variable can be used for a direction, as long as it makes sense. In previous posts we presented the energy-mix for different countries in time, showing e.g. fossil fuels, nuclear energy and renewables in the three dimensions.

Citroën Cactus (Photo by dimitrisvetsikas1969 on Pixabay)

Knowing what the graph shows, it’s time for some additional screenshots. If you double-click the picture, the real 3D-graph will appear in your web-browser (if Javascript and WebGL are enabled and assuming you are online).

Automotive4 3D graphOn double-clicking, the 3D-graph will appear in your web-browser. There are several options to move graph: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse at the same time will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.

 

 

 

 

In the screenshot to the top, we see the 3D-graph from above. The years with profit and loss for the different companies are clearly visible! The screenshot to the bottom was turned around 180 degrees. Here we see GM started out with a loss in 2012, while Ford was making good profit. This is quite different from the situation in 2017, when both were doing well.

Peugeot (Photo by AutoPhotography on Pixabay)

For more information, please have a look at our other posts, our website (https://anrep3d.com ) or our youtube-channel . Again, the free demo-package (zip) can be downloaded, unpacked in a folder and the .jar file can be started immediately.

Advertisements
Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Automotive 4 – GM (General Motors)

Time for the third automotive company to enter the graph! By now you will know the procedure, so this post will be rather short. After Ford it makes sense to take the annual reports from General Motors.  It’s also a lazy choice, as GM publishes in USD and the reporting year is equal to the calendar-year.

(Photo by MichaelGaida on PixabayCadillac)

Cadillac

General Motors holds a variety of brands and to be honest, I knew only half of them. Of course the famous ones like Buick, Chevrolet (including the rebranded Daewoo), Cadillac and GMC are obvious, but I never saw a Holden, BaoJun, WuLing and JieFang. Perhaps this is because the latter three are Chinese joint ventures – with JieFang focusing on trucks – and Holden being Australian.

Chevrolet CamaroChevrolet Camaro

(Photo by Juhasz Imre on Pexels)

The annual reports of GM were really nice and structures. It took little time to collect all the numbers and no surprises came up. In the previous posts we took Revenue, (net) Profit, Equity and (total) Assets to be put in the input-file, so it had to be the same set for GM. This time I thought it would be nice to offer you the Excel, including the tab from which I derived the .csv-file, becoming a part of the input-file.

BuickBuick (Photo by Smarko on Pixabay)

Be aware that this is not an input-file yet, because a parameter-line has to be present. That’s why I also add the complete input-file both as a picture and a download this time.

Input-fileIf you want to use it with the free demo, that’s fine but it will only read one line and create a graph with one single “building”. By rotating the lines in the input-file, this could be a different “building” every time, so in the end it is possible to see them all. Of course this will bring you 3×6 (companies times years) = 18 different graphs instead of the single one created by the licenced generator.

 

GMC carGMC

(Photo by SHRAVANKUMAR on Pixabay)

 

 

Although I put pictures of cars in my posts, the AnRep3D-generator is not as poetic. It is about financial information being visualised. Yet I want to present another picture of the famous Cadillac, before the 3D-graph is shown.

Another CadillacAnother Cadillac (Photo by MichaelGaida on Pixabay)

Now it’s time for the 3D-graph! I had to adjust the scaling-factor in the input-file as it was still aligned with Mitsubishi, which turned out to be rather small in comparison with Ford and GM. Now it fits the screen. Below a screenshot is shown.

3D-graph 3 automotive companiesClicking the screenshot will open the 3D-graph in another tab in your browser (WebGL and JavaScript have to be active). The real 3D-graph is an html5-file and the image can be translated and rotated in any direction.

 

 

 

There are several options to move graph: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse at the same time will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.

HoldenHolden (Photo by SunriseGraphics on Pixabay)

 

 

 

 

For more information, please have a look at our other posts, our website (https://anrep3d.com) or our youtube-channel. Again, the free demo-package (zip) can be downloaded, unpacked in a folder and the .jar file can be started immediately.

