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

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About AnRep3D

AnRep3D is the new company, founded after the handover of Scientassist (together with VRBI) to one of my sons. From now I will focus on three-dimensional graphs for the financial markets, showing the main figures from annual reports in comparison.
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