$SAP (-0.73%) would now be a good starting point ? After this has already fallen so well

In terms of my portfolio performance/volatility, the last few weeks have probably been the craziest weeks since I started investing. Within a week, my portfolio lost over 100,000 euros in value during the precious metals crash only to gain back over 200,000 euros in value in the subsequent recovery by the end of February.

As a result, I reached a new milestone at the end of February. For the first time, the portfolio value exceeded the EUR 1.5 million mark. 😊

👉🏻 February:

Start: 1,368,240 euros + 100 cash

End: 1,559,4604 euros + 300 cash

Deposit: 5,400 euros

Profit: +186,020 euros (+13.59%)

The increase in value is mainly due to the good performance of my gold portfolio stocks (K92 Mining $KNT (+0.42%) and Equinox Gold $EQX (-0.45%) ). In the meantime, the gold price has slowly risen again and this is of course also reflected in the share prices. The two companies together now account for over 50% of my portfolio... This is actually an unreasonable ratio, but I am still convinced that there is still a lot of potential here. Both companies are in a great operational position, are debt-free and have even announced small dividend payments as a reward. 👍🏼

Otherwise, I continued to sell and buy here and there in February. I took profits on Puma $PUM (+0.05%) , Vonovia $VNA (-1.1%) , Henkel $HEN3 (-0.41%) , K+S $KSC , Target $TGT (+0.05%) and Western Union $WU (+0.14%) while I increased my position in SAP $SAP (-0.73%) , PayPal $PYPL (-0.57%) and Novo-Nordisk $NOVO B (+0.1%) further expanded.

The Iran war will certainly cause some turbulence on the stock market in the coming days. Experience shows that precious metals will benefit in times of uncertainty, but the oil price is also likely to receive a significant tailwind. With my high exposure to gold and my position in Occidental Petroleum $OXY (+1.49%) I believe I am well positioned, at least in the short term. 👍🏼

➡️🆓: On my way towards 4 million total assets, the target achievement level is now 49.8%.

Here's to good stock market trading and see you in a few days! 😊

I also see with $SAP (-0.73%) .

$NVDA (-0.27%) and other pure AI companies are currently being punished because many market participants fear that AI could be a bubble. At the same time, classic software vendors such as $SAP (-0.73%) or $IBM (-0.3%) are also coming under pressure - ironically on the grounds that AI can now develop better software. And energy companies are also being eyed with suspicion.

All of this cannot be true at the same time and does not fit together logically.

In my opinion, there is currently a largely unfounded fear of any kind of change in the market. This fear leads to a strange reticence and at the same time feeds the doomsday apologists.

On closer inspection, the thesis that "AI is replacing traditional software" is highly questionable - especially when it comes to business-critical applications:

Imagine every user simply building their own accounting software with AI. Sounds tempting at first. But in practice, an accounting system must function reliably and deterministically function reliably and deterministically. But that's exactly what modern large language models and neural networks can't do.

Neural networks are generally not deterministic (or only under very narrow conditions). More importantly, they cannot be proven mathematically correct - and the problem of formally verifying large neural networks is NP-hard (or in many cases even NP-complete).

In concrete terms, this means that if an AI-based SAP system has to process exactly the same calculation three times in succession, it is not that the result will always be exactly the same. And even less so for another, but actually equivalent, calculation.

The situation is even more critical in security-relevant areas (cybersecurity, medicine, aviation, autonomous systems, etc.). Here it is essential that threats are reliably and reproducibly recognized.

In short: Determinism, formal verifiability, governance and reliable reproducibility are still extremely important values for business software. This is why the hype that "AI will soon replace all traditional software" should be viewed much more calmly and critically.

The state as a market player

When debt is problematic - and when it enables growth. Classification beyond simple debt ratios

Reading time: approx. 5-6 minutes

Fiscal policy is not a side issue for the markets in 2026. It is a valuation factor. Budget deficits, special funds, defense budgets, industrial policy - all of these have a direct impact on yields, valuation multiples and sector rotations. If you only look at debt ratios, you miss the point. The decisive factor is the ratio of growth to interest rates - in short: g to r.

g stands for the nominal growth of an economy, i.e. real growth plus inflation. r stands for the average effective interest rate at which a state refinances itself. The sustainability of debt depends largely on how these two variables relate to each other.

The key correlation is as follows: as long as the nominal growth of an economy is higher than the average financing rate of its debt, the debt ratio stabilizes or decreases relative to GDP - even in the case of moderate primary deficits. Formally: If g > r, time works for the debtor. If r > g, time works against him.

