Tag Archives: Artificial Intelligence

Rocket Internet Post Mortem, SpaceX (again) and the strange Google capital increase

Rocket Internet Post Mortem

Last week I mentioned in the comments on the blog and on Twix that I got some “bad vibes” and decided to liquidate my Rocket Internet position even before the planned SpaceX IPO next week.

There were overall 3 things that kind of spooked me and let me to take the profit (+30%) instead of waiting the one more week. Here are the 3 items:

  1. I mentioned initially, although it was not part of my investment thesis, that there might be a chance of a special dividend. Now it has become clear that there will be no special dividend. However, it also became clear that Rocket Internet intends to limit information flow to shareholders even more in the future which is clearly not positive
  2. SpaceX: Another news item that spooked me was that SpaceX is aggressively pitching via German brokers for German retail investors. German investors had never access to  US IPOs before. Some might find this positive, I find that rather “surprising” and potentially a hint that demand is not high enough for Elon’s appetite.
  3. Another surprising event was the “surprise Capital increase” from Alphabet/Google. Interestingly, this represented the largest capital increase of all time at 85 bn USD but there was only very limited coverage about it in the financial news and mostly about Berkshire’s participation. But more on this later

Overall, I decided that the “easy money” was now made with Rocket internet and I was able to sell at around 25,80 EUR per share, netting a profit of 30% within 5 months, which is clearly one of my better “Special situations” investments.

I am not 100% sure that the share price increase was driven by SpaceX, maybe the rapid increase in the value of the Kalshi stake helped as well. I am not sure if there are a lot of other “plays” to benefit from KalshI’s incredible growth.

One could argue that I left some upside on the table here but the success of this investment is almost 100% depending for some time on someone else paying me more for the shares that I paid for, which is something I don’t feel too comfortable for a special situation investment.

Overall, I was clearly lucky with the timing on this one.

2. More SpaceX thoughts: Hyperliquid Perps and Damodaran

Since I wrote my update on Rocket Internet and SpaceX a few days ago, quite some things happened.

As mentioned above, we now know that Elon loves Germany so much that at the time of writing, German retail investors can now access this IPO via 8 or 10 different retail brokers.

Interestingly, SpaceX kind of already trades in a synthetic for as a “perpetual future” on a crypto exchange called Hyperliquid:

According to some sources, in order to compare apples to apples, one would need to discount the price by 10% to make it comparable to the actual SpaceX shares. That means on this “grey market”, a synthetic SpaceX share only trades at ~153 USD, above the 135 USD “sticker price” but inside the 135-162 USD bookbuilding range.

Although no one knows for sure if this has any relevance, it is at least a reference point and it seems to be traded quite liquid.

Another interesting source is the attempt of a valuation by Prof. Damodaran. What I like about Damodaran is that he at leasts tries to put values on these kind of situations and is very transparent with his assumptions. I know most tech bros laugh about these attempts but I think avery serious investor should read what Damodaran writes because there is always a lot to learn.

In a nutshell, Damodaran values SpaceX at about 100 USD per share. The ain changes to his initial, pre prospectus valuation is that he increased the margins for the Space and Starlink business, but significantly decreased the expected margins for the AI business.

My biggest shift is in my estimated target margin is for the AI business, where the dynamics that are pushing gross margins down, i.e., increased competition and high costs of delivering AI services, will persist; my estimated operating margin drops from 45% to 25%.

Damodaran is also smart enough to mention that in the first days after the IPO, valuation clearly doesn’t matter at all. But within the first 12 months or so, even for SpaceX, reality will need to be met somehow.

For me however the main take  away is the significantly reduced margins for the AI business which leads me to the:

Surprising 85 bn USD Capital increase of Alphabet

Being a Corporate Finance/Treasury guy by training, the news that Alphabet is raising 85 bn USD via a capital increase really surprised me.

The “package” itself is quite complex. After announcing initially 80 bn USD in total proceeds, Alphabet ended up with ~85 bn.

