Abusing the AnRep3D-generator: visualising energy-sources!

Originally the AnRep3D graph generator was meant to visualise financial data from annual reports. Recently I realised other values can be visualised the same way. I performed a lot of energy-calculations the last couple of years and it’s clear we all try and get away from fossil fuels, especially coal, because of the climate-change.

Natural gas produces about half the amount of CO2 per unit of energy (let’s say per PetaJoule). It’s still a lot of CO2 and that’s why natural gas is considered to be a “transition” fuel. In the end we will move towards energy-sources without a net CO2 emission at all.

We all know about solar-, wind- and hydro-power but for a lot of countries nuclear power is an important alternative and the operational production of energy doesn’t generate CO2. On top of it there is bio-fuel and other forms of biological materials used as energy-sources.

Because of this set, I decided to use coal for the width of the building (replacing “equity”), oil for the depth and gas + non-fossils as height (revenue in the normal situation). The non-fossil part would become the roof (serving as “profit”) and the yellow part of the height representing gas (in a profit and loss report it would be the “costs” to be subtracted from the revenue to get the profit). Using countries instead of companies, the picture gets completed!

Suddenly we will see “good” and “bad” buildings. If a building is taller, the gas and non-fossil part of the total energy-usage is high. A plump building shows a country is relying on coal and oil. A broad plump building is the worst, because it represents high coal usage. A deep building is about a focus on oil. Of course tall building with a small roof still shows a lot of natural gas consumption and less non-fossil energy. A thick roof could means a lot of renewables but also a lot of nuclear energy (like e.g. in France).

Other choices would have been valid as well. E.g. taking coal for width, but oil+gas for depth. This would have left the height to be used for nuclear (yellow part) and renewables (green roof). We will explore those options in upcoming posts about “the abuse of AnRep3D”. If people are interested, an alternative version of the generator could be made available, called something like Energy3D.

Where do I get my data from? It’s not in the annual reports and countries don’t publish them either. The International Energy Agency however, has very nice charts showing all the energy-flows. Excluding exports, all data can be collected from the chart at the right point. http://www.iea.org/Sankey/ To the top the measure can be chosen: either PetaJoule or MMboe. It doesn’t matter as both are objective units to present amounts of energy. I collected the information for a couple of countries and I will generate a graph. Below an example of the value for oil in France.

Oil_France

For now I didn’t want to leave you without a 3D-graph at all. That’s why I used the free demo-version of AnRep3D (to be found at: anrep3d.com/free-demo – one building only) and created a 3D energy-graph for the UK using it.

Remember: this time the width is energy from coal, the depth is energy from oil, the yellow part of the height is energy from natural gas and the green roof is nuclear + renewables (solar, wind, hydro, bio). All sources were presented as PetaJoules to be able to compare all sources (but MMboe would have done as well). Electric is not a part of the graph as it’s either generated from one of the other sources or the primary form of energy produced by renewables (solar, wind and hydro).

Energy_UK

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Visualising a mix of companies in a spatial graph (III)

Before we talk about the graph, let me tell you the actual spatial graph I am talking about is available at our AnRep3D website: http://graphs.anrep3d.com/smallmix.htm  Any modern browser with WebGL enabled will show this X3DOM-based graph, which actually is just a webpage. We will show some screenshots for people who are not able to look at the graph for whatever reason, but if possible, keep the original graph at hand.

The distance between the “buildings” was increased, because after the correction of the values for Easyjet and Elecnor the buildings became narrower and extra space had to be created for the labels. As a result, the graph is further away, more in the background. in the background

By clicking the right mouse-button and moving down at the same time, the graph will come closer.

Zooming in

To re-adjust the position of the graph in the screen, double-click in the graph. When clicking in the middle of the Elecnor-building, the graph will move up because now Elecnor was selected as the new centre. Click on USG-People and the graph will move to the left. Remember: when the graph is in a very strange position, click the refresh-button to reload the page and the original position will be shown again.

Back to original position

To be able to see equity and assets at the same time, we have to look at the top of the building (or the bottom). The graph can be tilted easily by clicking the left mouse-button and moving the mouse downward (or upward) at the same time. Using the middle of Elecnor to click at will keep the graph aligned horizontally.

Top view

Now it’s time to have a closer look at the companies. Zalando doesn’t have a lot of debt: the building is not much deeper than its width – not even two times. As the equity (width) is part of the total assets (depth), the extra part represents the debt.

