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Reading time: approx. 3 - 4 minutes

Anyone who buys a share and expects a return first thinks of profit growth. The company earns more, the share price rises. This logic is correct, but it only explains part of the reality.

A second lever often has just as strong an effect: multiple expansion. In simple terms, the share price can be broken down into profit multiplied by the multiple. Returns are therefore generated either by rising profits, by a rising multiple, or by both at the same time. The multiple does not rise because more is earned, but because the market is prepared to pay more per unit of profit.

Three factors regularly drive this.

1. change of narrative. If a company is reclassified by the market, the willingness to value it changes.

A cyclical industrial group suddenly becomes a platform. A hardware manufacturer becomes a software company. The decisive factor here is not the narrative alone, but that the market expects a structurally higher quality of cash flows: more growth, better margins, less cyclicality. $MSFT (+3.4%) is perhaps the cleanest example. Under Steve Ballmer, Microsoft was seen as a stagnating Windows company with a P/E ratio of around 10 to 12. Satya Nadella repositioned the company as a cloud platform. The multiple multiplied, but not blindly: Azure growth and margin improvement provided visible confirmation early on. Story and fundamentals picked up together.

2. interest rates. Lower interest rates increase the present value of future profits.

More precisely: the total discount rate, i.e. the risk-free interest rate plus the risk premium on equity, is decisive. Growth stocks react more strongly to this than the market average because their profits lie further in the future. The longer the term of the expected cash flows, the greater the interest rate effect on the valuation. 2022 was a real-time test of this: When the Fed aggressively raised interest rates, highly valued growth stocks such as $PYPL (+0.98%) or $SHOP (+4.13%) fell massively in value. The discount rate effect was dominant, even if operational disappointments were also a factor in both cases.

3. risk perception. When the market perceives a company as safer, the perceived uncertainty of cash flows decreases.

Lower equity costs justify a higher multiple without anything having changed operationally. At $AMZN (-0.57%) this was observed when AWS was reported separately for the first time. Investors recognized that there was a highly profitable cloud segment behind the low-margin trading business. The Group's risk profile was reassessed. The multiple increased.

$NVDA (+1.23%) illustrates multiple expansion better than any textbook example, but with an important nuance. At the end of 2022, Nvidia was trading at a forward P/E of roughly 30 to 40. Then came ChatGPT. Suddenly, investors no longer saw Nvidia as a graphics card manufacturer, but as an infrastructure provider for artificial intelligence. The multiple climbed sharply.

At the same time, earnings estimates exploded. $NVDA (+1.23%) This is therefore not an example of pure multiple run-up, but of the ideal case: narrative change, earnings revisions and multiple expansion occurred simultaneously. All three levers pulled together.

$META (-1.01%) shows the other side. In 2022, the multiple collapsed from around 25 to less than 10. The market no longer believed in the metaverse, feared a structural decline in the advertising business and saw billions disappear into reality labs. Profits fell and the multiple shrank. Double compression.

What followed was re-rating in its purest form. Mark Zuckerberg announced the "Year of Efficiency". Costs were massively reduced and the company reprioritized. Profits recovered quickly. The multiple rose from below 10 to over 25.

Who $META (-1.01%) bought at the end of 2022 or beginning of 2023 caught a rarely clean pattern: profit recovery plus re-rating. Both levers at the same time.

This leads to an uncomfortable truth. The multiple itself is not an independent force, but a function of growth expectations, interest rates and perceived cash flow quality. What cannot be reliably predicted is not the multiple, but how expectations and narratives shift. The market can read the same quarterly figures as confirmation or disappointment, depending on what it has previously priced in.

What you can do is recognize when the multiple is already pricing in a lot of optimism and assess whether the narrative supports it. A P/E ratio of 70 for$NVDA (+1.23%) needs sustained high earnings growth to remain justified. If the multiple compresses to 40 without a drop in earnings, the revaluation alone creates a significant headwind of over 40 percent. This has not happened. $NVDA (+1.23%) has grown into the valuation.

In my view, multiple expansion is more of an observation than a strategy. You can see it more clearly in the rear-view mirror than through the windshield.

The next article turns the question around: What happens when the multiple barely moves? When is pure earnings growth enough to deliver exceptional returns? $AMZN (-0.57%) has shown over two decades that this is possible.

Reading time: approx. 4-5 minutes

I have written a lot about key figures in recent weeks and months. P/E ratios, ROIC, FCF yield, PEG, Rule of 40, interest rates, liquidity, market phases, multiple mechanics, volatility and fiscal policy.