According to the FT, this is the largest capital increase in the history of capital markets, the second largest was Petrobras in 2010 at around 70bn.

The financial press focused mainly on the 10 bn stake that Berkshire Hathaway took as part of the package. To be honest, this is a very small amount of money for Berkshire’s current size. It is also hard to really judge how good of an investor Greg Abel actually is.

The interesting thing about this capital increase is that so far, at least in the ~40 years that I follow stock markets, capital increases in size only occurred in the following situations:

  1. Primary share portion in an IPO
  2. Emergency capital raising in a crisis ( e.g. Banks in the GFC)
  3. Major M&A transaction where the acquiring company pays with new shares (Paramount)

In Google’s case, clearly none of the three situations applies. According to TIKR, Alphabet still has net cash despite ~100 bn in bonds outstanding. So in theory they could issue a lot more debt. 

I heard the argument that Equity is “cheaper” than debt as the interest rate on a debt offering would be 5% whereas the “earnings yield” at the current 30x P/E is “only” 3,3%. However this does not reflect the tax shield from interest and especially not the fact that Alphabet’s earnings will most likely increase for the foreseeable future and that very soon that “earnings yield” for the issued shares will be much higher than the current 3,3%.

This is the main “justification” of Alphabet for the capital raise besides a 30 bn additional tax bill:

If you read this carefully, it is clear that they could still fund the 2026 Capex more or less with operating cashflow, but already in 2027, they plan to spend much more than that. 

The really interesting thing is clearly: What are their plans beyond 2027 ? My best guess is that they plan with even larger investments that are not offset by operating cash flow. 

But even so, why not wait until 2027 or so when they have a clearer point of view ? And I think here comes something into play which in my old Corporate Finance days was the golden rule of financing: “Raise when you can, not when you must”.

I think the Alphabet guys might have seen SpaceX’s announcement, they know that OpenAI filed for an IPO and that Anthropic will come to the capital markets as well.

As large as the listed capital markets are, there is only so much appetite for capital increases. Maybe they even fear a significant market correction which would require them to issue a much larger number of shares for the same amount of money.

Funnily enough, there were rumours that even Meta seems to think about raising large amounts of capital to fund their AI Capex programs.

One other factor that might also play a role here is that both, Private Credit and Private Equity which have been offering significant amounts of capital so far fight with redemptions themselves and are potentially overallocated to data centres already

To me it is pretty unclear where all this is going. However one thing now is clearer to me: 

The capital required to scale up this technology is larger than even the latest and best funded players like Google expected.

In my opinion, this means that it is very unlikely that we see 5 companies scaling this in parallel on their own (Alphabet, Meta, OpenAi, Anthropic & SpaceX). 1,2 or even 3 of those players might fold at some point in time or would need to collaborate really closely with someone like Microsoft or Apple to stay in the race. Or get help from the Orange guy in some sort.

Scrutinizing Data Centre Infrastructure orderbooks

For ordinary investors this might also mean to better scrutinize order books of companies that are supposed to profit from a further AI build out and trade at high multiples themselves.

At the moment, it is enough if a company releases “AI data centre” contracts to justify sky high multiples. I guess going forward, maybe even sooner than later, one really needs to understand from which counterparts those contracts are. Because not all of them might be actually turn out to be valuable.

In any case, as someone who loves capital markets, this is a great time to be alive and witness what is going on at the moment.

Visibility as a Creator/Writer on LLMs – A test and some thoughts

Visibility on LLMs

Management summary:

This post does not offer any actionable investment content. Rather I wanted to find out if my blog is visible on the various LLMs and if I want to be visible. I would be very interested in how fellow “creators” think about this and how they approach this topic.

Visibility of Value and Opportunity on different LLMs

Just out of interest, I asked several LLMs about the 5 best Investment blogs for European stocks. The results were quite interesting.

Google Gemini for instance distinguishes significantly in which language one asks and which model you use. A German language prompt gives a very different answer (mostly German language Blogs) than an English prompt and “fast” mode gives very different results from “thinking” mode.