For Tesla it’s completely different: the debt is probably five times as high as the equity, so the equity ratio is rather low but the company still doesn’t look like a bank! (see previous post about Dutch banks).

Looking at their revenues, the difference is small, but Tesla manages to lose a lot of money, while Zalando makes a small profit.

Comparing

Comparing Elecnor to Tesla, we see it has more or less the same shape, so a rather high debt as well. The revenue is only half as high as Tesla’s but there is some profit after all. Of course their business-models are very different. Tesla will spend a lot of money at R&D without caring about profit in the short term.

 

EasyjetEasyjet is surprising. To generate a revenue in the same magnitude as Tesla, they need much more money, because it is expensive to own airplanes and to be compliant with all the regulations in aviation. The equity-ratio is somewhere between the values of Zalando and Tesla, but what really surprised me is the profit. I thought airlines don’t make a lot of profit, but the firm green roof tells me otherwise.

USG PeopleFinally USG people is able to generate a rather high revenue (somewhere between Zalando and Elecnor), without having a lot of money. Neither the equity nor the value for total assets is high. Of course they will hardly have any tangible assets and almost no stock. Most of their expenses will be related to people, so hardly any investment to be made (relatively speaking).

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Visualising a mix of companies in a spatial graph (II)

We already had a look at the revenue, profit, equity and total assets of five very different companies (the well-know Zalando, Tesla and Easyjet, the probably less-known temp agency USG-People and then the Spanish technology company Elecnor). Yet we only presented a range of numbers. Although some people will understand the characteristics of a company – or even recognise the company – from those numbers, it’s better to visualise them. That’s what AnRep3D does: the numbers in the input-file are converted to spatial graphs. Once again, I started the generator and got the screen below:

Start-screen AnRep3D

Then I selected the files for input and output and got the message that the graph was generated. As I double-clicked the output-file (an .htm-file), the graph appeared in my browser. Let’s have a look!

First graph of five companies

The five companies are represented by their buildings, standing abreast. The front-view shows their equities (width) and revenues (height). If the roof is green, there is a profit but a red roof means a loss. All companies show a smaller or larger profit, except for Tesla with it’s very clear red top! So its total revenue was needed to cover all the expenses and then some (the red part).  Yet Tesla’s equity is rather low as the narrow building emphasises! On the other hand, Tesla is able to generate a lot of revenue with a small relative small amount of own money. Of course a lot of other capital (not shares, but loans and bonds) could be available. If we click in the graph, hold the mouse-button an move the mouse downwards, we will see the graph tilt.

Tilted graph of five companies

Now we have a better view at the depth of the building (total assets). If we consider the depth of the building –  from front to back that is – we see the total assets. It should be equal to the combination of equity and liabilities. Looking from this position I knew immediately something went wrong! Both Easyjet and Elecnor showed equities higher than their assets but this doesn’t make sense! Was it a typo or did I switch assets and equity? Well, both actually.

For Easyjet equity and assets were switched indeed. I only noticed when observing the graph. It is stupid, I know but at the same time it shows how powerful a visualisation can be! After correction the Easyjet building will remain the same, only rotated by 90 degrees.

For Elecnor I just put the decimal point at the wrong position. Stupid as well and I’m happy I wasn’t presenting graphs for a meeting of shareholders. After correction this building will get only 10% of the width in the graph shown above. I adjusted the input-file and then the graph had to be generated again of course, but it’s a matter of seconds. This time I used the version with billions instead of millions and as a result  the “scaling factor” cannot be 500 but is 0.5. So actually the values will be doubled. At the same time I had to increase the spacing (to 100) and reduce the font-size (to 3), because of the buildings would become narrower and the labels would overlap as a result of it. Below the corrected input-file – this time with semicolons instead of comma’s as both are allowed as a separator (I’m very sorry I presented a misleading set of values earlier):

5,1,0.5,100,3
Zalando; 2015; 2.96; 0.12; 1.27; 2.12
Tesla; 2015; 3.69; -0.81; 0.83; 5.32
Elecnor; 2015; 1.88; 0.066; 0.74; 3.49
Easyjet; 2015; 6.47; 0.76; 3.10; 6.67
USG_People; 2015; 2.55; 0.020; 0.487; 1.28

Looking at the new graph, based on the improved set of numbers, we can see Elecnor and Easyjet have changed (but the other three still being the same).

