I'm curious to hear what you have to say. I have selected 3 shares that pay dividends and have been declining recently and are of course considered worth buying by analysts. $1211 (-1,62 %)
$SAP (-1,1 %)
$CTEC (+1,14 %)

Diese 3 Aktien könnten im Dezember richtig spannend werden! 🚀📈 - YouTube

Why do we read so little about SAP here? $SAP (-1,1 %) I find the correction and the current share price very interesting for an initial entry. Or am I alone in this?

Please let me know your opinion on the German software company.

Reading time: approx. 8 minutes

In one of my last articles on the weaknesses of the P/E ratio, I showed why the seemingly simple price/earnings ratio can easily be misleading. It takes into account neither the capital structure nor the level of debt of a company, ignores special accounting effects and makes companies from different sectors artificially comparable, even though their business models function completely differently. Three central problems stand out in particular:

• Debt: Two companies with the same P/E ratio can have completely different risk profiles if one is highly indebted.
• Accounting logic: Depreciation and amortization, taxes and one-off effects can strongly distort profits - the P/E ratio reacts sensitively to this.
• Sector comparison: Capital-intensive industrial companies and scalable software companies can hardly be meaningfully compared using the P/E ratio.

If you want to gain a deeper understanding of what a company is really worth, you have to look beyond the share price alone and look at enterprise value (EV). While the P/E ratio only reflects the market value of the equity, the EV comprises the entire enterprise value, i.e. what a buyer would actually have to pay. The formula is simple: EV = market capitalization + debt - cash and cash equivalents.

This reveals the economic reality: a company with a high cash position is actually cheaper than the P/E ratio suggests, while one with a high level of debt is more expensive. In combination with EBITDA - earnings before interest, taxes, depreciation and amortization - this results in EV/EBITDA, the key figure that has long been standard in professional financial analysis.

EBITDA reflects the operational strength of a company before financing decisions or tax effects distort the picture. If you put the enterprise value in relation to this operating profit, you get a structured answer to the question: How many years of the current EBITDA would a buyer have to pay to take over the company completely?

This approach is much more meaningful than the P/E ratio. Two companies with identical earnings and the same market capitalization can be valued completely differently with identical P/E ratios as soon as their debt is taken into account:

• Both generate €1 billion profit with €10 billion market capitalization → P/E ratio = 10.
• Company A: no debt → EV = € 10 bn.
• Company B: additional debt of € 5 bn → EV = € 15 bn.
• With the same EBITDA of € 1.5 billion, the EV/EBITDA is 6.7x (A) and 10x (B).

Same profit, completely different risk.

This is precisely the strength of EV/EBITDA: it is neutral in terms of capital structure, focused on operating earnings power and comparable across sectors. Especially in the M&A environment or for private equity investors, it is the key valuation indicator because it shows what is paid for the actual business - regardless of the form of financing.

Typical valuation levels vary by sector:

• Capital-intensive sectors such as energy, chemicals or engineering: usually 5-8x.
• Software and MedTech companies: often 15-25x.
• $SAP (-1,1 %) (SAP SE): historically around 10-12x EV/EBITDA.
• $ADBE (+0,23 %) (Adobe Inc): around 18-22x EV/EBITDA.
• $BAS (+0,72 %) (BASF SE): regularly below 6x, due to high capital commitment and cyclicality.

EV/EBITDA is not an absolute figure, but a ratio that should be read in the context of the market environment. Multiples rise during upswings and fall during recessions. Nevertheless, a rough guide is: below 7x is considered favorable, 7-12x as fair, above 12x as ambitious or growth-driven.

Of course, this ratio also has its limits. It ignores investments, taxes and actual cash flows and can make capital-intensive business models appear too positive. It should therefore always be considered together with key figures such as EV/EBIT, free cash flow yield or the PEG ratio.

At its core, however, EV/EBITDA remains the more realistic benchmark: it brings operating performance, debt and market value into a common relationship and shows what a company really costs. The P/E ratio may be simpler - but those who rely on simplicity often only see half the truth.

How do you proceed? Do you use EV/EBITDA as the central valuation indicator or does the P/E ratio remain the starting point for you? And in which sectors do you think the ratio reaches its limits?

Deutsche Telekom $DTE (+0,32 %) wants to enter the construction and operation of data centers for artificial intelligence (AI) on a large scale. Group CEO Timotheus Höttges announced in Berlin the launch of a joint project with the US chip company Nvidia $NVDA (-0,47 %) in which a so-called AI factory is to be built in Munich at a cost of over one billion euros.

"Without AI, you can forget about industry," said Höttges. "Without AI, you can forget about Germany as a business location." The Deutsche Telekom CEO pointed out that only five percent of high-performance AI chips are currently used in Europe, compared to 70 percent in the USA.

Höttges emphasized that the data in the Munich AI cloud should remain entirely in Germany. Only employees from Germany and Europe would be used to handle the data. And the technology comes from Germany and the USA. This means that there are no longer any excuses for German and European companies not to use AI on a large scale.