Here are the 5 top blogs in Fast mode for the German prompt: (“Welches sind die 5 besten Investment Blogs für Europäische Aktien, insbes. Nebenwerte ? “):

And here the results for the same prompt in “thinking Modus”:

There is some overlap and I am on both of the lists, which is great, but still interesting.

A few days earlier I tried a slightly different prompt (“Nenne mir bitte die 5 besten Investment Blogs die sich mit Europäischen Aktien beschäftigen. “)

And I got very different results:

What is also interesting is that Gemini doesn’t look for Substacks when I ask for blogs. Asking specifically for Substacks, gives once again different top 5 for the fast and thinking model, but the V&O Substack does not appear when asking for Substacks.

When I ask Gemini in English for blogs, I get the following result for “fast” mode:

In Thinking mode, this is the output:

So I show up in both, but the other 4 are different.

Overall it is quite interesting that asking in German language automatically selects mostly German blogs and how much the results differ from fast to thinking mode.

Of course, different LLMs give different answers. The very same German prompt from above  gives this result overview in ChatGPT:

The English prompt gives the following result:

ChatGPT interestingly does not care too much in which language you ask, the overlap is higher than for Gemini. But it has remembered my 10 factor Scoring model and without asking has somehow mixed that into the decision.

Claude interestingly doesn’t seem to know my blog at all. I have to say I am disappointed 😉

The LLMs know Value and Opportunity

So after putting out content for 15 years, Gemini and ChatGPT LLMs clearly know about my blog, but it is really interesting how differently they answer to the very same questions. Also that language plays such a role for the results is kind of interesting for me.

Interestingly, if I use the normal Google search, my blog is not visible at all, at least not on the first 10 pages, irrespective of what kind of searches I do. This mirrors  a little bit the traffic statistics form my WordPress overview where Google as a source for traffic more or les disappeared a few years ago. Only when I ask for a certain analysis, for instance Eurokai specifically on the Value & Opportunity blog, I see my blog in the results. Otherwise no chance.

I have to admit that I have also become quite lazy to add a lot of Keywords etc but in general, Google search as such seems not to be “my friend” anymore. Some years ago, especially the more general articles received significant traffic, even years after I wrote them, but that has gone totally away.

How to optimize for LLM visibility  ?

I feel very lucky that I don’t have to optimize for traffic, otherwise I could imagine that trying to optimize LLMs is not so easy. I have briefly researched the topic and it seems that for now, LLMs seem to emphasize a longer track record and credibility.

One of the nice things is that one can ask the LLm to explain. Google Gemini’s answer is quite flattering I have to admit:

If I wanted to make more advertising for my work, I would basically copy& paste that answer.

Of course, I also wanted to know why I don’t appear on Claude’s list. This is what Claude tells me:

Typically for an LLM, it apologizes. What I find interesting is that Claude indeed seems to start looking in high traffic locations and then doesn’t go much further.

Do you actually want to be visible to LLMs ?

One question one has to ask is of course as a writer & creator: Do you want to be (fully) visible to LLMs or not ?

Despite my visibility on Gemini and ChatGPT, the LLMs do not refer a lot of traffic back to the site. I can see Gemini with a little traffic and ChatGPT with no referrals at all. So they know about the blog, but they don’t refer a lot of people to the blog. Maybe the answers are already good enough if my content gets shown. Outside my Email list, most traffic still comes from Google search and TwiX.

If you want to monetize your content directly, it is clearly not good when LLMs can read your stuff and summarize it perfectly. I was for instance quite astonished when a TwiX user asked Grok to summarize my Biontech post in TwiX and Grok did so with a pretty decent summary.

On the other hand it seems that at least for Gemini and ChatGPT, you need to show them your content in order to get recognized. I guess a good compromise could be to show some of the content so that the AI can learn about what one writes but then keep newer stuff behind a paywall or so.