Cadillac Lounge Cadillac Lounge (Photo by Free-Photos on Pixabay)

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Automotive 3 – Ford

The 3D-graph was created last time, so now we only have to add companies to it. That’s easy, as the input-file consists of blocks. A block holds a set of lines (one for every year) for a company. Let’s add Ford, because it is in USD already and its book-year is equal to the calendar-year. An easy post this time, without complications – or so I thought.

The first step is to get Ford’s annual reports of course. Because we already took the classic set Revenue, net Profit, Equity and total Assets (RPEA) for Mitsubishi, we have to do the same for Ford as we shouldn’t compare apples and oranges.

Ford Mercury(Photo by Luis Quintero on Pexels)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

By now you know I look for the word “consolidated” to move to the financial statements as quick as possible. Doing so I noticed Ford is not only a motor company, but is also offering financial services. Not very strange and only a small part of the numbers, so I just took the totals. On copying the values from the balance-sheet, I took the liabilities as well. We don’t need them for this graph and those numbers won’t be in the input-file but it allows me to check whether the sum of equity and liabilities meets the total assets. If not, there will be a typo or I picked the wrong column. (I use copy-paste and sometimes the actual year reported is in the left column another time it’s in the right one, so a mistake is made easily.  Another time I just miss a part of the number when selecting).

Unfortunately, the sum of Liabilities and Equity did not match the Assets, although the numbers were right! Then I discovered this floating number representing a “redeemable non-controlling interest”. Well, that’s fine but I don’t like it this way. Reading the note, I understood it was a temporary situation to be solved the next year. The amount was part of the total assets, but kept out of the equity.

Old futuristic Ford (Photo by ID12019 on Pixabay)

 

 

 

 

 

 

Then the next year the same thing happened and the year after as well. All six annual reports showed this gap of some dozens of millions, floating between liabilities and assets. Of course it’s not a “side letter” and a note was available, so it’s transparent and let’s move on. Two solutions were available to close the gaps again: 1) add the floating value to the equity or 2) remove it from the assets – actually setting the assets equal to the sum of equity and liabilities. I preferred the latter as the impact is smaller. Please keep this in mind when looking at the graph!

Classic Ford (Photo by scottwebb on Pexels)

 

 

 

 

Creating the additional block for the input-file wasn’t very hard. I saved the previous one (Mitsubishi) under a new, neutral name and added the block from ford.csv (the excel-sheet saved as an MS-DOS csv). Then I generated the file and … was surprised to see Mitsubishi and nothing else. After a couple of seconds I realised that the “number of companies” in the parameter-line was still 1 (one). After changing it to 2 (as the file holds two companies now), the 3D-graph was generated again.

Ford Thunderbird (Photo by Gustavo Belemmi on Pixabay)

 

 

 

 

Below the steps of the process are shown. The first screen is a kind of concise manual:

AnRep3D generator 1

Then the input- and output-files have to be selected – first the input-file:

AnRep3D generator 2

After clicking the button “inputfile” all files in the folder are shown. Among all the files visible are a couple of annual reports, the excel-sheets for Mitsubishi and Ford, the generator itself (a .jar – just like the free demo-package to be downloaded from our website) and the input-file, renamed to automotive.txt  The output-file automotive.htm – the actual 3D-graph – is already present because of the first attempt.

AnRep3D generator 3

The same screen appears when looking for the output-file. If there is none yet, the name of a new file can be entered. The extension will be .htm anyway. This time the output-file was already present and the generator asked me if I wanted to overwrite. I clicked “Yes”. The result is the screen below:

 

AnRep3D generator 4

 

After clicking “Start” the confirmation-screen appears. The 3D-graph is available in the folder now and can be started in the web-browser (webGL and Javascript should be allowed in the settings).

AnRep3D generator 5

 

 

 

Again we present a screenshot only, but a clickable one. On clicking the picture below original 3D-graph will be shown in your web-browser. Suddenly Mitsubishi Motors looks small, because Ford is so much larger. The values are 5 – 15 times higher (e.g. revenue for Ford is about 150 billion USD, but for Mitsubishi Motors it is about 20 billion USD). When the other companies get in, we will resize the 3D-graph again.Mitsubishi-Ford

(There are several options to move graph: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse at the same time will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.)

