The French group Schneider Electric $SU (-2,4 %) increases its dividend by 11.43% from €3.50 to €3.90

Ex-Date: 13.05.25

Pay day: 15.05.25

The year to date shows that excessive dependency harbors risks. Increasing political uncertainty and high valuations are prompting many investors to look for alternatives. Europe and Asia offer exciting companies that are often valued more favorably and have great long-term potential.

Strong European alternatives for your portfolio:

Adyen $ADYEN (-1,12 %) is a leading payment service provider that is benefiting from increasing digitalization. After a difficult year, the company could get back on track.

Schneider Electric $SU (-2,4 %) from France is a key player in energy and automation technology and is benefiting from electrification and the growing focus on sustainability.

Novo Nordisk $NOVO B (-1,85 %) a classic and dominates the market for diabetes and obesity medication. The strong demand for Wegovy and Co. ensures continuous growth.

ASML $ASML (-1,57 %) is indispensable for the chip industry. Without ASML's machines, there would be no modern semiconductors. A real growth stock for the future.

Lotus Bakeries $LOTB (-1,25 %) is growing worldwide with its popular Biscoff cookies. The expansion into new markets makes the company exciting for long-term investors. More on this in one of my last posts.

Exciting stocks from Asia:

Tokyo Electron $8035 (-1,32 %) is one of the most important suppliers to the semiconductor industry and is benefiting from the global chip boom.

Alibaba $9988 (-1,4 %) remains an e-commerce and cloud giant with long-term potential despite regulatory challenges.

Fast Retailing $9983 (+0,23 %) (Uniqlo) is growing strongly in Asia and could establish itself as a global fashion brand.

The MSCI World ex USA as an alternative for passive investors:

If you want to reduce your US share but do not want to invest in individual stocks, you can use an ETF on the MSCI World ex USA as an alternative. Regular purchases via a savings plan can gradually dilute the US share in the portfolio.

What is your current US share? Are you planning to reallocate or are you still heavily invested in the USA?

#etfs
#stockanalysis
#tech
#dividends
#growth
#usa
#eu
#asien

1st Vinci (DG: SGE) $DG (-1,45 %)

* Quantitative valuation:

* P/E ratio: approx. 12 (6 points)

* P/B ratio: approx. 1.8 (8 points)

* ROE: approx. 12% (6 points)

* Leverage ratio: approx. 0.5 (8 points)

* Dividend yield: approx. 4% (10 points)

* Sales growth: approx. 5% (6 points)

* PEG ratio: approx. 1.5 (6 points)

* Cash flow yield: approx. 7% (6 points)

* Valuation table:

| Metric | Share Value | Reference Values | Share Rating | Weighted Score |

|---|---|---|---|---|

| P/E | 12 | 10-20 (6 points) | 6 | 6 |

| P/E | 1.8 | 1-2 (8 points) | 8 | 8 |

| ROE | 12% | 8-15% (6 points) | 6 | 6 |

| Debt/equity ratio | 0.5 | 0.3-0.6 (8 points) | 8 | 8 |

| Dividend yield | 4% | >4% (10 points) | 10 | 10 |

| Sales growth | 5% | 4-8% (6 points) | 6 | 6 |

| PEG Ratio | 1.5 | 1-2 (6 points) | 6 | 6 |

| Cash flow yield | 7% | 5-10% (6 points) | 6 | 6 |

* Qualitative assessment:

* Market position: 9 points

* Competitive landscape: 7 points

* Management quality: 8 points

2. ABB (DG: ABBN) $ABBNY (-1,18 %)

* Quantitative assessment:

* P/E ratio: approx. 26 (1 point)

* P/B ratio: approx. 3 (1 point)

* ROE: approx. 16% (10 points)

* Leverage ratio: approx. 0.4 (8 points)

* Dividend yield: approx. 2% (1 point)

* Sales growth: approx. 6% (6 points)

* PEG ratio: approx. 2.2 (1 point)

* Cash flow yield: approx. 5% (6 points)

* Valuation table:

| Metric | Share Value | Reference Values | Share Rating | Weighted Score |

|---|---|---|---|---|

| P/E | 26 | >20 (1 point) | 1 | 1 |

| P/B ratio | 3 | >2 (1 point) | 1 | 1 |

| ROE | 16% | >15% (10 points) | 10 | 10 |

| Leverage ratio | 0.4 | 0.3-0.6 (8 points) | 8 | 8 |

| Dividend yield | 2% | <2% (1 Punkt) | 1 | 1 |

| Umsatzwachstum | 6% | 4-8% (6 Punkte) | 6 | 6 |

| PEG Ratio | 2,2 | >2 (1 point) | 1 | 1 |

| Cash flow yield | 5% | 5-10% (6 points) | 6 | 6 |

* Qualitative assessment:

* Market position: 9 points

* Competitive landscape: 8 points

* Management quality: 9 points

3rd Randstad (DG: RAND) $RAND (-1,23 %)

* Quantitative assessment:

* P/E ratio: approx. 10 (10 points)

* P/B ratio: approx. 1.5 (8 points)

* ROE: approx. 13% (6 points)

* Debt-equity ratio: approx. 0.5 (8 points)

* Dividend yield: approx. 4% (10 points)

* Sales growth: approx. 4% (6 points)

* PEG ratio: approx. 1.3 (6 points)

* Cash flow yield: approx. 8% (6 points)

* Valuation table:

| Metric | Share Value | Reference Values | Share Rating | Weighted Score |

|---|---|---|---|---|

| P/E | 10 | <10 (10 Punkte) | 10 | 10 |

| KBV | 1,5 | 1-2 (8 Punkte) | 8 | 8 |

| ROE | 13% | 8-15% (6 Punkte) | 6 | 6 |

| Verschuldungsgrad | 0,5 | 0,3-0,6 (8 Punkte) | 8 | 8 |

| Dividendenrendite | 4% | >4% (10 points) | 10 | 10 |

| Sales growth | 4% | 4-8% (6 points) | 6 | 6 |

| PEG Ratio | 1.3 | 1-2 (6 points) | 6 | 6 |

| Cash flow yield | 8% | 5-10% (6 points) | 6 | 6 |

* Qualitative assessment:

* Market position: 8 points

* Competitive landscape: 6 points

* Management quality: 8 points

4th Schneider Electric (DG: SU) $SU (-2,4 %)

* Quantitative assessment:

* P/E ratio: approx. 23 (1 point)

* P/B ratio: approx. 3 (1 point)

* ROE: approx. 15% (6 points)

* Leverage ratio: approx. 0.5 (8 points)

* Dividend yield: approx. 2% (1 point)

* Sales growth: approx. 7% (6 points)

* PEG ratio: approx. 2.1 (1 point)

* Cash flow yield: approx. 6% (6 points)

* Valuation table:

| Metric | Share Value | Reference Values | Share Rating | Weighted Score |

|---|---|---|---|---|

| P/E | 23 | >20 (1 point) | 1 | 1 |

| P/B ratio | 3 | >2 (1 point) | 1 | 1 |

| ROE | 15% | 8-15% (6 points) | 6 | 6 |

| Debt/equity ratio | 0.5 | 0.3-0.6 (8 points) | 8 | 8 |

| Dividend yield | 2% | <2% (1 Punkt) | 1 | 1 |

| Umsatzwachstum | 7% | 4-8% (6 Punkte) | 6 | 6 |

| PEG Ratio | 2,1 | >2 (1 point) | 1 | 1 |

| Cash flow yield | 6% | 5-10% (6 points) | 6 | 6 |

* Qualitative assessment:

* Market position: 9 points

* Competitive landscape: 7 points

* Management quality: 9 points

Summary:

* Randstad appears to be the most attractive in quantitative terms due to its low P/E ratio and high dividend yield.

* ABB and Schneider Electric have higher growth and profitability ratios, but are also valued higher.

* Vinci offers a good middle ground.

Randstand and Vinci will therefore move in. Until such time as Swiss shares are tradable throughout the EU again, I am considering whether to add Schneider Electric or ABB.

I wish you a sunny start to the week!

I was inspired by a Focus Money article and because many people here are asking.

I won't be investing myself, it's too short-term for me. But there are still some very interesting companies.

Feel free to write in the comments whether such "copied articles" are of any use to the community or are legally correct :)

The signs of a peace process in Ukraine are solidifying. This is triggering a run on the stock market for shares that could benefit from reconstruction

Regardless of the political interpretation, the stock market has been turning its back on the war for several days now and is betting on the coming peace. Stocks that are likely to benefit from the reconstruction in Ukraine have soared. The UBS Ukraine Reconstruction Index, which comprises 25 of these stocks, has been climbing for days and is at an all-time high. "The effects of a possible ceasefire in Ukraine are still being underestimated on the financial markets," says Bernd Meyer, Chief Investment Strategist and Head of Multi Asset at Berenberg, who is convinced that the rally will continue. Reconstruction requires enormous resources. According to estimates by the World Bank, the costs for this amount to a total of 500 billion dollars - the equivalent of Austria's gross domestic product and more than three times Ukraine's annual economic output before the war. The money is likely to benefit construction companies, suppliers, infrastructure companies and banks in particular. European companies could be the main beneficiaries - especially from neighboring countries such as Poland and Hungary, but also the Czech Republic, Austria and Germany.

With Wärtsilä $WRT1V (-1,43 %) a provider of technologies for the shipping and energy markets, and Konecranes $KCR (-2,32 %) a manufacturer of industrial cranes and drive technology, Finnish companies are also on the list of potential peace beneficiaries - as are Italian companies such as the cement and building materials manufacturer Buzzi $BZU (-0,26 %) The list is long. There is a great need for building materials, steel and cables to restore the destroyed infrastructure and energy supply. There is still no thematic fund or ETF on the beneficiaries of the reconstruction in Ukraine. Investors who want to benefit from this are therefore well advised to combine several securities into a portfolio themselves.

