Hi everyone,

I often read posts here where people ask for feedback, but the story behind them is missing. That’s why today I’d like to share my own portfolio—and my story—in a completely transparent way.

A little about me:

I’m 31 years old and have been active on GQ for quite some time. My current net worth of just under 1.28 million euros is the result of my own hard work. Even as a child, I would occasionally try out potentially profitable business ideas on the side to earn some money—and six years ago, I took the plunge into self-employment.

I now have two companies in different industries. It became clear to me quite early on that I needed a high, recurring active income if I wanted to build up a certain level of wealth, so I left my full-time job fairly early on.

For the next 12 months, I’m planning on a monthly income of approximately 30,000 euros. In addition, I naturally have recurring income, which can fluctuate up or down over the long term.

My goal is to continue growing this wealth prudently so that I can eventually live entirely off the dividends. Currently, for tax reasons, I hold portions of two stocks ($MSFT (+3.85%) and $NOVO B (+0.28%) ) are held as individual positions in my holding account, and the rest is held in my personal account.

My Strategy and the Core of the Portfolio

I follow a classic core-satellite approach. The core—which I intend to use later as a kind of pension substitute—consists of two ETFs: the $HMWO (+0.39%) and the $QQQ. (+0.28%) I’m aware that these two holdings overlap; I continue to contribute to both monthly via a savings plan.

The individual stocks and my problem children

When it comes to individual stocks, I look for a combination of long-term trends and reliable cash flow. On the one hand, I deliberately overweight tech stocks and future classics such as $MSFT (+3.85%) , $GOOGL (+0.58%) , $NVDA (+0.4%) , $META (-3.45%) , $AMZN (+0.13%) and $AAPL (+1.52%) , because I am firmly convinced that these industries will continue to perform well in the coming years.

For my dividend strategy and the necessary cash flow, I’ve invested in quality stocks such as $ALV (+1.32%) , $MUV2, $NOVO B (+0.28%) and $UNH (+0.49%) in my portfolio. This is complemented by classic dividend-paying stocks such as $BATS (-0.92%) , $SIE (+1.49%) , $ARCC (+0.07%) and $O (-0.06%).

But let’s be honest: values like $MPW (+0.03%)
$PYPL (+5.58%) , $BAYN (+1.31%) or gambling $LILM aren’t performing at all as once hoped.

In the crypto sector, $BTC (+0.42%) as the largest holding, along with a small amount of $SOL (+0.64%) and $XRP (-0.24%) the whole thing—in the future, I’ll consolidate everything into the position $BTC (+0.42%) and add a little $4GLD (-0%) to it.

What’s Next

At the end of this month, I’m expecting a large incoming payment of around 50,000 euros. I’d like to split the amount and invest it both in the $HMWO (+0.39%) as well as specifically into my dividend stocks to further strengthen the foundation.

The goal is to reach a portfolio value of 1.5 million by the end of the year.

Feel free to share your thoughts—I look forward to the discussion :-)

Now it's my turn: I unexpectedly and with great momentum broke the 100k€ mark! It was a long journey—6 years—and I hope the next 6 won't take as long.

My PORTFOLIO 2036

Hello, everyone,

I often post my new purchases for my Portfolio 2036 here. To some, it might look like I’m buying stocks here without any rhyme or reason.

But you shouldn’t just see my portfolio as a collection of stocks—rather, as a complete technological ecosystem centered around AI, Physical AI and humanoid robotics.

That’s why today I’d like to try to explain my way of thinking to you a little.

Of course, my portfolio doesn’t cover only this growth area, but in today’s presentation, I’d like to use the technology sector to illustrate a portion of my portfolio and the thinking behind it.

After all, this sector accounts for 50% of my portfolio.

My friends,

I hope you enjoy this weekend reading, and please let me know in the comments if you liked it.

Here, I’m looking at several levels:

Sector

🧠 AI chips NVIDIA

💾 HBM / Memory SK Hynix, Micron

💽 NAND / SSD Kioxia

🤖
Semiconductors / Mixed-Signal & Embedded Systems STMicro

🔬 Chip Testing Advantest

🔌 Power Supply Vicor, Vistra

❄️ Data Center Vertiv, IES Holding

🏢Hyperscaler data centers Itochu

⚡ Decentralized Energy Generac

🌐 PHOTONICS / OPTICAL DATA TRANSMISSION Lumentum

🌐 Fiber Optics Fujikura

🤖 Physical AI / Robotics Kawasaki

🏭 Electronics Manufacturing Kitron, AT&S

🕐 Precision/Timing Frequency Electronic

🧑‍💻 AI Applications Innodata, GFT

🔐 Cybersecurity/Identity Wallix

This is much more diversified than it appears at first glance.