For more information, please have a look at our other posts, our website (https://anrep3d.com) or our youtube-channel. Again, our free demo-package (zip) can be downloaded, unpacked in a folder and the .jar file can be started immediately. The screens look the same as the pictures above (with some warnings it’s a demo). Only one company and one year will be visualised as only one data-line will be read, otherwise it’s equal to the paid version. For any questions, contact us at info@anrep3d.com

Ford Oldtimer(Photo by hansbenn on Pixabay)

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Automotive – 2: Mitsubishi

In the previous post we explained the steps to be taken to get a full graph with six automotive companies over six years. Every next post a company will be added to the 3D-graph, but as we did’t create a 3D-graph yet, this will be done now. For no specific reason I picked Mitsubishi Motors (remember: not the whole Mitsubishi Chaebol) as the first in line. The annual reports are avialable at this link:  Mitsubishi  https://www.mitsubishi-motors.com/en/investors/library/anual.html?intcid2=investors-library-anual

The bookyear is “broken” and ends at March 31. This means the greater part of the bookyear is in the previous calendar-year and therefore we will consider the annual reports to be about the calendar-year before. So 2018 will be treated as 2017 and so on until 2013 representing 2012 – to align the numbers as much as possible with the book-years of other companies.

The fastest way to get to the balance and overview of profit and loss is to search for the word “consolidated”. In most annual reports it points to the financial sector in a few clicks. Below an example is shown for (parts of) the Profit & Loss statement and the Balance sheet. The Revenue-number is called “Net Sales”.

Profit_Loss_Mitsubishi

Another example shows a collage from the Balance-sheet for the same book-year.

Balance_Sheet Mitsubishi

Here the difference between Assets and Liabilities (Equity) is referred to as “Total Net Assets”. Of course the values for Net profit and Total Assets were also extracted from those tables, but are not visible in the examples above. Although the amounts are in JPY (Yen), it turns out that only the reports named 2018 and 2017 were purely in yen, but the older ones have dollar-columns for the reported year. This saves a lot of time. To obtain the right JPY-to-USD rates, I went to:

https://www.poundsterlinglive.com/best-exchange-rates/us-dollar-to-japanese-yen-exchange-rate-on-2017-09-30

The link is an example of September 30, 2017. This is the middle of the bookyear ending at March 31 2018 and is the best estimate for Revenue and Profit. The “Average: 1 USD = 112.5505 JPY” at this date was used, but for the balance I took the end of the bookyear. Then the average was 106,0115. The same principle was applied to the values for the bookyear ending at ending at March 31 2017.

Mitsubish Barbie

Picture from Petr Elvis at Pixabay https://pixabay.com/en/users/ElvisCZ-1106877/

 

 

 

All relevant values (and then some) were entered in an Excel spreadsheet and checks were performed to be sure the right values were in. (E.g. Equity + Total Liabilities should be equal to Total Assets. Sometimes there was a rounding error of 1 and as it was about millions of yen the rounding error was 1 million yen or about ten-thousand USD, but that’s ok I guess). The conversions to USD were also done in the Excel and provided millions of USD – a much smaller amount of course – but the dollar-values in the older reports were in thousands of USD. Finally, after a little reshuffling and re-modeling, I got this input-file (the first line is the parameter-line)  when I saved the Excel-sheet as an MS-DOS .csv:

Mitsubishi Inputfile AnRep3D

The additional semicolons don’t harm and neither do empty lines after the last entry.

 

 

The generator was able to convert the input-data into an html5-page (.htm-format) and I was curious how it would look. However, al I saw was a blank page. At first I didn’t understand, but then I noticed my Internet-connection was broken. When the graph is loaded into the web-browser, a service from the Fraunhofer IGD is called. This service, called X3DOM (pronounced as X-freedom) converts the X3D the generator created into – very complex – JavaScript. After the conversion it is possible to download the result by right-clicking and then no internet-connection is needed to view the graph, but the first time the connection to this service has to be in place. Connecting to the Internet again, I saw a really huge yellow block and I realised I forgot to set the scaling-factor. The numbers were up to several hundreds of thousands, so I changed the scaling-factor from 1 to 500 (the new value is in the picture above – it’s the third value of the parameter-line). Then a normal 3D-graph came up and this is the one I will share with you below. Next time a second company will be added, and then a third and so on. The picture below is clickable and clicking will show the 3D-graph in the browser. By the way: the green roofs represent profit and the red one is about a loss.