Another strategy would be, not to share anything on the web in order to protect one’s “intellectual property”. As for now, the LLMs don’t give a lot of traffic back, so why should you be visible at all ?

In my case, I am lucky that (so far) I can monetize my content very indirectly.

For me, the main payoff comes through constructive feedback and, every now and then a nice email from a reader or even better, some personal contact and someone says “I read your blogs for x years and really like it”.

My other goal is also“make the world a little bit of a better place” by maybe teaching some people how to “invest” instead of just “gambling” blindly and help them to hopefully better secure their financial future. For this goal, getting my content “indirectly” distributed through LLMs is clearly helpful.

If someone asks if xyz-Shitco is a good investment and somehow in Gemini’s neural net it identifies a  “red flag” that it has maybe learned through my posts, this could be a very powerful “amplifier”. But this is clearly hard to measure.

Summary:

For now, I am quite flattered, that 2 out of 3 LLMs find my content good enough to put me into the Top 5 European Small Cap blogs. That is clearly niceclearly a nice feedback. 

Most of all, I feel very lucky that I don’t have to directly monetize my content. I think this will be less straightforwardstraight forward than in the “search machine age”. There will be some solutions for sure but I guess “cause and effect” might be less linear than in the old times.

I would be very interested in how fellow “creators” think about this and how they approach this topic.

Some thoughts on Vibe Coding, SaaS vs AI (10 Moats) and Guidewire Software

Executive Summary:

This post does not contain any actionable investment advice but rather some personal ramblings on Vibe coding and the attempt to analyze a specific Software company (Guidewire) according to a Template of 10 Moats for Software companies and their vulnerability to the AI threat.

Introduction:

My track record as a Software investor is to put it mildly, very poor. My best Software Investment so far is Chapters Group which I bought as a net-net before it even became a VMS Serial Acquirer. My blog and portfolio archive also tell me that I sold Microsoft in 2011 at ~25$ per share with a 4% gain because I thought that the Office products had no future. So please take everything I say about Software with a grain of salt or even better, just ignore it.

I do have a background in Software development. Although I would not call it Software development but “Code butchering”. It started as a teenager on a C64 with Basic and Assembler and ended in the late 1990s with Cobol/PLSQL working for a large US Consulting Company (yes, I was young and needed the money). Knowing the speed of financial institutions, I would not be surprised if some of my Spaghetti code would still be running somewhere….

Why am I saying this ? Because of course, Software stocks have been doing quite poorly over the past weeks/months. In addition, I also had the opportunity to play around with Claude Code first hand. 

Random ramblings on AI

You didn’t ask for it but you get it nevertheless: Some random thoughts on various aspects of Artificial Intelligence. Spoiler: No actionable insights (I think).

Gemini 3.0. vs. Nvidia

Google Gemini 3.0 seems to be a really good model. I am currently using it with my prompts and it seems a little bit better but not that much.  NotebookLM seems to have improved a lot.

However, according to various sources, the model was trained and runs exclusively on Google TPU chips. The Nvidia Bulls keep saying that Nvidia has such a large advantage including their software, that those ultrafat margins will persist for many years as there is no alternative. I am not so sure about this. 

This is the EBIT margin development of NVIDIA since 2002:

Read more

Some thoughts on DeepSeek- The Black Swan for MAG7 or something else ?

For various reasons, I was able to spend much more time on this topic since Sunday than I would usually have. On Sunday morning, the topic somehow picked my interested and I have been trying to understand as a Non-Expert what is going on here.

For full disclosure: I have no positions in any of the MAG7 stocks, but that might make me equally biased than someone who has mortgaged his family home to invest in NVDIA.

On Sunday Morning, I initially used mostly Twitter, but during the day this was overflooded with MAGA Crap. Twitter is still a good place at an early stage for “virally developing situations”, bit it gets washed with (AI written) turd pretty quickly.

The DeepSeek topic is interesting on many dimensions. Here are some facts (taken from Wikipedia, but confirmed by other sources):

Read more