Adjusted graph

Because of the increased spacing, the buildings moved into the back as well. By right-clicking the mouse and moving it at the same time, the graph will zoom.

Zooming in

Tilting again (left-clicking the mouse, holding the button and moveing down) we can see total assets being higher than the equity for all companies shown. Easyjet only turned by 90 degrees, but Elecnor only being much smaller than previously.

Tiling zoomed graph

If we would go on, this post would be too long to read, so I keep the in depth discussion for the next time. Meanwhile have a look at www.anrep3d.com

The only advice for now: if you really messed up with tilting or zooming, don’t worry! By clicking the “refresh” button in your browser, the graph will get back to its original position!

Back to original position

Back to original position using the “refresh” button

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Visualising a mix of companies in a spatial graph (I)

In the previous post I presented a number of companies from different branches of industry, with a revenue between – roughly – 1 and 10 billion euros. Easyjet presented its annual report in GBP and Tesla in USD and a formal conversion is not easy. Earnings come in during the year, against fluctuating exchange rates , but the balance is a kind of photograph at the end of the year. On the other hand we know this is just a blog, illustrating the power of visualisation, using spatial (3D) graphs. So an error of about 5% wouldn’t harm. I like http://www.xe.com/currencycharts to convert the currencies but many others are available. After putting all values to euros using a 2015 average for the exchange-rate, I got this input-file:

Inputfile company-mix

Inputfile company-mix

For the people who want to look for themselves, e.g. using the free AnRep3D demo (fully functional, but showing only one company a time) I present the numbers below.

Zalando, 2015, 2960, 120, 1270, 2120

Tesla, 2015, 3690, -810, 830, 5320

Elecnor, 2015, 1880, 66, 7400, 3490

Easyjet, 2015, 6470, 760, 6670, 3100

USG_People, 2015, 2550, 20, 487, 1280

All values are in millions.

I have to admit I didn’t read my own manual (I wrote it myself, I know) and made a stupid mistake as a result (again). Now the parameter-line says: 5, 1, 500, 10, 3 meaning:

  • five companies
  • one annual value each
  • divide all values in data-lines by 500
  • put 10% of extra space between the buildings (because USG People is a long title)
  • choose font-size 3 for the labels

However, instead of 500 for the third value I entered 0.002. I thought it was a multiplier instead of the divider it actually is! One can imagine what happened: the building were huge, gigantic. Zooming out, the labels were nowhere to be found (of course not – their distance to the buildings was enormous as well).

After a while I realised what had happened and corrected the third value. This time the graph was normal and even very interesting . In the next blogpost I will show and discuss  this graph. Meanwhile, have a look at www.anrep3d.com or read the earlier AnRep3D posts.

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Comparing different types of companies in a spatial graph

In previous AnRep3D posts (e.g. Oil & Gas companies in spatial graphs  and Looking at the 3D-graph), a couple of companies in the same branch of industry (oil & gas, banks) were compared in spatial graphs generated by AnRep3D. This time I thought it would be nice to compare a couple of companies from different industries because their “buildings” in the graph will have very different shapes.

Interesting industries to show in such a graph could be retail,  manufacturing, utilities, service providers selling “transport space” (e.g.  an airline or general logistics company) and a service provider selling “people’s hours” (like a temp agency or a consultancy firm).

It’s quite easy to think of a couple of companies, but putting a large one (with a revenue of e.g. over a 100 billion of  euros) next to a smaller one (with e.g. a revenue  of 1 million) wouldn’t be very informative. Therefore the size of the companies shown should be within the same range.

After some browsing I came up with two sets of companies: moderate ones on a global scale and the larger ones.

  • For the first set I chose Zalando, Tesla, Elecnor, Easyjet  and USG  – all with annual revenues between 2 and 5 billion.
  • The second set are Tesco, PSA, E.on, Maersk and IBM  – all with revenues between 50 and 100 billion. Although very different in size, the shape of the building would be more related to the type of industry they are in than their size.

At the moment I am still collecting some numbers for the larger ones, but I could get hold of revenue, profit, equity and total assets for 2015 already. I only have to convert Tesla and Easyjet from USD and GBP to EUR yet. This means the input-file will be created soon. The graph will be available immediately afterwards, because collecting the numbers is the time-consuming part. Of course it’s the other way round for our customers: the numbers are there, but creating a the kind of spatial graph AnRep3D offers would take a lot of time. And that’s why our generator is a useful instrument for analysts!