AnRep3D graph Mitsubishi

(There are several options to move graph: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse at the same time will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.)

This time I don’t comment on the graph (yet). Have a look and draw your own conclusions.

Don’t forget to visit our website: https://anrep3d.com/ It’s also possible to contact us directly mailto:info@anrep3d,com  The movies at our YouTube channel provide more in depth explanations about the 3D-graph generator.

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Automotive – the process of creating a 3D-graph

Yes, we’re still alive. After the FAANG post we prepared a couple of mailings and decided to keep the FAANG post on top for a while. Now it’s time to move on and come up with something different. The style will also be a little different, as we will take you with us in the process of creating a graph. As a result we won’t have interesting graphs yet, so we refer to pictures of cars from the different motor-companies we will discuss. I want to thank Pixabay, Pexels and Unsplash and for making the pictures available and the photographers for their royalty-free pictures.

Ford Mustang YellowFord Mustang

(by Nic96 on pixabay)

 

 

 

 

Why automotive? Well, a lot of motor-companies have had their issues, scandals, successes. Just a couple of headlines:

Teslacomplaint against Musk

GMlegacy of problems

PSAvauxhall PSA group takeover

Fordford is basically giving up on us car business

Mitsubishi Motors aims to move on from scandal

(Mitsubishi is a chaebol, so we refer only to the automotive part)

Volkswagenbbc news business

Then all of them (and not only the ones I selected) have to face the climate goals.

The comment “process of creating a 3D-graph” is a little bit misleading as this is actually only the last step of the process and will take only a couple of seconds. As for every graph, collecting the data is more of a challenge unless one has them already and needs a good visualisation. The group of users we are aiming at will already have them of course, but we are not part of them although we would like them to be our partners. This means I have to think about interesting examples and collect and prepare the data manually.

Cadillac convertible coupé (by Emslichter on Pixabay) Cadillac Convertible Coupé

 

 

 

 

 

The name of our product – AnRep3D – stands for Annual Reports presented in 3D. Indeed Annual Reports are a good source of data and the graphs are able to visualise all kinds of information. (By the way, it’s not about financial data only. Earlier we prepared graphs showing the energy-mixes of countries in time – please have a look at our other blogposts for this subject.) However, the Form 10-K format also holds the relevant information and sometimes websites will show an overview of revenue, EBITDA, gross and net profit of a company in time. As stated above, professionals working with financial data all day will have more efficient ways to collect the relevant set of data, but we still are bound to a manual process for our blogposts.

Volkswagen BeetleVolkswagen Beetle (Photo by Murat Soyluoglu from Pexels)

 

 

 

 

In this post I will only tell the approach of the next series of posts, leading to a 3D-graph showing some financial properties of a couple of automotive companies in time. The next post will provide some numbers and so on. Then the input-file will be prepared and finally the 3D-graph will be generated and provided,  so please be patient! If you’re not, please download our demo-package  use the links provided in this post and experiment with the 3D-graphs yourself. The demo-package is fully functional and comes with a complete manual, but it only reads one line of data and will show just one company in one single year instead of the Manhattan-like map with buildings representing companies (different companies from the left to the right and their positions throughout the years from the front to the rear end of the graph).

Tesla   (Photo by Alex Iby on Unsplash) Tesla

 

 

 

 

 

 

 

 

 

 

The sources I will use to extract the necessary data from are:

Ford (calendaryear – in USD)

GM (calendaryear – in USD)

Mitsubishi  (broken bookyear. Statements as of end of March – in JPY).