Why is this the case? Government debt is measured in relation to economic output. If GDP grows faster than interest costs, the economy "grows" relatively into debt. The ratio falls or remains sustainable. If the ratio reverses, interest expenditure increases relatively more than the economy's income. This creates fiscal pressure.

This logic is not new. It can already be found in classical debt arithmetic and has often been linked to the inequality formula r > g from the work of Thomas Piketty in more recent discussions. It is important to classify it correctly: there, r > g describes the relationship between return on capital and growth in the context of wealth concentration. The mechanics are similar for public finances, but the focus is different - it is about debt sustainability. The mathematical core is related, but the economic application is different.

Applied to 2026, this means that in a world of structurally higher interest rates, the difference between g and r will become the decisive macro lever.

The German government debt ratio is currently around 63-65% of GDP. Internationally, this is moderate. However, the decisive factor is momentum. Nominal growth has recently been roughly in the region of 2-4 %, depending on the quarter. At the same time, new issue yields for ten-year German government bonds are in the range of around 2.5-3 %. Germany is therefore in a borderline zone. g and r are close to each other. A clear growth advantage no longer exists automatically as in the zero interest rate regime.

This makes the quality of fiscal spending crucial. If additional debt has a primarily consumptive effect, the ratio rises faster than economic output. If, on the other hand, it flows into infrastructure, digitalization or defence capacities, it potentially increases trend growth - i.e. g - and shifts the equation in favour of sustainability.

Rising defense budgets have a direct impact on $RHM (+1.39%) (Rheinmetall AG). Infrastructure and industrial projects increase the order base at $SIE (-1.99%) (Siemens AG). Grid investments stabilize regulated cash flows at $EOAN (+0.44%) (E.ON SE) and $RWE (+1.36%) (RWE AG). Digital modernization strengthens providers such as $SAP (-0.73%) (SAP SE) or security providers such as $YSN (-1.18%) (secunet Security Networks AG). These are concrete fiscal transmission channels in sales, cash flow and margins.

But every additional issue also has an impact on the bond market. Higher supply can cause yields to rise. Higher yields increase discount rates - particularly relevant for long-dated growth cash flows. Fiscal policy therefore generates two forces: profit impetus through demand and valuation pressure through higher capital costs. Which one prevails depends on the market framework.

In the US, the government debt ratio is significantly higher - roughly in the range of 115-125% of GDP. At the same time, nominal growth is more robust than in Europe. As long as nominal growth is in the range of around 4-6% and long-term Treasury yields are below or only slightly above this level, the debt dynamic remains manageable. It becomes critical when interest expenditure rises faster than the nominal income of the economy.

Industrial policy programs have a direct impact on individual sectors. Semiconductor investments stabilize investment cycles at $INTC (-0.64%) (Intel Corporation) and $NVDA (-0.27%) (NVIDIA Corporation). Defense spending supports $LMT (-0.26%) (Lockheed Martin) and $NOC (-0.14%) (Northrop Grumman). Infrastructure programs have an impact on $CAT (-0.74%) (Caterpillar Inc.). Tax incentives in the energy sector stabilize cash flows at $NEE (-0.25%) (NextEra Energy). Fiscal policy becomes a sector-specific source of income.

The historical US post-war example illustrates the dynamics. After the Second World War, the debt ratio was over 100 %. It fell significantly in the following decades. Strong nominal growth played a central role. At the same time, financial repression, regulated capital markets and phases of unexpected inflation had a debt-reducing effect because they reduced real interest burdens. g was greater than r for a longer period of time - partly also influenced by politics.

Conversely, the European sovereign debt crisis showed what happens when r > g and confidence wanes. Rising risk premiums increased interest costs, growth stagnated and the debt ratio turned negative.

For investors, this means that debt is not a moral judgment, but a mathematical and institutional issue. The decisive factors are growth, interest rates and confidence. If you only look at the debt ratio, you ignore the dynamics behind it.

In 2026, it is precisely these dynamics that will be decisive. In an environment without a zero interest rate buffer, fiscal policy is no longer an automatic growth lever. It can enable growth - if it is used productively and g is stable above r. However, it can also generate valuation pressure if r rises above g in structural terms.

The state is therefore one of the largest allocators of capital in the world. Its budget decisions act like an additional investment fund in the trillions. If you want to understand markets, you have to read this dynamic in the valuation framework - not in isolated percentages.