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Oil & Gas companies in spatial graphs

In some respects Oil & Gas companies are the opposite of banks. Usually they have large amounts of money fixed in all kinds of assets and their equity is mostly over 25% of their total assets. This means Oil & Gas companies  won’t have the “deep” buildings we saw for the banks in our spatial graphs.

On the other hand, the industry had its own crisis: the sudden drop of the oil price. If we look at the graph of the oil-price in time, it looks more or less like this:

Oil-price 2012-2017

Oil-price 2012-2017

Before 2014 everything seemed to be fine, but after 2014 the world was gloomy. That’s why 2013 and 2015 are interesting years to look at balance and profit & loss of some companies in the industry. We took four – headquartered in USA and Europe (UK, Netherlands and France): ExxonMobil, BP, Royal Dutch Shell and Total.

This time the numbers were collected from several websites directly:   https://www.stock-analysis-on.net , http://www.ft.com , http://www.fd.nl  and http://www.redmayne.co.uk

The input-file looks like this (remember – all amounts represent millions, so the actual amounts are mostly billions!):

Input-file Oil&Gas companies

Input-file Oil&Gas companies

After starting the generator (the .jar-file) and selecting the input- & output-files, the graph was generated. The first impression is nice. In the front (2013) large towers with thick green roofs). Completely different from the corridor-like buildings representing banks.

Spatial Graph of Oil&Gas companies - by AnRep3D

Spatial Graph of Oil&Gas companies – by AnRep3D

Even in 2015, although BP showing a red roof (loss) and the buildings being lower and narrower (less equity), they don’t look like banks. However, the buildings in the front – representing 2013 – are much higher than the ones in the second row, representing 2015. It’s certainly not the perspective fooling us! In 2015 the roofs are still green, except for BP, but thinner than  before. Looking from above we can see the companies actually shrunk!

Top-view Oli&Gas graph

Top-view Oli&Gas graph

Of course our message is not about banks or Oil&Gas companies, but about the powerful spatial graphs, generated by AnRep3D.

For those who want to see the real 3D graph and manipulate it themselves, the link is here. Click and hold to tilt and rotate the graph. Double click to translate the graph. Right-click and move to zoom.

 

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Looking at the 3D-graph

Finally we are able to have a look at the AnRep3D graph. Everybody will have .htm-files associated with the browser, so the only thing to do is double click at the file in Explorer (Windows). In the screenshot the graph (we called it blog.htm) is just below the generator itself (the .jar-file).

 selecting output-file

The graph opens in the browser and looks quite small. This is the result of the extreme balances banks have. Hardly any equity compared to the total assets. Because of the narrow, very deep “building” the distance to the graph is quite large.

 first graph

By right-clicking and moving the mouse (or rubbing the touchpad, like I do), the graph will come near.

graph zoomed in

Now we can see something is wrong: the rather long name of ABN-AMRO leads to an overlap of the label with the one for ING. The distance was already 100% extra, so we have to make the label smaller. Either by shortening the name or by reducing the font-size from 5 to e.g. 3. The red line points at the adjusted value in the input-file.

adjusted font

We can start the generator again and choose the same input- and output-files as we took in the previous post. This time the file blog.htm already exists, so the generator asks whether we want to overwrite and we simply confirm.

question

Now the graph is much better and we can start to manipulate it. Zooming in and out using the right button. Tilting, turning by moving the mouse. Translating by clicking somewhere in the graph.

smaller labels

turning

Just try the original 3D graph!

SNS (to the right)  seems to be much, much smaller than the other three. The building for ABN-AMRO in 2005 looks quite large, but in 2010 it is rather small and on top of this, the roof is red instead of green. This means in 2010 there was no profit, but a loss.

ABN AMRO shrunk

In 2015 ABN-AMRO is still small, but the roof is green. Interesting is the width of the buildings. In 2005 they were very narrow, but in 2010 a little bit broader. This is the result of a higher equity, forced by the Basel-accords for banks.

Basel

So by translating just a couple of values from an annual report into a 3D graph, we can learn a lot about a series of companies – just at a glance! AnRep3D.com

Try this 3D-graph yourself!

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