PSA  (calendaryear – in EUR)

Tesla (calendaryear – in USD)

Volkswagen  (calendaryear – in EUR)

Mitsubishi PajeroMitsubishi Pajero (Photo by mickatuning69 on Pixabay)

 

 

 

 

The comments show some other challenges as well: not all of the bookyears are equal to a calendaryear so the best match has to be found for comparison. Usually the Annual Report will be considered to match the calendaryear it covers for the greate part. This means a 2018 Annual Report for the bookyear ending in March 2018, will be used as an Annual Report for 2017.

Then different valuta apply. Converting values to have just one of them is inevitable (for the graph it doesn’t matter which one and therefore I will use the most abundent one to limit calculations). The set of six holds three reports in USD, two in EUR and one in JPY so all values will be converted to USD.

For the balance it is easy: the exchange-rate at the end of the year applies. For the revenue and profit it’s more complex as the exchange rate was not constant during the year. The best option is to estimate the average throughout the year and use this value.

Peugeot Prototype (Photo by michelclavel on Pixabay) Peugeot Prototype

 

 

 

 

 

 

Don’t forget to visit our company website ( https://anrep3d.com/ ) It’s also possible to contact us directly at info@anrep3d.com   The movies at our YouTube channel provide more in depth explanations about the 3D-graph generator:

Opel Concept Car (Photo by Tonspion on Pixabay) Opel concept car

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

FAANG

Can we define a couple of technology-companies as a large tooth? Probably not, but still the acronym FANG was introduced to group Facebook, Amazon, Netflix and Google. When Apple was added (remarkable as this is a real hardware-centered company – the others being service providers and platforms from the start) it became FAANG. https://www.investopedia.com/terms/f/faang-stocks.asp

The question is, do these companies have something in common from a financial perspective? Let’s use AnRep3D to find out!

Now that we have a legend, it is easy to pick the most interesting values for the dimensions of the graph. Total Revenue and Net profit or loss, are still interesting so let’s take those. Then Equity, as always but this time Liabilities (rather than Total Assets often used in this blog) would be interesting. Of course it makes only sense if we don’t take a single snapshot in time. AnRep3D allows us to compare the companies over a couple of years. The most recent five available will do: 2013 – 2017.

I must admit that I’ve been a little bit lazy: if a series of years was available in the most recent Annual Report (e.g. Revenue and Net Profit for 2013 – 2017), I didn’t bother to look into the other ones, except for a quick check. The websites used to obtain the annual reports were: http://www.annualreports.com/Company/facebook 

http://investor.apple.com/financials.cfm

http://phx.corporate-ir.net/phoenix.zhtml?c=97664&p=irol-reportsannual

https://www.netflixinvestor.com/financials/annual-reports-and-proxies/default.aspx

https://abc.xyz/investor/ and https://www.sec.gov/Archives/edgar/data/1288776/000128877614000020/goog2013123110-k.htm

Let’s start with a screenshot from the resulting graph first. Again, it’s clickable, although this time clicking doesn’t lead to the real 3D graph but will show a short movie (at our Youtube-channel) of the moving 3D-graph. Of course the real graph is also available. As it actually is an html-page it will be shown in your browser.

Front view FAANG 3D graph

(As always there are several options to move graph: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.)

Some information about the process: After collecting all the necessary values, the parameter-line was set. Of course it mentionted the five companies and five years. After the 5,5 the stretch-factor was put to 5000 and the additional space to 20%. Probably 0 would have done as well. Then the font-size was put at 5 and because we wanted the legend to show labels, the three pieces of text were added after the font-size. So the full parameterline was like this:

5; 5; 5000; 20; 5; Revenue (Net Prof.); Equity; Total Liabilities

The values for each company in a single year were put in separate lines and this means we had 25 data-lines. Here they are (all values in millions of USD):