The next part will conclude the series: Part 10 - Why key figures fail without a valuation framework. There I will bring the entire series together with the key figures series - and show why classification is more important than mathematical precision.

I've picked up a few really exciting thoughts over the last 2-3 days that I wanted to share. The current software sale is part of a rotation that has been going on for a while now

The thesis: HALO instead of Asset Light 😇 Josh Brown (The Compound) put it aptly: for years, "asset light" (software, data, consulting) was the non plus ultra. High margins, no physical ballast. Today, that's exactly the risk. If your product consists only of information, an LLM can replicate it. The flight is now into HALO (Heavy Assets, Low Obsolescence) - companies that own "real" things that can't just be prompted away.

SAAS - Is the "per seat" model dead?

Nate (super exciting guy) posits the thesis: AI needs software. AI doesn't just replace $CRM (-0.43%) or $SAP (-0.73%) & CO. That's nonsense. But that's what SaaS is struggling with. AI replaces people >>> The "per seat" business model, the non-plus-ultra of the SaaS world, is faltering.

Interesting sectors according to Dan Ives (Sell Side - has funds himself, bias!!!)

Enterprise AI: Palantir ($PLTR (-0.41%))

"The first address" for AI applications in government and companies. He sees the path to a trillion-dollar valuation here.

Cybersecurity: CrowdStrike $CRWD (-0.26%) & Palo Alto $PANW (-0.01%)

AI makes attacks more dangerous, so every company needs better defenses.

Data layer: Snowflake $SNOW (+0.51%) & MongoDB $MDB (-0.45%)

Before an AI can work, the data must be cleanly structured. These companies are the "garbage collection and sorting system" for AI data.

Platform giants: Microsoft $MSFT (-0.14%) & Salesforce $CRM (-0.43%) or $SAP (-0.73%)

He sees Salesforce as massively undervalued (P/E ratio of approx. 15), as the market is ignoring the potential of "Agentforce" (AI agents).

AI models are worthless without context. The big SaaS players are sitting on the companies' historical data. Whoever has the data controls the AI agents that access it. That's the reason why, according to Ives, they are not simply "prompted away".

Sources:

Okay Computer Podcast (Dan Ives / Dan Nathan)

The 200-line prompt that killed $285B (NoteGPT/Anthropic Analysis)

What Are Your Thoughts / Animal Spirits (Josh Brown & Michael Batnick)

$SAP (-0.73%)

The fall in the share price of SAP came as a surprise, but not without reason. The key question, however, is whether the sell-off is justified.

When expectations are disappointed

The slump in the SAP share price came as a surprise to many investors, but had several clearly identifiable causes. The disappointing development in the cloud business was cited as the main reason for the sell-off.

SAP is regarded as one of the most important European beacons of hope here, but growth in the cloud backlog was weaker than forecast. This is explosive, as this order volume represents future revenue. When SAP also signaled that cloud growth could slow down in 2026, the mood tipped abruptly. Confidence turned into skepticism, which immediately led to selling pressure.

This was compounded by the fact that individual Kennzahlen did not meet expectations. This was enough to make analysts nervous. Several banks and research houses lowered their price targets or downgraded the share. In a tense market environment, such signals act as an accelerant.

Added to this is the generally negative sentiment towards software companies. Increasing uncertainty about economic development, coupled with doubts about traditional business models in the age of artificial intelligence, are weighing on the entire sector.

SAP as an AI loser?

And AI is currently being used as an argument for everything anyway, as in the case of SAP. In the course of the share price slump, SAP was also described as an AI loser in some places. However, I have not found any tangible arguments for this thesis. Nor do I understand the logic behind this idea.

SAP's products are deeply embedded in the core operational processes of companies.

Purchasing, financial accounting, logistics, human resources and production planning are highly complex, data-intensive and business-critical.

AI is used here as a tool to increase efficiency, but not as a replacement product for SAP. As a rule, AI providers have no direct access to these processes at all, unlike SAP.

Furthermore, SAP has a structural advantage that pure AI companies do not have: high-quality, company-specific data. AI is only as good as the data it works with. The most valuable data is not in open models, but in ERP systems. SAP has controlled this level of data for decades. Anyone who wants to optimize business processes can hardly avoid this database.

More likely psychology

Furthermore, ERP systems are not replaced lightly. The switching costs are high, the integrations are deep and the risks are enormous. AI can improve, accelerate and simplify these systems - it does not replace them.

SAP offers exactly what corporate customers need: Control, security, compliance and traceability. Many generative AI solutions are difficult for companies to manage from a regulatory or operational perspective and are unthinkable as an alternative, especially for larger companies.

