Hedge funds are struggling due to AI supposedly making markets more efficient, “AI is making hedge funds unable to hedge:”
The 12-month correlation between composite hedge funds and the S&P 500 is 0.955, at the 99th percentile of historical readings. Multi-strategy hedge funds show a 0.819 correlation, also near a record high at the 98th percentile.
That means hedge fund returns are tracking the broader market far more closely than usual, offering their investors less diversification.
The funny thing is, I am having an easier time than ever hedging. Despite being a unknown/random blogger, I found the best hedging strategy out there, that of course being shorting Bitcoin, which despite the method being made public, works better than ever. I had observed that Bitcoin tended to be extremely weak and sensitive to bad news–e.g. tariffs, China, or Middle East–but not participate as much on the upside, leading to a divergence where Bitcoin severely lags tech stocks. So this was in Summer 2025, and no one else had been doing this. People widely assumed Trump would get the reserve funded, and Bitcoin would go to $140k+. But he instead dropped the ball big time.
Here are the receipts. For example, a month ago on /r/quant, I disclosed method. The thread got 70 up-votes, as people found it interesting and novel. And again a different thread got 48 up-votes, in which I took a victory lap when a year ago warned investors to stay away from Bitcoin and MSTR. At that time, 8-12 months ago, it was widely assumed Bitcoin and MicroStrategy would perform well under Trump; to the contrary, they are down 8% and 40% respectively over the past year versus QQQ being up 19%–a massive divergence or underperformance on the part of Bitcoin.
But wouldn’t I be worried that disclosing the method on Reddit would make it less effective? No, because the system tells you what will happen. Even though I had shared the method months ago on Reddit, that hasn’t hurt its effectiveness. Disclosure may hasten the outcome, but doesn’t change it. A famous short-seller who publishes a report about a company which unbeknownst to investors is concealing a major fraud, does not change the existence of the fraud, but it will hasten the fraud being revealed and the stock falling.
My disclosing it does not change the fact that capital will continue flowing out of crypto and into AI and other ‘big tech’ (e.g. Google), and that there will be no Bitcoin reserve under Trump. In other instances, like algorithmic trading, where you’re looking for tiny and brief inefficiencies in markets and competing with other traders, then disclosing is a bad idea.
Here is the flow:
System:
-AI is everything, and is the most important technology now.
-Capital flows into AI and ‘big tech’, which have pivoted to AI. The biggest of tech companies, such as Meta, Microsoft, and Alphabet, are also effectively AI companies.
-Capital flows out of crypto.
Secondary consequences:
-Trump and Wall St. defect on crypto, and are now 100-percent behind AI.
-No Bitcoin reserve, as I correctly predicted.
-‘Big tech’ stocks; e.g. QQQ, outperform Bitcoin.
-Bitcoin crashes despite bull market in QQQ.
-Predictions of ‘AI being a bubble’ keep being wrong.
Investing strategy:
-Short Bitcoin as a hedge.
-Invest in QQQ & private AI companies.
Despite AI, it’s the same patterns over and over. To quote the meme, nothing ever happens. A theme of the blog is that patterns and trends tend to be much more persistent than commonly assumed. People assume that alpha is quickly eroded as patterns become known to the public and are exploited, but this can take a surprisingly long time, even when the methods are disclosed.
This makes sense when you think about it , as the assumption that trends must be quickly mean-revert also implies markets are not efficient. Under an actually efficient market, short-term mean reversion cannot always be taken for granted. The irony of invoking efficient markets to justify the unsustainably of alpha , implies market inefficiency.
A theme of the blog is that trends reflect an underlying system. Knowing the system means you can predict trends to a high degree of accuracy; to outsiders it may be like being psychic. Because systems, by definition, are slow to change, trends can last much longer than often assumed by the media or others, such as why AI valuations refuse to fall despite the insistence of its unsustainably or a bubble by the media.
Or why my method of shorting Bitcoin to hedge the stock market is still so effective despite it being public, defying saturation. If the system dictates that AI and tech stocks are the future and that crypto is obsolete, then there is no reason to expect this to change anytime soon.
Systems-based approaches will always be superior compared to ‘more experience’ or ‘better credentials’. The herd assumed trump would save bitcoin, and that bitcoin was too risky to short.
Capital flows and optimal allocation will always beat AI. No matter how advanced AI becomes or how much money is spent on AI, capital will always seek a path of optimal allocation, much like conservation of energy or other immutable laws of the universe. This means money flowing out of inferior assets and into superior ones.
As long as you can know which assets will be marked as inferior vs superior you can profit big by shorting the former as a hedge against the latter. So how does one know without having to be psychic? This is where the systems-based approach comes into play. The system tells you where the capital will be allocated. So I had the superior system of knowing that money would flow out of crypto and into AI , and I knew Trump would delay on the Bitcoin reserve, and has now dropped the ball on it entirely. Those factors would cause it to be inferior, hence underperform.
The may sound circular or arbitrary. There is no avoiding some guesswork in terms of knowing the right system, but the
point is, AI cannot override capital flows. Even if AI leads to a post-scarcity economy and boosts productivity massively, such flows will still exist. This could be between competing super-intelligent AGIs optimizing capital allocations in some entirely digital economy.
This is where smart people are still useful , by anticipating these flows. I, for example, was the lone voice in late 2024 and early 2025 who l predicted that trump would not follow through on any of the crypto stuff. The widespread assumption was he would waste little time, but I correctly predicted indefinite delay. I knew this because I had the right system. Everyone was getting bad info or mislead. They were running on outdated system software.
A lot of people cynically assumed Trump was for sale or would easily sellout to crypto donor interests. But if politics is cynical, why would trump keep his end of the bargain and honor donors’ wishes? A maximally-cynical outcome is donors try to buyout Trump, and then Trump does nothing and keeps the money.
By applying my systems-based approach by having a superior understanding of politics and ‘money flows’, I took the opposite/contrarian position and profited. The better model or system will always win. If you know what will happen by being a few steps ahead, you cannot fail.