Facebook;2017;40653;15934;74347;10177;;
Facebook;2016;27638;10217;59194;5767;;
Facebook;2015;17928;3688;44218;5189;;
Facebook;2014;12466;2940;36096;3870;;
Facebook;2013;7872;1500;15470;2388;;
Apple;2017;229234;48351;134047;241272;;
Apple;2016;215639;45687;128249;193437;;
Apple;2015;233715;53394;119355;171124;;
Apple;2014;182795;39510;111547;120292;;
Apple;2013;170910;37037;123549;83451;;
Amazon;2017;177866;3033;27709;103601;;
Amazon;2016;135987;2371;19285;64117;;
Amazon;2015;107006;596;13384;52060;;
Amazon;2014;88988;-241;10741;43764;;
Amazon;2013;74452;274;9746;30413;;
Netflix;2017;11693;559;3582;15431;;
Netflix;2016;8831;187;2680;10907;;
Netflix;2015;6780;123;2223;7980;;
Netflix;2014;5505;267;1858;5185;;
Netflix;2013;4375;112;1334;4070;;
Google (Alph.);2017;110855;12662;152502;34793;;
Google (Alph.);2016;90272;19478;139036;28461;;
Google (Alph.);2015;74989;16348;120331;27130;;
Google (Alph.);2014;66001;14136;103860;25327;;
Google (Alph.);2013;55519;12733;86977;22073;;

The order is as in FAANG. Because the values were entered in an Excel-sheet and saved as an “MS-DOS csv” the separators are semi-colons. No decimal points were used in this case. The extra semi-colons at the end of each line are meaningless. How does the graph look? Well, you probably watched the video or looked at the real graph shown in your browser, but the a screenshot is shown again, because now we will discuss it:

Front view FAANG 3D graph

A couple of things are remarkable. Firstly, Apple is a real giant for several reasons. It has the highest revenue, highest profit and the second highest equity (after Alphabet / Google). Netflix is the opposite as it seems a dwarf. Why? Simply because its revenue, profit and equity are the smallest for the group and although Facebook’s revenue is not as impressive as Apple or Amazon either, its profit is much higher than Netflix’s for all the years. Let’s have a look from above in the next screenshot.

Top-front view of 3D graph FAANG

Now we can see the difference between Amazon and Alphabet/Google. The former has a really small profit (thin green roof) in comparison with the revenue, so the margin is quite low for Amazon and for those who are not colour-blind: the red roof means there was a loss in 2014! Alphabet/Google on the other hand, has rather thick green roofs, although Apple is invincible in absolute terms. If we look at the ratio of the green roof to the total height (the margin), then Facebook is even more impressive in 2017.

Another striking difference between Amazon and Alphabet/Google is the ratio of equity (width of the building) and total liabilities (depth of the building). Amazon has a rather normal gearing with the liabilities being about four times the equity being about, but for Alphabet/Google it’s the other way round! It has hardly any debt at all (well, that’s an exaggeration, but still). Facebook looks more like Alphabet/Google than like Amazon, on comparing their gearing.

Remember that 2017 is in the front and see how the revenue for Amazon and Alphabet/Google grew over the years. It’s not the perspective of the graph that makes the building of the older years look smaller. Their revenue – and equity – was really lower at the beginning as we can see from aside.

Right-side view of 3D graph FAANG

The huge buildings in the background are Apple – covering Facebook completely and Netflix is hardly visible anyway. Amazon’s equity grew, but the liabilities too. For Alphabet/Google, the liabilities remained as small as they were in 2013. Flipping the graph to the other side, we can see Facebook.

Left-side view of 3D-graph FAANG

Again, Apple is a big wall in the background, but now we can see Facebook showed in impressive growth for revenue, profit, equity and liabilities.

That’s it for now. I hope the FAANG-visualisation provides a better understanding about the differences and similarities (from a financial point of view of course) of the companies behind the acronym. The screenshots and comments are nothing more than suggestions. Please try and discover yourself by looking at the real 3D-graph as a screenshot is only a poor extract of the so much richer original.

A free demo is available. It is fully functional, but will only process one data-line and therefore only one building will be in the graph. It can be used to get acquainted with the generator before purchasing a full licence.

Of course we are happy to provide licences for the full version of the generator. It’s quite affordable as it is still a one-off payment for companies that are willing to become an early partner (EUR 450 ex VAT for 2017). Contact us at info@anrep3d.com  or have a look at our company’s website first.

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Alternative usage of the AnRep3D-generator – Part II

Last week I did not finish the story, to prevent an overload of information. However, both graphs were available (by clicking the different screenshots), so it was possible to investigate them oneself. Now it is time for some guidance for readers who prefer to read a story, rather than manipulating the graphs themselves.