In my view, the narrative of "AI loser SAP" is ultimately based less on facts than on stock market psychology.

Really disappointing?

But all this is just my assessment. There is probably another way of looking at it. In the end, the truth is in the figures. So let's take a look at them.

In this analysis, I would like to focus on the question of what is "disappointing" and what is not.

SAP's quarterly figures and outlook have been widely described as disappointing, but that is in the eye of the beholder.

In this case, the dividing line should be clear. On the Börse more weight was given to the fact that expectations were not met - which is usually the case.

For investors, however, the decisive factors are whether the company is developing in the right direction, whether the outlook is positive and whether the valuation is right.

In the fourth quarter, sales increased by 3% to EUR 9.68 billion, but adjusted for currency effects, the increase was 9% and therefore only just below the figure for the full financial year of 11%.

However, the sales figures are still distorted by the transformation towards the cloud.

Profit and cash flow increase massively

The operating result increased by 27% to 1.90 billion euros in the fourth quarter. Profit improved by 16% to 1.62 euros per share. You can be disappointed by this - or not.

The operating result improved from EUR 8.15 billion to EUR 10.42 billion in the 2025 financial year, an increase of 31%.

Earnings per share climbed by 36% from EUR 4.53 to EUR 6.15 per share (both non-IFRS).

Free cash flow almost doubled over the year from EUR 4.22 billion to EUR 8.24 billion.

You can also be disappointed by this - or not. It is in the eye of the beholder. Rationally, however, it is perfectly clear how such business figures should be classified - there is no need to comment further.

Outlook and valuation

The order intake suggests that the positive trend is likely to continue for the time being. The current cloud backlog increased by 16% to EUR 21.05 billion. Adjusted for currency effects, the increase was even 25%.

For 2026, SAP is forecasting an increase in cloud revenue from EUR 21.0 billion to EUR 25.8 - 26.2 billion, which corresponds to growth of 23 - 25 %.

Cloud and software revenue is expected to increase from EUR 32.54 billion to EUR 36.3 - 36.8 billion and the operating result from EUR 10.42 billion to EUR 11.9 - 12.3 billion.

Free cash flow is expected to increase from EUR 8.24 billion to EUR 10 billion. SAP therefore expects a jump in profit of around 16% and an increase in free cash flow of 22%.

This may also disappoint - or not.

According to the report, SAP has a P/E ratio of 23.8 and a forward P/FCF of 20.8, which is reasonable in view of the double-digit growth rates.

Over the last five years, the P/E ratio has averaged 26.3 and the P/FCF 27.5.

In the course of the quarterly figures, a two-year share buyback program with a volume of up to EUR 10 billion was approved, which corresponds to around 5% of the market capitalization

SAP share: Chart from February 9, 2026, price: EUR 173.42 - symbol: SAP | Source: TWS

A return above EUR 175 would ease the situation from a technical perspective. Above EUR 183 there would be a procyclical uptrend Kaufsignal with possible price targets at EUR 200 and EUR 214.

If, on the other hand, the share falls below EUR 165, an extension of the correction towards EUR 148 - 150 must be expected.

Source

https://www.lynxbroker.de/boerse/boerse-kurse/aktien/sap-aktie/sap-analyse/?a=3355991664&utm_medium=email&utm_source=newsletter&utm_campaign=newsletter-boersenblick&newsletter=true&mc-rss-cache-bypass=2026021007&goal=0_d93daae099-3e7ba2c904-410756260#sap-enttaeuschend-oder-nicht-das-ist-die-eigentliche-frage

In this video, I analyze two of the most important heavyweights in the DAX, each of which has an index weight of around 9.5%:

• SAP
• Siemens

Both shares have an enormous influence on the market as a whole - and are currently on the brink of decisive decisions.

SAP analysis: Following the publication of the latest quarterly figures, the $SAP (-0.73%) collapsed by around -14 %.

I analyze in detail:

• the causes of the share price decline
• the development of earnings figures
• the valuation after the setback
• the most important technical support and resistance levels

I also clarify whether the sell-off was exaggerated or whether there are structural risks behind it. Siemens analysis (before the quarterly figures on 12.02.):

$SIE (-1.99%) Will present its quarterly figures shortly. I am investigating the question:

• what earnings figures can realistically be expected
• how to classify the current valuation
• which technical chart zones are now decisive
• whether Siemens faces a similar risk to SAP after the figures

Comparison of SAP vs. Siemens: A central focus of the video is the direct comparison of the two companies. I analyze whether a similar scenario could develop at Siemens as at SAP - or whether the share is fundamentally and technically more stable.

In this video you will learn

• how I assess earnings risks
• how I define buy, sell and target zones
• how large corporations affect the DAX
• when setbacks are opportunities - and when they are not

This video is aimed at active traders, swing traders and investors who want to make informed decisions on DAX heavyweights.

https://www.youtube.com/watch?v=5aJ6sBqAr64

Last week, Siemens was $SIE (-1.99%) had overtaken SAP $SAP (-0.73%) then SAP was ahead again on Thursday. The two companies are currently on an equal footing with a market capitalization of around 200 billion euros each.

In the 38-year history of the Dax, which was launched on July 1, 1988, no other company has been at the top as often as Siemens, according to Handelsblatt calculations. One of the Munich-based company's recipes for success is reliability in the form of steadily rising earnings and dividends. Added to this is the ability to constantly adapt to industrial developments.

Ten of the current 40 DAX companies have been represented in the selection index, which originally only included 30 stocks, from the very beginning: Allianz, BASF, Bayer, BMW, Deutsche Bank, Henkel, Mercedes-Benz (then still under the name Daimler-Benz), RWE, Volkswagen and Siemens.

According to calculations by the Handelsblatt Research Institute, Siemens shares have performed best among these Dax veterans, with a price increase of almost 2300 percent. Anyone who has held the share since the Dax was founded has achieved an average price gain of 8.7 percent per year.

This does not include the many dividends paid to shareholders. Siemens shares have risen by around 5,850 percent when price gains and dividends are added together. This results in an average annual return of 11.3 percent.

No share that has been listed on the Dax since the beginning has performed better. By way of comparison, the Dax as a whole, including all dividends, has achieved an average annual return of 8.8 percent since its inception.

This Siemens return does not even take into account a particularly rewarding transaction for investors. Anyone who held Siemens shares at the end of September 2020 automatically received one Siemens Energy share free of charge for every two shares held. $ENR (-1.27%) booked into the securities account.

With this step, Siemens spun off its power plant division. The new shares ended the first trading day on September 28, 2020 at €21.21 each. One share currently costs 153 euros. This corresponds to an increase of 621 percent in just five and a half years.

Siemens shareholders will soon receive another substantial bonus. After its power plant business, Siemens is spinning off its medical division. This is already listed on the stock exchange under the name Siemens Healthineers $SHL (+0.42%) and is also listed on the Dax. However, Siemens currently holds around 67 percent of the shares.

This means that Healthineers is still fully consolidated in Siemens' balance sheet, i.e. Siemens recognizes the profits in its balance sheet. This will soon change, as 30 percent of Healthineers shares are to go to Siemens shareholders in a direct spin-off. They are to receive the new shares in their securities account, similar to Siemens Energy. What the distribution ratio will look like is still open.

With this deconsolidation of the medical technology unit, which has been listed on the stock exchange since 2018, the Siemens Group will lose almost a third of its sales, and the spin-off will also leave its mark on profits. For the current fiscal year, analysts are forecasting an average net profit of €8.1 billion for Siemens, compared to €9.6 billion last year. The reason for this is the loss of Healthineers.

Nevertheless, this strategy makes sense from an investor's point of view, as Siemens' priority is to grow faster and become more profitable. This shareholder-friendly focus is the reason why there are more and more different shares in the Siemens family.

Infineon $IFX (-1.79%) is one of them, as Siemens floated its semiconductor division on the stock market back in 2000. There are now four Siemens shares in the Dax.

One reason for the many buy recommendations by analysts (currently: 21 buy | 4 hold | 4 sell) for Siemens is, in addition to the ambitious, but compared to its competitors, more favorable valuation, the profit sharing for shareholders. The Managing Board intends to increase the dividend from €5.20 to €5.35 for the past fiscal year, which at Siemens ended on September 30, 2025. This is the fifth increase in a row. The dividend has more than tripled since 2010.

At 2.1%, the dividend yield is rather low by historical standards. In the last 20 years, there has almost always been at least three percent to be had. However, the lower yield is by no means the result of slower rising, let alone falling, dividends, but solely due to the enormous increase in the share price. Over the past three years, the share price has risen by 80 percent.

The dividends have not been able to keep up with this rapid development. As a result, the dividend yield for new entrants has fallen. However, this is not a real problem in view of the sharp rise in the share price.

Source text (excerpt) & image: Handelsblatt, 05.02.2026