》Great day for Germany and Europe《

Federal Digital Minister Karsten Wildberger (CDU) spoke of "a great day for Germany and for Europe". "We are celebrating an investment with a signal effect: more than one billion euros for an AI factory with the most modern chips in the world." But this is more than just an AI factory for industry. "It is a signal of new beginnings. A further step on Germany's path to resolutely exploiting the opportunities offered by artificial intelligence."

In Berlin, Nvidia CEO Jensen Huang recalled that the concept of Industry 4.0 was developed in Germany. "Germany had this vision of connecting the digital world with the physical world.

With AI, we can now bring a super version of Industry 4.0 to life. And this is a new era, namely industrial AI." Nvidia is the world's leading provider of high-performance chips that are essential for training and using AI.

Deutsche Telekom is already a provider of conventional cloud services and operates over 180 data centers worldwide. At the same time, the Group cooperates with large platforms such as Google Cloud, Amazon AWS $AMZN (-0,53 %) or Microsoft Azure in the cloud business.

However, Deutsche Telekom's economic success is driven by its core business with telco services in Europe and the business success of its US subsidiary T-Mobile $TMUS (-0,03 %) business success.

》Part of a larger AI strategy《

The AI data center in Munich's Tucherpark is just the start of a larger-scale AI strategy at Deutsche Telekom. The Group hopes to be considered for a major European Union funding program for so-called AI Gigafactories.

The EU defines a gigafactory as a data center with 100,000 or more special AI chips (GPUs) - the facility in Munich will only run with 10,000 GPUs.

In order not to lose touch with the future topic of AI and at the same time remain independent of US companies such as Open AI, Google $GOOGL (-0,37 %)Microsoft $MSFT (-0,4 %) and Meta $META (-0,56 %) Brussels is planning to promote the construction of four to five such large data centers.

The interested parties from Germany were unable to agree on a uniform application. Therefore, in addition to Telekom, the Schwarz Group, which is behind Lidl and Kaufland, the cloud provider Ionos $IOS (+0,58 %) and other consortia.

Federal Research Minister Dorothee Bär (CSU) emphasized the importance of this initiative. At least one AI Gigafactory must come to Germany.

With the Bavarian AI factory, Deutsche Telekom is primarily targeting users in industry.

The first customers include Agile Robots $AGL (+0 %)a leading German high-tech company that specializes in AI-controlled automation solutions and intelligent robotics.

In addition to Nvidia, other cooperation partners include Europe's largest software company SAP $SAP (-1,1 %)Deutsche Bank $DBK (-0,61 %) and the AI provider Perplexity.

Nvidia $NVDA (-0,47 %) and Deutsche Telekom $DTE (+0,32 %) are preparing to launch a billion-euro initiative for a data center in Germany. This was reported by the Bloomberg news agency, citing sources familiar with the matter. The project is intended to meet the region's demand for computing capacity.

Europe's largest software group SAP $SAP (-1,1 %) is expected to be the anchor tenant of the data center. The plans themselves have been known for some time, but no official announcement has yet been made.

An event in Berlin in November could be the occasion for the announcement. Deutsche Telekom CEO Tim Höttges, Nvidia CEO Jensen Huang, SAP CEO Christian Klein and Digital Minister Karsten Wildberger are expected to attend. The event is planned for Munich, a source said.

The project aims to develop regional AI capabilities. In the US market, companies such as Microsoft and Google have invested hundreds of billions of US dollars in AI infrastructure. Europe is lagging behind both US and Chinese competitors in this area.

》Europe's AI infrastructure offensive comparatively small《

Nvidia's management previously expressed concerns about Europe's pace in expanding its computing infrastructure. European companies are reaching their limits if they want to use AI systems and at the same time maintain data sovereignty within European borders.

The planned facility will use around 10,000 graphics processors - specialized chips that power AI systems. However, this dimension remains modest compared to projects elsewhere. A data center developed in the US state of Texas by Softbank, OpenAI and Oracle is designed for around 500,000 GPUs.

In February, the European Union presented a 200 billion euro plan to promote AI development in the member states. The initiative aims to triple the region's AI computing capacity over the next five to seven years. However, implementation of the plan is slower than expected.

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After giving a lot of thought to whether I should add to one of my many positions or look for a tidbit, I decided to welcome SAP to my portfolio - one of the few companies in Germany that still has sufficient potential, but is moving sideways this year.

In addition, I will probably be getting rid of some positions soon and cleaning up my portfolio a little by the end of the year - at least that's my plan... The following are the main ones that catch my eye

$PUM (+1,72 %)

$LXS (-1,85 %)

$PAH3 (-1,23 %)

$SIX2 (+0,11 %)

Once bought with the idea of dividends and a possible turnaround in mind, I doubt that the situation with these companies will change abruptly and now regard them more as yield killers.

SAP comes in handy as an addition in order to still be able to invest alongside $ALV (-0,25 %) and $DHL (-0,14 %) another German company in the portfolio.