Although the screenshots will be clickable again, first the links for the two graphs (country totals for the energy-mix and the values for the same countries per capita) are presented: http://graphs.anrep3d.com/Energy_1995-2015_all.htm and http://graphs.anrep3d.com/Energy_1995-2015_pc.htm

The first picture is a combination of two screenshots from the same graph. In the top-half we see the Germany “building” for 1995 (within the red circle). The width represents the part of nuclear energy (absolute value in PJ) and the height is the amount of renewables (the green part being the bio-energy component).

Combined screenshots Germany

The bottom half of the picture shows Germany again, but now for 2015 (again in a red circle). This time the building is much narrower, indicating an enormous reduction of the nuclear energy. It’s the impact of the “Energiewende”. At the same time, the building is much higher than in 1995 because of the increase of renewable energy. The green roof is really thick so the majority of those renewables are still biofuels and not wind or solar (found in the yellow part underneath).

If we turn the graph to see the side of the 2015 buildings, it becomes clear that most of the energy-consumption in Germany is still fossil-based. Only for France, showing more or less a square building, fossil and nuclear are about the same. See screenshot below.

RenewablesA better way to compare all countries in the graph – when looking at the usage of fossil energy – is to take the top-view.  In the real 3D-graph the names of the countries are in front of the lanes and easily checked, but because this is only a fixed screenshot the names were put in manually.

Fossil Nuclear Top

This top-view shows us that the fossil consumption of Germany and the UK is higher than for France and for Italy it is really small (we already know Italy doesn’t have any nuclear energy of itself at all). At the same time we know that France uses about twice the amount of nuclear energy of Germany and the UK taken together. That’s why France has very low carbon-emissions!

The – absolute – amount of nuclear energy consumed by France is more than a half the nuclear consumption of the USA, although the latter has a much larger population! The shape of the USA-building resembles the shape of the one for Germany because the ratio of fossil to nuclear is very similar (in spite of the “Energiewende”). The People’s Republic of China consumes more ore less the same amount of fossil fuels as the USA (in 2010 it was less, but in 2015 it was already about 30% more than the USA), but its population is at least three times as large. And India, with a population that is also over one billion, still consumes less than half of the USA-amount of fossils. It’s time to switch to the “per capita” graphs, showing us the average consumption of an individual in every country. This won’t change the shape of the buildings as the mix of fossil, nuclear and renewables will remain the same, but the relative sizes of the buildings will be different after all!

The first screenshot of the “per capita” version shows the legend clearly at the front of the graph. The values are the same as the previous ones for the countries, but divided by their population for the year of consumption. Suddenly the USA is not very different from Germany or the UK, but both China and India are hardly visible any more. They have a very large number of inhabitants, but the energy-consumption of the average individual is much lower than in Europe or the USA.Energy per capita with Legend

An oblique top-view illustrates even more clearly that the average inhabitant of France consumes more nuclear energy than the average American from the USA. And although France was good at renewable energy in 1995, the USA was doing better!Energy per capita 2

Moving from the side to the front, we can see in 2015 individuals in Italy and Germany are on top when it comes to renewable energy and for Italy it’s even about 50% of non-bio&waste (yellow part of the height – e.g. hydro, wind, solar). In this graph the most interesting part is not the comparison between countries, but the change in the mix over the years!

Energy per capita top front

Well, that’s all for the alternative application of the AnRep3D-generator. Try the graphs yourself by double-clicking the screenshot. The real 3D-graph will appear in your browser (if JavaScript and WebGL are enabled).

(To manipulate the graph there are several options: clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.)

Please contact us at info@anrep3d.com or have a look at our website https://anrep3d.com and download the free demo-package (no signing in required yet).

We would really like to have more partnerships with Universities (including Universities of Applied Sciences) to let students explore the possibilities of the generator and come up with new applications we didn’t think off ourselves. We are convinced that the addition of a (meaningful) third dimension in visualisation adds a lot of value, because the human eye is a powerful instrument when it comes to pattern-recognition!

Posted in Visualising Financial Information | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment