Item #1: Bitcoin dies as ‘Crypto President’ narrative turns into disillusionment. From the WSJ: It Was Supposed to Be Crypto’s Year. Then Came the Crash.
And as Paul Krugman also noted, the Trump trade is unraveling.
Today Bitcoin is still crashing this morning, down 7% while the market is flat or only down a little. In only a month, the entire Trump-Bitcoin narrative has died, just like I predicted.
To the best of my knowledge, I was the lone voice telling people there would be no Bitcoin reserve. The assumption in late 2024 and early 2025 was Trump would bend over backwards for crypto donors, but instead he did nothing but sign an executive order for an unfunded ‘stockpile’. This was in March and no further progress since then. For all practical purposes, it’s dead.
This is also more evidence of those who have the largest followings tend to be wrong. For example, Thomas Lee of Fundstrat Capital, who has 567.7K followers on Twitter, in mid-2025 gave a year-end target of $250k and $12k for Bitcoin and Ethereum, respectively. With only about 30 days left in 2025, neither projection is anywhere close.
Item #2: Everyone keeps predicting an AI bubble (and keeps being wrong):
If it does burst, It will be the most anticipated bubble ever. What everyone missed instead was the crypto bubble. Although the media has long called crypto a bubble, the focus has turned to AI being a bubble instead, which in hindsight was wrong.
Consider four possibilities:
1. AI is a bubble, crypto is a bubble
2. AI is a bubble, crypto is not a bubble
3. AI is a not bubble, crypto is not a bubble
4. AI is a not bubble, crypto is a bubble
The consensus was one of the first three options. I correctly forecasted a crypto bubble, but not an AI bubble. AFIK, I was the only one to choose the fourth quadrant.
These AI bubble predictions are useless or meaningless. Invariably, someone will get it right by chance and call himself a ‘genius’ for having called the top. My own take is the awaited AI collapse will not happen, or it will take much longer than everyone is expecting.
2-3 years from now, we’ll still be seeing the same headlines by the useless media about the ‘inevitable’ AI bubble/collapse that is ‘just around the corner’. As seen with Uber from 2010-2019, Amazon during the early 2000s, or Tesla from 2010-2020, these companies always find ways to raise more money and defy predictions of their demise. People are terrible at predicting this sort of stuff.
Item #3: Trump Genesis Mission:
Just as I predicted: With the signing of the Genesis Mission executive order, Trump is going all-in on AI to boost American competitiveness against China, while crypto gets kicked to the curb. Trump is pragmatic in this sense, not the partisan ideologue portrayed by media. He’s willing to set aside partisan differences to make America a global leader in AI.
Very excited to see this AI for Science Executive Order—the Genesis Mission. The Administration has appropriately ambitious goals here; we may be on the verge of world-changing breakthroughs. Congratulations to all involved! pic.twitter.com/s5zgjAJZNu
— Dean W. Ball (@deanwball) November 24, 2025
The obvious trade is buy tech stocks $QQQ and short Bitcoin, like I been saying. Tech stocks have the full-backing of the POTUS, whereas crypto has been abandoned, mentioned above.
Item #4: From Sebastian Jensen, “Unconditional self-acceptance is impossible”. I especially like this line, “I think this is a massive source of a lot of insecurity: if you are not willing to think of yourself in a negative or positive way, then you cannot think of yourself at all,” but I would change “of yourself” to “for yourself”.
Item #5: From Freddie deBoer, “Was the United States Once a Global Leader in Educational Metrics? Have We Fallen From Those Lofty Heights? No and No”:
Poor math performance by average students made no difference to our scientific and technological advantages; the performance of the most academically gifted and inclined are what matter in the world of high-stakes science and technology. Which is fine.
America dominates when it comes to outliers on the far-right-tail of the ability distribution/bell curve. America sucks up top talent from all over the world, and creates optimal conditions and incentives to turn said talent into economic growth, trillion-dollar tech companies, and high standards of living. This is one of many reasons America is so successful despite a middling ‘national IQ’.
As Freddie notes, the average is weighed down by large populations of low-performing groups, that a century ago would have been excluded from the data. For many of these people, school amounts to little more than daycare. Is this good? Perhaps not, but it beats alternative of these kids being on the streets causing trouble or not learning any skills whatsoever.
Freddie has also correctly noted that today’s blacks outperform blacks from 50+ years ago in terms of absolute academic ability, but relative differences between groups still persist, as all groups have simultaneously seen improvement. The only way to create equality would be to hold back high-performing groups, which is what we’re seeing now with the push to defund gifted education.
When assessing the efficacy of policy, one must take into account counterfactuals and confounders. Both sides get this wrong to varying degrees. Talent is real, and that disparities reflect individual differences of ability. The pursuit of ‘equality of outcomes’ is ill conceived by making society worse off.
Item #6: Weight loss challenge:
First I completed the trading challenge. Given the evidence above and other posts, like having predicted the demise of the Bitcoin-Trump narrative and also creating the Bitcoin hedging method, which no one else had done, it’s incontrovertible that I’m on the short list of the successor to Warren Buffett, Soros, or Jim Simons in terms of skill, or at least in that ballpark (net worth…not so much).
Second, the ‘IQ challenge’. This required producing original math research that meaningfully contributes to the literature. I finished this in mid-2025. I discuss this in more detail here. Cont. [0]
The third challenge is to lose 10-15lbs to get lean. I write a lot about dieting, and having lost a lot of weight earlier, I have some knowledge of this topic. But given the poor literature on dieting success, to be honest, I am not optimistic. This will be much harder mentally than the other two. Even though it’s only 10-15lbs, it gets exponentially harder as more weight is lost. No GLP-1 drugs for now. Why am I mentioning this? Sharing your goals with the public can create a sense of accountability.
Item #7: Calling out “Honest Broker”:
From his October 2025 article “The Bubble Just Burst,” he writes, “But when the market opened this morning, Meta shares dropped more than $80. That’s $200 billion in market cap wiped out in an instant.”
So Mr. “Honest Broker”, it’s dishonest of you to ignore your failed 2022-2023 predictions of Meta as if nothing happened. Meta stock was $100 in December 2022 when his article “How Web Platforms Collapse: The Facebook Case Study” was published. Now it’s at $640. I was correct again in telling people to buy Meta stock in the low $100s and from 2022-2024. In fairness, I didn’t predict the 2022 crash, so I am owning up to that. He should do the same.
The fact he gets so much attention and money despite being wrong about almost everything is proof we don’t live in a meritocracy.
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I had derived analytical techniques to finding and proving identities involving Bloch groups. This represented a new approach that resolved an impasse after the ‘canonical case’ had been exhausted. Basically, there are identities and transformations that are downstream of the canonical case. It also explains why it was so hard to find new results. The cited authors mentioned the difficulty. Finding any was a miracle on my part requiring an entirely new approach, as the known methods had been exhausted.
Similar to my discovery of the best trading strategy without any Wall Street affiliation but as some random blogger, I was able to write this research just by skimming PDFs and thinking through it without a degree or an advisor. Autodidacticism is not unheard of for the humanities, a notable example being Moldbug who in his spare time conceived an entire political philosophy, but it’s rarer to do this with math or physics without producing total crap. It almost never happens.
Another example is Zaharia Burghelea from Romania, who developed novel methods to evaluate challenging integrals and infinite series that wouldn’t otherwise be doable, even with the help of sophisticated computer algebra packages. This agrees with my ‘some guy’ theory. Some of the most interesting discoveries and ideas are from random people online, not people with brands or are well known.