While I do place a strong emphasis on AI and technology—within this megatrend, I focus on very different stages of the value chain.

My 2036 vision would therefore look more like this now:

Phase 1:

AI Training → NVIDIA / HBM / Micron / SK Hynix

Phase 2:

AI Inference → Kioxia / SSD / Networking / Fujikura

Phase 3:

AI Infrastructure → Vertiv / Vicor / Generac / AT&S

Phase 4:

Physical AI → Kawasaki / Advantest / Robotics / Sensors

Phase 5:

AI in the Enterprise → Innodata / GFT / Wallix

And specifically Phases 3–5 could prove more decisive for the portfolio over the next ten years than today’s purely GPU-driven narrative.

That’s why, from a 10-year perspective, I would by no means view Japan as a side bet. On the contrary: Kioxia, Fujikura, and Kawasaki give my portfolio three different long-term options in memory, connectivity, and physical AI.

(@PikaPika0105 )

If these theories pan out, my portfolio could look significantly different in 2036 than it does today—and some of the smaller positions today, in particular, could then have become disproportionately important.

🇯🇵 Kioxia – Memory Is Becoming an AI Infrastructure Theme

Kioxia is an excellent fit alongside Micron and SK Hynix because it covers another aspect of the memory boom: NAND/Flash and SSDs.

The company is now explicitly positioning itself for the next phase of AI: After training comes, increasingly, inference, and Kioxia sees rapidly rising storage demands, particularly in agent-based and physical AI.

Especially interesting for my 10-year horizon:

AI → more data → more storage → more SSDs → more flash capacity.

And Kioxia continues to invest heavily: Together with SanDisk, investments totaling over $31 billion in Japan , including an expansion of 3D flash production.

To me, this is an important addition to my existing semiconductor thesis.

https://www.kioxia-holdings.com/en-jp/news/2026/20260602-1.html?utm_source=chatgpt.com

🔵 Fujikura – perhaps one of the most underrated AI infrastructure plays

Why do I hold a position in Fujikura?

Because as data centers continue to grow larger, data must must be transmitted at extremely high speeds within and between data centers.

And that requires fiber optics.

In March 2026, Fujikura announced plans to invest up to 300 billion yen in additional capacity for fiber optics and optical cables in Japan and the U.S. The goal is to eventually triple production capacity.

In May, among other things, a new plant was opened in Sakura with an 40 billion yen ; production is scheduled to begin in late 2030

https://prtimes.jp/main/html/rd/p/000000182.000056990.html?utm_source=chatgpt.com

In May, among other things, a decision was made to build a new plant in Sakura with an investment of approximately 40 billion yen in investment ; production is scheduled to begin in late 2030.

This fits extremely well into my portfolio:

NVIDIA → Data Center → Vertiv → Vicor → Fujikura → Kioxia

This means I not only own the chips, but also an increasing number of companies in the infrastructure needed for the chips to function at all.

🤖 Kawasaki – this is where things get really exciting in the long term

With Kawasaki, I see a completely different option:

Physical AI + Robotics.

And in 2026, something actually developed here that makes the question of robotics at Kawasaki very interesting.

In May, Kawasaki opened Silicon Valley and is collaborating there with companies including NVIDIA, Microsoft, Analog Devices, and Fujitsu. https://global.kawasaki.com/en/corp/newsroom/news/detail/?f=20260522_8524&utm_source=chatgpt.com

This was followed in July by a partnership with Fujitsu to implement Physical AI in the healthcare sector —for example, autonomous robots for transporting medications and samples in hospitals. https://global.kawasaki.com/en/corp/newsroom/news/detail/?f=20260716_2992&utm_source=chatgpt.com

And the key point:

Kawasaki doesn’t just want to treat Physical AI as a research topic, but explicitly wants to bring it into real-world applications—factories, logistics, hospitals, construction, agriculture, and so on. https://global.kawasaki.com/en/corp/newsroom/news/detail/?f=20260716_2992&utm_source=chatgpt.com

That makes Kawasaki, in my view, an interesting player in the second wave of AI:

🏢 ITOCHU

ITOCHU is now explicitly positioning itself in the hyperscale data center sector as a growth area and investing in the corresponding real estate and infrastructure chain.

https://www.itochu.co.jp/en/business/general/project/12.html?utm_source=chatgpt.com

Even more interesting: ITOCHU cites “Capturing rapidly growing power demand from AI and data centers” as an explicit investment theme. At the same time, the group is expanding its own AI and data capabilities through a Global Tech Center.

ITOCHU

• Hyperscaler Data Centers
• Data Center Real Estate
• Power Supply for AI Data Centers
• Financing & Investment
• Network of Technology Companies

This even results in a rather nice “humanoid system” from my portfolio:

🧠 Brain / AI chips

NVIDIA

💾 Memory

Kioxia, Micron, SK Hynix

🤖 Senses + Motor Skills + Edge AI

ST Microelectronics

👁️ Senses / Sensors

Kawasaki + others

🕐 Nervous System / Timing

Frequency Electronics

🕐 Nervous System Lumentum

🌐 Data Cables

Fujikura

🔬 Quality Control

Advantest

⚡ Power Supply

Vicor, Generac

⚡ Energy Vistra Corp.

🏢 Data Center

ITOCHU, Vertiv

🦾 Body / Robotics

Kawasaki

🏭 Manufacturing & System Integration

Celestica

🏭 Manufacturing / Electronics

Kitron, AT&S

🔐 Identity / Security

Wallix

🤖 AI Applications

Innodata, GFT

And ITOCHU is particularly interestingbecause the company serves as a sort of bridge between several sectors: data centers, energy, real estate, technology, and finance. This also aligns with ITOCHU’s business model, which is based on corporate investments and trading.

🤖 STMicroelectronics = Sensors + Motor Control + Edge AI

I would place ST in a humanoid directly on the head, arms, and joints .

ST itself now lists more than 500 componentsfor humanoids, including MEMS sensors, microcontrollers, motor drivers, power management, and edge AI. Of particular interest are 3D depth sensors, motion/acceleration sensors, and local AI processing.

This means that, for my thesis, ST is not just a traditional semiconductor stock:

ST → Perception → Processing → Motion

🔧 STMicro = “Sensor Technology + Embedded Intelligence + Motor Control”

The key areas are:

• 👁️ Sensors – MEMS, motion, pressure, environmental, and ToF sensors
• 🧠 Microcontrollers & Embedded Processing – STM32 and other MCUs
• ⚡ Power Semiconductors – SiC, Power Management
• 🦾 Motor Control – Control of electric motors and actuators
• 🤖 Edge AI – AI processing directly on the device
• 🚗 Automotive – Very broad range of applications
• 🏭 Industrial – Automation, robotics, and industrial electronics

STMicroelectronics describes its business as a combination of analog, digital, power, and MEMS/sensing.

🌐 Lumentum = optical nervous system

I would describe Lumentum as between the head/data center and the entire body .

Among other things, the company supplies lasers, optical transceivers, and optical circuit switching for AI clusters. Especially with AI data centers getting larger and larger, the optical connection between GPUs, memory, and racks is becoming increasingly important.

https://www.lumentum.com/en/products/data-center?utm_source=chatgpt.com

This is particularly interesting for my portfolio because Lumentum thus covers a different segment than Fujikura:

• Fujikura → fiber optics/cable infrastructure
• 
  Lumentum → optical components/lasers/switching
• 
  NVIDIA → computing power
• 
  Kioxia/Micron/SK Hynix → Storage
• 
  Vertiv/Vicor → Power & cooling

Lumentum itself views 1.6T optics and CPO as important next steps in the development of AI networks.

🏭 Celestica = “Fabrication & System Integration”

In my model, Celestica is essentially the “system integrator” for the AI data center: The company integrates networking, storage, rack integration, power, and cooling. Particularly exciting are the 800G/1.6T networks and the collaboration with AMD on the Helios Rackscale AI platform.

https://www.celestica.com/blog/article/engineering-the-future-of-ai-infrastructure-at-ocp-apac-2026?utm_source=chatgpt.com

For our humanoid, I would therefore describe Celestica as follows:

🏭 Celestica = “Physical Structure & System Integration”

• AI servers/racks → connects the individual components
• Networking → High-speed connections within the AI cluster
• Storage → Data supply to the GPUs
• Power & Cooling → Rack-level integration
• Manufacturing → Builds systems on a large scale
• 1.6T Networking → Infrastructure for the next generation of AI

Particularly interesting for my 10-year thesis: Celestica also has a CPO program with a hyperscaler , with production scheduled to begin in 2027. This means Celestica even overlaps with my Lumentum/Fujikura optics thesis.

And forgive us our heavy foot,

just as we forgive the Sunday drivers.

And lead us not into the green dream of 5 marks per liter,

but deliver us from the eco-tax, the CO2 tax, and Friedrich Schmerz.

Amen

It happened today. An exceptional day on the stock market catapulted my portfolio to 400K euros (self-made) just a few weeks after my 29th birthday. I wanted to share that here.