Banks: Erste Group Bank $EBS (-1,6 %) Powszechna K. Osz $PKO (-1,56 %) Santander Polska $SPL (-2,05 %) Polska K. Opieki $PEO (-1,32 %) Raiffeisen Bank Int.$RBI (-0,97 %)

Construction: Wienerberger $WIE (+1,86 %) Sniezka Construction $SKA Strabag $STR (+1,77 %)

Insulation: Kingspan Group $KRX (-1,42 %) Rockwool $ROCK B

Glass: Cie de Saint-Gobain $SGO (-1,58 %)

Cranes: Konecranes $KCR (-2,32 %)

Cement: CRH $CRH (-1,87 %) Buzzi $BZU (-0,26 %) Holcim $HOLN (-0,59 %) Heidelberg Mat. $HEI (+0,41 %)

Construction machinery: Caterpillar $CAT (-1,63 %)

Mining: Ferrexpo $FXPO (+1,05 %) Metso $METSO (-1,48 %)

Chemicals: BASF $BAS (-2,73 %)

Industrial gases: Air Liquide $AI (-0,54 %)

Infrastructure: Schneider Electric $SU (-2,4 %) Rexel $RXL (-1,64 %) Wärtsilä $WRT1V (-1,43 %) Weir Group $WEIR (-0,89 %)

Infrastructure (E): Siemens Energy $ENR (-0,12 %) Prysmian $PRY (-0,04 %) NKT $NKT (+2,35 %) Nexans $NEX (-0,46 %)

Agriculture: Kernel $KER (-3,64 %)

Logistics(warehouse): Kion $KGX (-1,36 %)

Steel: Arcelor Mittal $MT (+0,58 %) and for stainless steels Outukompu $OUT1V (-1,33 %)

Sanitary technology: Geberit $GEBN (+0,06 %)

Specialty chemicals: Evonik $EVK (-1,08 %) Arkema $AKE (-2,16 %) Wacker Chemie $WCH (-1,29 %) Lanxess $LXS (-3,27 %)

Schneider Electric S.A. $SU (-2,4 %)the French competitor to Siemens, posted a strong increase in net profit to 4.27 billion euros in 2024 compared to 4.00 billion euros in the previous year. Sales rose by 6.3 percent to 38.15 billion euros, exceeding analysts' expectations of 4.12 billion euros in profit and 37.65 billion euros in sales.

Particularly noteworthy is the organic growth in the Energy Management division, which increased by 11.5 percent to 31.13 billion euros. This shows that the company is not only performing strongly across the board, but also in important segments.

The dividend is to be increased by 11 percent to 3.90 euros per share. Schneider Electric is planning adjusted organic EBITA growth of 10 to 15 percent for 2025.

What do you think of these figures? Do you think Schneider Electric will continue to grow so strongly? 📈

Graphic: AI generated

The rapid development of AI has triggered a veritable boom in data centers. Companies such as OpenAI and DeepSeek are driving this revolution and the demand for high-performance servers is growing exponentially.

However, the increase in computing power is also accompanied by massive energy consumption, an issue that is leading to global discussions about infrastructure, efficiency and future investments [1].

At the same time, the question arises as to whether there is currently an overinvestment in computing power. The Chinese AI company DeepSeek, for example, has presented a model that works more efficiently than previous large language models (LLMs).

Does this mean that we will soon need less computing power?

Or will the Jevons paradox occur instead, i.e. the effect that more efficient technologies actually increase overall consumption in the long term? [2, 3]

In this article, I will focus on the key developments in the data center sector, the growing demand for energy, regional characteristics, current challenges and potential investment opportunities.

As always, the article is intended to shed light on the background to current events, provide food for thought and give impetus. The stocks mentioned do not, of course, constitute investment advice.

🤖 Data centers: the foundation of the AI revolution

The growing global demand for AI-supported software and digital applications requires powerful data centers. Goldman Sachs analysts forecast that the global demand for power from data centers will increase by 50% by 2027 and by up to 165 % could increase [1].

This chart below forecasts the energy consumption of data centers (in terawatt hours) by 2030, distinguishing between AI- and non-AI-based applications in the US and the rest of the world. Total consumption is expected to rise to over 1,000 TWh by 2030 [4].

Our analysts expect data center power consumption to increase by more than 160% by 2030

Source: [4], primary: Masanet et al. (2020), Cisco, IEA, Goldman Sachs Research

This data shows how AI applications will massively increase energy consumption. The rapid increase in the area of "US AI" and "Rest of world AI" is particularly striking.

The three main reasons for this increase are

• Larger AI models:

New models such as GPT-5 or DeepSeek AI require more and more computing power. Training and operating these models requires trillions of calculations [1].

• Real-time AI applications:

Companies are integrating AI into numerous applications: from search engines to personalized financial and healthcare services.

• Cloud computing & data storage:

As digitalization progresses, the global demand for data storage and cloud services is increasing [1].

Which companies dominate the market?

On the demand side for data centers, large hyperscale cloud providers and other companies are building large language models (LLMs) that are capable of processing and understanding natural language. These models need to be trained on huge amounts of information using power-intensive processors [4].

On the supply side, hyperscale cloud companies, data center operators and asset managers are deploying large amounts of capital to build new high-capacity data centers.

These include, among others:

• Microsoft $MSFT (-1,53 %) : Operator of Azure Cloud and partner of OpenAI
• Alphabet $GOOGL (-2,9 %) : With Google Cloud and DeepMind
• Amazon $AMZN (-1,96 %) : AWS, the world's leading cloud provider
• Meta $META (-2,42 %) : Develops its own AI chips and continues to expand its infrastructure

In addition, specialized data center providers such as Equinix $EQIX (-0,77 %) and Digital Realty $DLR (-0,47 %) as they supply physical infrastructure to the hyperscalers [6].

According to Goldman Sachs Research, demand for data center infrastructure will increasingly outstrip supply in the coming years.

The utilization rate of existing data centers is expected to rise from around 85% in 2023 to more than 95% by the end of 2026. However, the situation is expected to ease from 2027 onwards as new data centers are commissioned and demand growth driven by AI slows down (see chart below) [1].

Goldman Sachs currently estimates that the global power consumption of the data center market is around 55 gigawatts (GW). This is made up of cloud computing workloads (54%), traditional workloads such as email or data storage (32%) and AI (14%) [1].

For the future, analysts predict that electricity demand will increase to 84 GW by 2027. The share of AI is expected to grow to 27%, while the cloud share will fall to 50% and traditional workloads to 23% [1].

By the end of 2030, around 122 gigawatts (GW) of data center capacity will be online.

At this point, I asked myself as a layman how the units mentioned so far are to be understood, in my first graphic I speak of 1,000 TWh of energy consumption of all data centers by 2030 and now here is talk of 122 GW of data center capacity? In order not to go completely beyond the scope of the article, I have added a section at the very end in case some of you also feel like a layman and want to put the "units" into perspective.

... and now on with the article...

One central problem remains:
Where does all the energy come from?

⚡️Energieversorgung: Can the grid keep up?

According to estimates by Goldman Sachs, more than 720 billion US dollars will have to be invested in expanding the power grid worldwide by 2030 in order to supply the new data centers with sufficient energy [1].

Europe in particular, where electricity consumption was expected to decline for many years, is experiencing a veritable "demand shock" [1].

Which energy sources supply data centers?

• Natural gas & battery storage:

Natural gas is seen as a realistic short-term solution to meet continuous demand. It serves as a bridging technology until renewable energy and storage solutions are further developed, as renewable energy is not available around the clock [4].

• Renewable energies:

Wind and solar energy could cover around 80 % of demand in the long term, provided that sufficient storage solutions are integrated [4].

In practice, solar plants run on average only about 6 hours per day, while wind power plants run on average 9 hours per day. There is also a daily volatility in the capacity of these sources, depending on the radiation of the sun and the strength of the wind [4].

The graph shows the fluctuations in capacity factors for wind and solar energy in the USA in 2023. The capacity factor indicates how efficiently an energy source utilizes its maximum output throughout the year.

• Wind energy (light blue line): The highest capacity factors occur in the winter months (Jan-March) and drop significantly in the summer months (Jun-Aug).

• Solar energy (dark blue line): Efficiency rises in the spring (Mar-May) and reaches its maximum in the summer months (Jun-Aug) before falling in the winter (Nov-Dec).

The graph illustrates that wind and solar energy can complement each other seasonally: While wind is more efficient in winter, solar energy provides the highest yields in summer. This shows how important a balanced energy mix is to ensure security of supply.

In addition to finding environmentally friendly energy sources to power data centers, technology providers can reduce emissions intensity through efficiency gains.

The following chart shows the development of the workload and energy consumption of data centers between 2015 and 2023. Although the workload almost tripled, energy consumption remained almost constant until 2019 thanks to efficiency gains. The efficiency gains then slowed down from 2020 onwards.

Source: [4], primary: Masanet et al. (2020), IEA, Cisco, Goldman Sachs Research

This chart supports the discussion on the Jevons paradox (see below). Efficiency gains could be offset or even exceeded in the long term by higher workloads and AI demand. This highlights the need to make data center energy sources more sustainable.

• Nuclear energy:

Meanwhile, governments are also becoming more supportive of nuclear energy on the whole. Switzerland is reconsidering the use of nuclear generators for its electricity supply, while nuclear energy enjoys bipartisan support in the US and the Australian opposition party has put forward plans to introduce nuclear reactors [4].

Participants at the COP28 conference at the end of 2023, an annual summit convened by the United Nations to combat climate change, agreed to triple global nuclear capacity by 2050 [4].

Nuclear energy is considered the ideal option for basic power supply as it provides a reliable and constant supply of energy.

As a result, more and more large tech companies such as Alphabet, Amazon and Microsoft are turning to small modular nuclear power plants (SMRs).

📊 Increasing efficiency & the Jevons paradox

With new technologies such as DeepSeek, AI could work more efficiently in the future. But does greater efficiency automatically mean that less computing power is required?

The Jevons paradox: More efficiency = more consumption?

The Jevons paradox describes the fact that increases in efficiency often do not lead to lower consumption, but to higher consumption overall.

-Example:

In the 19th century, more efficient steam engines did not lead to lower coal consumption; on the contrary, as the machines became cheaper and more versatile, coal consumption actually increased.

With cars: more fuel-efficient engines did not lead to less gasoline consumption, but to people driving more cars.

-Applied to AI:

As AI models become more efficient, the cost per computation decreases. This makes AI applications attractive in even more areas, which in turn leads to a higher overall demand for computing power.

🌎 Regional distribution and global expansion of data center infrastructure

Current distribution: Where are the data centers located today?

Today, most data centers are located in the Asia-Pacific region and North America. Well-known locations are:

North America:

- Northern Virginia

- San Francisco Bay Area

Asia: Beijing

- Beijing

- Shanghai

These regions are characterized by high computing power, intensive data traffic and strong demand from corporate campuses [1].

The chart also shows the historical development of data center capacity by region (North America, APAC, etc.) from 2017 to 2024. The figures illustrate how fast the infrastructure for the AI revolution is growing and underlines why the energy requirements of data centers are increasing so rapidly.

The increase in capacity from around 20 GW in 2017 to almost 60 GW in 2024 shows an enormous growth trend. This correlates directly with the increasing demand for AI applications and cloud computing.

How is supply growing?

Goldman Sachs Research estimates that global data center capacity will increase to around 122 GW by the end of 2030, as mentioned above. The share of hyperscalers and specialized operators will increase from the current 60% to around 70% [1].

• Asia-Pacific:

The largest expansion of data centers has been recorded here in the past ten years.

• North America:

The largest expansion of new data centers is planned in North America over the next five years.

📈 Investment opportunities: Some winners of the AI and data center revolution

US shares e.g.:

• Carrier Global $CARR (-1,85 %) : Precise cooling technology and air conditioning for data centers
• Vertiv Holdings $VRT (-1,17 %) : Specialist in cooling and power solutions specifically for data centers
• Brookfield Renewable Partners $BEP.UN : Leading provider of renewable energy (hydropower, solar, wind) - supply contracts (PPAs) with data centers
• ON Semiconductor $ON (-4,2 %) : Leader in chips for energy efficiency and thermal management. Solutions reduce power consumption in data centers and support AI integration
• Texas Instrumentes $TXN (-4,18 %) : Energy-saving semiconductor products used in data center servers
• Equinix $EQIX (-0,77 %) : Specialized in data center infrastructure
• Digital Realty $DLR (-0,47 %) : Provider of physical infrastructure for data centers
• IBM $IBM (-1,53 %) : Quantum computing technologies that potentially consume less energy and development of energy-efficient AI solutions
• Arista Networks $ANET (-3,5 %) : Specialist in high-speed networking products for data centers
• Nvidia $NVDA (-2,11 %) : Leader in AI GPUs, Leader in AI training market. Best choice for large AI models and data center training
• AMD $AMD (-1,7 %) Competing with Nvidia with its own AI chips, but better positioned in the AI interference market where energy efficiency and cost-effectiveness are key. The interference market will be the next most important market, perhaps even the more important one.
• Broadcom $AVGO (-1,93 %) Profits from network solutions for data centers
• Microsoft $MSFT (-1,53 %) Google $GOOGL (-2,9 %) Amazon $AMZN (-1,96 %) : The big hyperscalers investing heavily in AI and cloud

European stocks e.g.:

• Siemens Energy $ENR (-0,12 %) Important role in modernizing power grids, integrating renewable energies and improving storage solutions for data center reliability
• Schneider Electric $SU (-2,4 %) : Leader in the development of energy management and cooling technology for data centers - specialty in the automation of both systems.
• ASML $ASML (-1,57 %) : Indispensable for modern chip production
• Infineon $IFX (-4,15 %) and STMicroelectronics $STM (-4,87 %) : Leading semiconductor companies with a focus on AI applications
• RWE $RWE (-0,87 %) and Enel $ENEL (-0,68 %) Utilities that are increasingly focusing on renewable energies for data centers

Japanese stocks e.g:

• Daikin Industries $6367 (-0,3 %) World market leader in air conditioning and cooling, offers specialized cooling systems for data centers and AI-supported plant management systems to further increase efficiency
• Tokyo Electron $8035 (-1,32 %) : Important supplier for semiconductor manufacturing
• Mitsubishi Heavy Industries $7011 (+4,15 %) : Works on the development of new nuclear power plants to secure the energy supply

🧠 Conclusion: AI, data centers & energy as the trend of the century?

Although some analysts warn of possible overinvestment, the figures indicate that the demand for computing power and energy for AI data centers will continue to rise sharply.

• Efficiency gains from models such as DeepSeek or new chip technologies could reduce energy consumption per computer, but the Jevons paradox means that overall demand will increase because more efficient systems will be used more often.

The biggest winners are therefore:

• Semiconductor companies: They supply the AI chips needed.
• Data center operators: They build the necessary infrastructure.
• Energy suppliers: They ensure the energy supply for the AI revolution.

In the long term, these companies could be among the biggest beneficiaries of the coming decades.

👨🏽‍💻 How do I position myself?

Personally, I think I am well positioned with the NASDAQ 100 $CSNDX (-1,93 %) (portfolio share of 23%), as the focus is on US technology and growth stocks. The ETF complements my All-World with a stronger weighting in innovative sectors such as AI and cloud computing.

In the near future, I will also take a closer look at Daikin Industrie $6367 (-0,3 %) share in order to increase the exposure to Japan and the share price offers an entry point at first glance.

In addition, AMD $AMD (-1,7 %) has also caught my attention, the reason being its positioning in the aforementioned interference market. Most of the capital is currently flowing into the expansion of new AI models. However, as soon as these become a "commodity" and everyone uses them, most of the capital will probably flow into the interference market (market for the application of AI models).

Furthermore, I have Siemens AG $SIE (-2,45 %) with approx. 2.3% portfolio share (still growing to approx. 4%), which I also see as well positioned for the future for the following reasons (in the context of the article):

Network stability

• Develops technologies for intelligent power grids ("smart grids"), essential for integrating renewable energies into the supply of data centers.

Data center control

• Provides automation and monitoring systems that optimize the energy consumption and efficiency of data centers

Efficient building structure

• The "Smart Infrastructure" division supports data centers with energy-efficient solutions for lighting, air conditioning and building monitoring

Not directly cooling systems, but:

• offers technologies that increase the energy efficiency of cooling systems by optimizing energy flows and data analysis

What is your opinion❓

• Which companies do you have on your radar?
• Is there a threat of overinvestment or are we just at the beginning of a century revolution?

Thanks for reading! 🤝

...Said digression follows after the sources...

__________

Sources:

[1] https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030

[2] "The Coal Question"
http://digamo.free.fr/peart96.pdf

[3] https://de.m.wikipedia.org/wiki/Jevons-Paradoxon

[4] https://www.goldmansachs.com/insights/articles/is-nuclear-energy-the-answer-to-ai-data-centers-power-consumption

[5] https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

[6] https://www.cbre.com/insights/reports/global-data-center-trends-2024

__________

🧭 Digression: on gigawatts and terawatt hours

In order to understand the relationship between the two figures, 122 GW (gigawatts) and 1,000 TWh (terawatt hours), it is important to clarify the units and their meaning:

• 122 GW (gigawatts):

Refers to the current average power capacity that data centers worldwide require to function. Power (measured in GW) describes the amount of energy consumed per second. This is therefore a snapshot of energy requirements.

• 1,000 TWh (terawatt hours):

This is an indication of energy consumption over a certain period of time, in this case one year. It describes how much energy is required in total in 12 months.

The forecast of 1,000 TWh is slightly below the value resulting from the calculation. The graph shows values slightly above 1,000 TWh; according to the calculation based on 122 GW of power capacity, energy consumption should be around 1,069 TWh.

Nevertheless, general reasons for deviations may be as follows:

• Efficiency improvements: Data centers could operate more efficiently through improved cooling, optimized hardware and software and thus consume less energy.
• Peak vs. average consumption: The figure of 122 GW could reflect peak demand, while the actual average annual demand is somewhat lower.
• Adjustments to the model: It is possible that the forecast of 1,000 TWh is conservative and does not take into account all additional loads or regional differences.

This shows how much the demand for data centers and energy will increase due to AI and digitalization by 2030

__________

Podcast episode 72 "Buy High. Sell Low."

Subscribe to the podcast to get nuclear power plants back on the grid in Germany. Inshallah.

00:00:00 20 power stocks for AI: Constellation Energy, Rolls-Royce, Schneider Electric, Siemens Energy, Cameco, Fluor Corporation, Vistra Corp, RWE, GDF Suez, Enel, Flowserve, Uniper, Crane Co, Quanta Services, MasTec, Legrand, Emerson Electric, Eaton Corporation, Uranium Energy, VanEck Uranium and Nuclear Technologies ETF A3D47K

39:30 Watchlist Max: Fluor Corporation, Schneider Electric, Quanta Services, MasTec, Legrand, Eaton Corporation

00:41:00 AMD

01:10:00 Apple

Spotify

https://open.spotify.com/episode/08XzNKA3nuiMlpcz9BYixB?si=qhG3ie7ETXm8O20VPEsp_w

YouTube

https://youtu.be/6olb6fp5AbQ

Apple Podcast

https://podcasts.apple.com/us/podcast/folge-72-20-stromaktien-f%C3%BCr-ki-amd-apple/id1695869891?i=1000684571374

#podcast
#spotify
$SPOT (+1,42 %)
$UEC (+24,46 %)
$CCO (+10,35 %)
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$F1LS34
$CR (-1,32 %)
$LR (-0,88 %)
$STZ (-0,54 %)
$EMR (-0,95 %)
$ETN (-0,9 %)

⬆️⬆️⬆️

- EXANE BNP raises the price target for ALLIANZ SE from EUR 271 to EUR 295. Underperform. $ALV (-1,13 %)

- BARCLAYS raises the target price for AIRBUS from EUR 166 to EUR 200. Overweight. $AIR (-2,96 %)

- UBS raises its price target for SAP from EUR 237 to EUR 283. Buy. $SAP (-2,77 %)

- BERENBERG raises the price target for LVMH from EUR 695 to EUR 720. Buy. $MC (-1,83 %)

- EXANE BNP raises the target price for MUNICH RE from EUR 550 to EUR 560. Outperform. $MUV2 (-2,18 %)

- RBC raises the target price for SIEMENS from EUR 205 to EUR 225. Outperform. $SIE (-2,45 %)

- CITIGROUP raises the price target for STELLANTIS from EUR 12.40 to EUR 13. Neutral. $STLA

- KEPLER CHEUVREUX raises the target price for DOUGLAS from 28.60 EUR to 29.90 EUR. Buy. $DOU (-1,72 %)

- CITIGROUP raises the target price for DWS from EUR 43 to EUR 44.70. Buy. $DWS (-1,49 %)

- CITIGROUP raises the price target for FRAPORT from EUR 62 to EUR 72. Buy. $FRA (-1,1 %)

- UBS upgrades AMADEUS IT from Neutral to Buy and raises target price from EUR 67 to EUR 80. $AMS (-1,12 %)

- DEUTSCHE BANK RESEARCH raises target price for PHILIPS from EUR 25 to EUR 26. Hold. $PHIA (-2,89 %)

- DEUTSCHE BANK RESEARCH raises the target price for MAN GROUP from GBP 2.65 to GBP 2.75. Buy.

- GOLDMAN raises the target price for RIO TINTO from GBP 67 to GBP 73. Buy. $RIO (-0,83 %)

- JEFFERIES raises the price target for SIEMENS ENERGY from EUR 31 to EUR 50. Hold. $ENR (-0,12 %)

- RBC raises the target price for SCHNEIDER ELECTRIC from EUR 195 to EUR 210. $SU (-2,4 %) Underperform.

- EXANE BNP upgrades HANNOVER RÜCK from Neutral to Outperform and raises target price from EUR 265 to EUR 285. $HNR1 (-1,92 %)

⬇️⬇️⬇️

- DEUTSCHE BANK RESEARCH lowers the price target for NOVO NORDISK from DKK 1000 to DKK 900. Buy. $NOVO B (-1,85 %)

- BOFA lowers the target price for RWE from EUR 44 to EUR 42. Buy. $RWE (-0,87 %)

- JPMORGAN lowers the price target for NETFLIX from USD 1010 to USD 1000. Overweight. $NFLX (-1,29 %)

- MORGAN STANLEY lowers the price target for SYMRISE from EUR 137 to EUR 130. Overweight. $SY1 (+0,29 %)

- KEPLER CHEUVREUX lowers the target price for REDCARE PHARMACY from EUR 145 to EUR 138. Hold. $RDC (-1,73 %)

- WARBURG RESEARCH lowers the target price for BECHTLE from EUR 51 to EUR 45. Buy. $BC8 (+0,21 %)

- STIFEL downgrades WACKER CHEMIE from Buy to Hold. $WCH (-1,29 %)

- RBC lowers the price target for DAIMLER TRUCK from EUR 55 to EUR 51. Outperform. $DTG (-2,85 %)

⬆️⬆️⬆️

- BERENBERG raises the price target for SIEMENS from EUR 215 to EUR 245. Buy. $SIE (-2,45 %)

- BERNSTEIN raises the price target for SIEMENS ENERGY from EUR 15 to EUR 22. Underperform. $ENR (-0,12 %)

- JPMORGAN PUTS SARTORIUS ON 'POSITIVE CATALYST WATCH' - 'OVERWEIGHT' $SRT (-1,83 %)

- GOLDMAN raises the price target for FRAPORT from EUR 87 to EUR 90. Buy. $FRA (-1,1 %)

- UBS raises the price target for NORDEA from EUR 145 to EUR 146. Buy. $NDA FI (-2,28 %)

- BERNSTEIN raises the target price for SCHNEIDER ELECTRIC from EUR 275 to EUR 280. Outperform. $SU (-2,4 %)

- UBS raises the target price for WPP from GBP 6.80 to GBP 7.20. Sell. $WPP (+0 %)

- BERNSTEIN raises the price target for ALSTOM from EUR 17 to EUR 24. Market-Perform. $ALO (-1,84 %)

- STIFEL upgrades HERMES from Hold to Buy and raises target price from EUR 2150 to EUR 2560. $RMS (-2,33 %)

- INFINEON +4.2% - 'TOP PICK' OF THE UBS $IFX (-4,15 %)

⬇️⬇️⬇️

- RBC downgrades UNILEVER from Sector-Perform to Underperform and lowers target price from GBP 48 to GBP 40. $ULVR (-0,12 %)

- BERNSTEIN downgrades ABB from Market-Perform to Underperform and lowers price target from CHF 46 to CHF 45. $ABBN (-1,18 %)

- BERNSTEIN downgrades SIGNIFY from Outperform to Market-Perform and lowers price target from EUR 30 to EUR 24. $LIGHT (-1,08 %)

- DEUTSCHE BANK RESEARCH lowers the price target for UMICORE from EUR 10.50 to EUR 10. Hold. $UMICY (+0 %)

- DEUTSCHE BANK RESEARCH lowers the price target for DOCMORRIS from CHF 45 to CHF 25. Hold. $DOCM (-2,79 %)

- BERENBERG lowers the price target for HORNBACH HOLDING from EUR 100 to EUR 94. Buy. $HBH (-1,24 %)

- CITIGROUP downgrades ROLLS-ROYCE from Buy to Neutral. $RR. (+0,6 %)

- JEFFERIES lowers the target price for BHP GROUP from GBP 22.50 to GBP 21.50. Hold. $BHP (+0,65 %)

- JEFFERIES lowers the price target for GLENCORE from GBP 5.50 to GBP 4.50. Buy. $GLEN (-0,22 %)

- JEFFERIES lowers the target price for RIO TINTO from GBP 64 to GBP 60. Buy. $RIO (-0,83 %)

- BERENBERG lowers the target price for NOVO NORDISK from DKK 975 to DKK 725. Hold. $NOVO B (-1,85 %)

Analsyst updates, 06.12.

⬆️⬆️⬆️

• BERNSTEIN raises the price target for SIEMENS from EUR 220 to EUR 227. Outperform. $SIE (-2,45 %)
• JPMORGAN raises the target price for SIEMENS ENERGY from EUR 38.70 to EUR 44. Neutral. $ENR (-0,12 %)
• JEFFERIES upgrades BMW from Hold to Buy and raises target price from EUR 80 to EUR 85. $BMW (-3,43 %)
• ODDO BHF raises the price target for AURUBIS from EUR 70 to EUR 76. Neutral. $NDA (+0,32 %)
• UBS raises target price for AUTO1 from EUR 9.80 to EUR 20.50. Buy. $AG1 (-1,04 %)
• UBS raises the target price for NORDEA from SEK 144 to SEK 145. Buy. $NDA FI (-2,28 %)
• DEUTSCHE BANK RESEARCH raises the price target for FREENET from EUR 34 to EUR 36. Buy. $FNTN (-1,48 %)
• DEUTSCHE BANK RESEARCH raises the target price for DS SMITH from GBP 4 to GBP 5.80. Hold. $SMDS
• JPMORGAN raises the price target for THYSSENKRUPP from EUR 3.80 to EUR 4.10. Neutral. $TKA (-0,23 %)
• JPMORGAN raises the target price for SALZGITTER from EUR 11.50 to EUR 14.10. Underweight. $SZG (-6,58 %)
• JPMORGAN raises the price target for SCHNEIDER ELECTRIC from EUR 270 to EUR 275. Overweight. $SU (-2,4 %)
• JPMORGAN raises the price target for KNORR-BREMSE from EUR 88 to EUR 92. Overweight. $KBX (-1,13 %)
• MORGAN STANLEY upgrades HANNOVER RÜCK to Overweight. Target price EUR 292. $HNR1 (-1,92 %)
• JPMORGAN raises the target price for COMMERZBANK from EUR 18.40 to EUR 19.50. Overweight. $CBK (-2,71 %)

⬇️⬇️⬇️

• GOLDMAN lowers the price target for LVMH from EUR 770 to EUR 720. Buy. $MC (-1,83 %)
• MORGAN STANLEY downgrades MUNICH RE to Equal-Weight. Target price 523 EUR. $MUV2 (-2,18 %)
• JEFFERIES downgrades MERCEDES-BENZ from Buy to Hold and lowers target price from EUR 73 to EUR 60. $MBG (-3,61 %)
• ODDO BHF lowers the price target for DELIVERY HERO from EUR 43 to EUR 38. Neutral. $DHER (-1,4 %)
• WARBURG RESEARCH lowers the price target for COMPUGROUP from EUR 31 to EUR 24.50. Buy. $COP (+0,09 %)
• JPMORGAN lowers the price target for VESTAS from DKK 143 to DKK 123. Neutral. $VWS (-1,79 %)
• JPMORGAN lowers the price target for KION from EUR 44 to EUR 43. Overweight. $KGX (-1,36 %)
• MORGAN STANLEY downgrades ORSTED to Equal-Weight. Target price DKK 480. $ORSTED (+1,73 %)