Today I would like to bring it all together.

Because for me, the key insight from the entire series is not a single key figure. It is something more fundamental: key figures only develop their value in the right valuation framework. Without context, they are precise - but not necessarily meaningful.

Key figures measure conditions. Markets act on expectations.

The price of an asset results from the present value of expected future cash flows. Historical profits, margins or cash flows are important reference points. But they are not the future - they are only part of the information base.

A P/E ratio of 30 is neither automatically expensive nor automatically cheap. It is initially a relation between price and profit.

Whether 30 is high or low depends on the interest rate level, growth expectations, risk appetite and the business model. In an environment of low real interest rates, higher multiples are more understandable because the discount rate is low. If interest rates rise structurally, this logic changes. The same profit is discounted more heavily - the multiple falls, even if everything remains stable in operational terms.

With $MSFT (+3.4%) (Microsoft), a higher multiple may be plausible as long as returns on capital are significantly higher than the cost of capital. If the cost of capital rises, the economic leeway is reduced. The company remains qualitatively strong - but the valuation reacts to the framework.

At $NVDA (+1.23%) (NVIDIA), we see how an investment cycle in AI infrastructure can carry a phase of multiple expansion. When growth or investment momentum normalizes, the perception changes. The multiple suddenly looks more ambitious - even though the metric itself appears unchanged.

Or let's take $XOM (-0.79%) (Exxon Mobil). A high FCF yield can arise in a high price phase. That looks attractive. But commodities are cyclical. Cash flows at the peak are often not sustainable. The key figure is correct - its interpretation depends on the cycle.

In the series, I have therefore presented a four-phase model: Build-up, Acceleration, Euphoria, Top. Not as a rigid scheme, but as an aid to interpretation.

Sales growth of 20 % can be seen as very positive in an early phase. In a later phase, the same figure can be perceived as insufficient. The key figure remains the same. The context changes.

Even the PEG ratio is only as good as its assumptions. With $SHOP (+4.13%) (Shopify), a normalization of growth can worsen the PEG without structurally damaging the business model. Forecasts are always subject to uncertainty.

A particularly central point is the relationship between return on capital and cost of capital.

A ROIC of 15 % sounds strong. If the cost of capital is 14 %, there is hardly any economic added value. An ROIC of 12 % can be significantly more attractive if the cost of capital is 6 %. The spread is decisive - not the isolated figure.

At the same time, precision remains important. A structured valuation model helps to make assumptions transparent. Sensitivity analyses show how strongly valuations react to changes in interest rates or margins. It only becomes problematic when the apparent accuracy of the output figure masks the uncertainty of the input assumptions.

The overriding insight is therefore: figures are necessary, but not sufficient.

An investor without key figures loses orientation. An investor with key figures, but without an evaluation framework, runs the risk of developing a false sense of security. Quality arises from the interplay of quantitative analysis, macro understanding, cycle awareness and business model analysis.

The question of whether the P/E ratio is 28 or 30 is not decisive in the long term. What is more important is the market framework in which we operate. Which phase dominates? How are interest rates and liquidity developing? Is the ROIC sustainably higher than the cost of capital? How sensitive is the valuation to changes in assumptions?

This series began with interest rates and liquidity. It then moved on to market phases and valuation mechanics and finally to individual key figures. If I could summarize everything in one sentence, it would be this: Key figures are tools. The valuation framework is the architecture in which they are used sensibly. Classification increases the informative value of key figures. Context structures precision.

If we take this idea further, the question arises as to the next logical steps. Here are four possible directions for the next series:

1. decision architecture in the portfolio

How do I define entry zones along scenarios? How do I determine position sizes depending on uncertainty? How do I deal with winners such as $MSFT (+3.4%) (Microsoft), which are ambitiously valued but remain structurally strong?

2. valuation mechanics & sources of returns

What is the composition of long-term performance? How much return on $AMZN (-0.57%) (Amazon) come from earnings growth, how much from multiple changes? When does earnings growth dominate, when valuation adjustment?

3. cycle investing without market timing

How do I differentiate between $XOM (-0.79%) (Exxon Mobil) structural quality from cyclical exaggeration? What role do earnings revisions play? How do different sectors behave in different phases?

4. quality vs. valuation

When is a valuation premium justified for high returns on capital? When is quality systematically overpaid? How long can spreads between ROIC and cost of capital realistically persist?

I would be interested in your assessment.

Which of these four directions would you prioritize? Or is there a completely different topic that we should systematically explore in more depth?

$SHOP (+4.13%)

Once a celebrated shooting star, now in the crossfire of the AI debate. Is the winning streak of Shopify in danger?

The flag may fly again tomorrow

Shopify belongs to a group of Aktienwhere the narrative changes completely at irregular intervals.

There were times when the company was seen as an alternative to Amazon as an outdated and unprofitable problem candidate, at times no price could be too high, then none too low.

In the last 2-3 years, the share has experienced a renaissance. The operating successes were remarkable and the share price increased almost tenfold.

For some time now, however, a new narrative has emerged and the share has come under significant pressure.

The stock market is currently dominated by one topic. There is growing concern that traditional software providers and SaaS platforms such as Shopify will be replaced by new, KI-focused competitors or alternative technologies.

This debate has led to a veritable "bloodbath" in the software sector. With share price losses of just over 30%, Shopify has come off relatively well compared to many other companies in the sector.

I will spare you the debate about possible disruption at this point. We have already examined this topic in detail using a number of other examples.

There is a certain risk of disruption for almost every company, and this risk has always been above average in the software sector, as small teams of developers repeatedly bring outstanding products to the market - in case of doubt, a single brilliant mind is enough.

Understanding disruption risk: Checklist for investors

However, it may be helpful if I provide you with a checklist that you can use to assess the risk of disruption for companies.

Factors that can Risiko can reduce the risk:

• A fundamentally high level of customer loyalty and a strong contract commitment.
• High switching costs for customers (monetary, training, data migration).
• Deep integration into the customer's existing IT landscape or work processes.
• Customer loyalty through a community, ecosystems, data, networks or additional services.
• The software is a core component of critical business processes.
• High dependency on company-specific data.
• Customizing / tailored workflows and applications.
• Complexity of core functions (difficult to replicate using AI).
• Proprietary algorithms or models.
• High regulatory hurdles in the background.
• Regulated industries / safety-critical software.
• Long project durations for customers.
• Exclusive database / first-party data.
• Strong brand / market leadership.
• Unique selling points that are difficult to copy.
• Highly specialized solutions.
• Integration of AI in own offerings.

On the touchstone

These are the first points that come to mind. In essence, it can be summarized as follows:

The deeper the software is integrated into the customer's work processes and the higher the switching costs, the less likely disruption is. The lower the potential savings, the less interesting a change is.

The risk is particularly low if the software provider can offer an exclusive database or network, as this cannot be copied.

In contrast, the risk of disruption is particularly high when it comes to standardized and interchangeable products. Especially open, easily reproducible functions or low-code.

The hardest hit could be software that has previously performed tasks that can be automated by AI. Such systems could effectively become obsolete.

What does this tell us about Shopify?

Anyone evaluating Shopify on the basis of the previous list, which by no means claims to be exhaustive, will come to a mixed conclusion.

Shopify's customer loyalty is high for a number of reasons and so are the switching costs. Anyone who has ever switched a website from one system to another knows what I'm talking about.

Many merchants use Shopify for core processes such as order processing, warehouse management, payment processing. Payments, taxes and issues such as legal compliance require a stable platform and trust - this cannot be replicated overnight.

In addition, Shopify's range of services is so large that it would be very difficult for an AI startup to copy everything.

On the other hand, it can be argued that new AI providers could put a strain on new business in the future.

For example, if you look at how quickly you can create websites and online stores with the help of AI, the question naturally arises as to whether this will have a negative impact on Shopify's growth.

The same applies to marketing campaigns and other individual features. Shopify customers don't have to move their entire store to the competition. It is enough that individual services are no longer used and are replaced by other providers.

Shopify is booming

Countless AI start-ups are working day and night to make life difficult for Shopify. But this is nothing new, it's been a matter of course since the launch of ChatGPT in 2022 at the very latest.

If you look at the business figures, Shopify's competitors have not been successful so far,

In the time since AI has become ubiquitous, Shopify has significantly increased its revenue from USD 7.06 billion to USD 11.56 billion.

Free cash flow has more than doubled from USD 0.94 to USD 2.15 per share.

No problems were evident in the financial year just ended. At the bottom line, sales increased by 30% to USD 11.56 billion and the operating result by 36% to USD 1.47 billion.

Free cash flow improved by 26% to USD 2.01 billion.

The value of all goods and services processed via Shopify's systems climbed to the impressive sum of USD 378.4 billion in 2025 (compared to USD 292.3 billion in the previous year).

There was also no sign of a slowdown in growth momentum over the course of the year. In the final quarter, growth amounted to 31%.

The operating result rose disproportionately, which also indicates that Shopify is still able to hold its own against the competition.

First cracks?

The only blemish is the FCF margin, which fell slightly from 18% to 17% in the last financial year.

Shopify attributes the decline primarily to increased investment in AI tools and platform development to secure future growth.

The much bigger problem, in my view, is that this trend could continue.

For the first quarter, Shopify is forecasting an increase in revenue in the "low 30 percent range", i.e. continued high growth.

However, gross profit is expected to increase at a somewhat slower rate, in the "high 20 percent range".

The FCF margin should even fall slightly over the course of the year

Shopify share: Chart from 16.02.2026, price: USD 112.70 - symbol: SHOP | source: TWS

Changes on this scale should not be overestimated, but it could be a first sign that competition has become tougher.

It is equally possible that this is not due to external effects, but simply to the fact that the Merchant Solutions segment is currently growing faster than the even more profitable Subscriptions Solutions division.

According to consensus estimates, FCF is likely to increase by 32% to USD 1.87 per share in the current financial year.

Shopify therefore has a multiple of 60 and is therefore unlikely to be an option for many investors.

However, it is also true that Shopify has almost been Börsengang just over ten years ago, Shopify has been valued almost consistently higher.

The same applies to other Kennzahlen. The P/E ratio is currently 12.3, for example. The long-term average was 17.7 and the average over the last five years was 16, despite the share price collapsing in the meantime

https://www.lynxbroker.de/boerse/boerse-kurse/aktien/shopify-aktie/shopify-analyse/?a=3355991664&utm_medium=email&utm_source=newsletter&utm_campaign=newsletter-boersenblick&newsletter=true&mc-rss-cache-bypass=2026021707&goal=0_d93daae099-25e554efe6-410756260#wie-sie-die-ki-gefahr-bei-shopify-und-anderen-aktien-besser-einschatzen-konnen

I'm a bit confused right now.

At the beginning of the year, my €1000 exemption order was reset to €0 (as usual). So far everything is normal.

So far this year I have:

• a larger partial sale → $SHOP (+4.13%) with a profit of around €350
• a few dividends → under €150 in total
• I have even sold 4 positions in the red $MCD (+0.25%) & $7974 (+0.9%) & $LOTB (-0.99%) & $QDV5 (+0.86%) (about 150€ minus)

Means: I should be somewhere around ~350-400 € usage.

Nevertheless, Trade Republic shows me that my exemption order has already been exhausted.

In addition, I notice:

➡️ For about two weeks now, capital gains tax has been withheld on all dividends, as if the exemption amount had been completely used up.

This cannot be mathematically correct.

Have you ever experienced this?

• Display bug?
• Advance flat rate? I don't even see it yet
• Delay in the internal calculation?
• Or a known problem at Trade Republic?

Before I contact support, I wanted to hear whether this has already happened to you.

Thank you 🙏

$SHOP (+4.13%) presented its Q4 2025 earnings figures today

Key figure earnings (Q4 2025)

Comparison to previous year (YoY)

Turnover 3.67 billion $ +31 %

GMV (gross merchandise volume)

123.8 billion $ +31 %

Earnings per share (adj. EPS) $0.57

(Expected: 0.43 - 0.51 $)

Free cash flow

715 million $

19 % margin

🚀 The most important drivers

• Growth series: This was the eleventh consecutive quarter of sales growth of over 25% (adjusted for logistics effects).
• AI focus: President Harley Finkelstein emphasized that 2025 was the year in which the tracks were laid for the "new era of AI commerce" (AI commerce). Products like Sidekick and the Universal Commerce Protocol were the focus.
• Share buyback: Surprisingly, a 2 billion dollar share buyback program was was announced, underlining management's confidence in its own cash generation.

🔮 Outlook for 2026

Shopify is very optimistic for the first quarter of 2026:

• Revenue growth: An increase in the low low 30 percent range (analysts had only expected around 25%).

Gross profit: Expected to grow in the high 20s percent range.

To summarize: Shopify continues to deliver strong growth and profitability at the same time - a combination that the market is currently celebrating to the extreme.

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