We published a lot in July.
More than usual, in fact.
But there was a reason for it. One piece of research kept opening the door to the next, and by the end of the month we had travelled from Chinese artificial intelligence to biotechnology, from biotechnology to two new stock recommendations, from China back into portfolio construction, and finally from digital abundance to one of the oldest physical bottlenecks in the world.
The journey was not planned in advance. That is partly what made it interesting.
It began with a question we have been pursuing for several months:
What happens to investment returns when intelligence becomes dramatically cheaper?
July gave us some answers.
China changed the economics
The natural place to begin is The China AI Reset.
The conventional AI debate remains obsessed with which country owns the most powerful model. We became more interested in a different question.
What if China does not need the best model in the world?
What if it only needs intelligence that is capable enough, improving quickly enough and cheap enough to perform an increasing share of economically useful work?
Chinese developers have been operating with less capital and more restricted access to advanced semiconductors than their American counterparts. Instead of stopping progress, those constraints appear to have encouraged a different kind of competition, centred on efficiency and cost.
That has important consequences.
If capable intelligence becomes cheaper, some of the scarcity premiums that defined the first AI boom should eventually come under pressure. At the same time, the businesses buying that intelligence receive a more powerful input at a lower price.
This is the essence of the Abundance Shock.
Value does not disappear when something becomes abundant. It migrates towards whatever remains scarce.
That led us directly into healthcare.
From chips to cures
We had already seen something happening in the market.
In Gold Steps Back. Biotech Steps Forward, our public Leaderboard showed Grail still sitting at the top of our realised winners, Roivant above 200%, and SBIO entering the leading group after a powerful advance.
Soon afterwards, we published The AI Trade May Be Beginning to Migrate From Chips to Cures.
The AI trade may be beginning to migrate from chips to cures.
“I think biotech is about to have a renaissance… ultimately driven by AI.”
Healthcare had been cheap for some time. We first made that case in October 2025. What July brought was something valuation cannot provide on its own: evidence that the market was beginning to care.
Earnings expectations were improving. Relative momentum was turning. Biotechnology had broken out. Large pharmaceutical companies were facing an increasingly important patent cliff, while mergers and acquisitions were accelerating.
Then AI added another dimension.
That became The Intelligence Dividend.
Drug discovery remains one of the most expensive exercises in trial and error in the economy. Choosing the wrong target, molecule or patient population can destroy years of work and enormous amounts of capital.
AI does not need to discover miracle drugs on demand to transform those economics. A modest improvement in target selection, trial design or the ability to abandon bad programmes earlier could create substantial value.
The cost of intelligence is falling while the cost of failure in biology remains extraordinarily high.
That gap caught our attention.
By the time we published When Cheap Starts to Lead, the investment case had moved beyond valuation.
When Cheap Starts to Lead
The market does not reward you for finding something cheap. It rewards you when everyone else is forced to stop ignoring it.
Healthcare was no longer simply inexpensive. Parts of it were beginning to outperform.
That was when Tier Two went looking for companies.
We bought two very different businesses
July’s VMF’s Security Selection added two new positions to the Quality Model Portfolio.
The first was Regeneron, which we explored publicly in The Discovery Machine.
Regeneron has spent years building proprietary biological evidence through millions of sequenced samples linked with clinical and molecular information.
That becomes more interesting as AI gets cheaper.
If excellent algorithms become widely available, the algorithm itself becomes less scarce. The biological data on which it can work does not.
Regeneron therefore offered us a way to own something we think may become increasingly valuable in the next stage of AI: proprietary evidence.
Halozyme offered almost the opposite business model.
In The Royalty Engine, we explained why.
Regeneron must discover medicines. Halozyme can prosper when somebody else already has.
Its delivery technology is licensed to pharmaceutical companies, allowing Halozyme to participate through fees and royalties while its partners carry most of the development and commercial burden.
It is an economic architecture we know well. Altius uses royalties to participate in mines and power projects financed by other companies. Halozyme applies a comparable logic to biotechnology.
So we bought both.
Regeneron gave us the discovery machine.
Halozyme gave us the tollbooth.
And the early results have been encouraging. From the reference prices used when the recommendations entered the paid Model Portfolio on 17 July through 28 August, Regeneron had advanced approximately 17% and Halozyme approximately 35%.
Five weeks proves very little about a long term investment thesis, but it is difficult to complain when the evidence starts arriving quickly.
Stronger conviction did not mean buying more
The China research kept improving during the month.
New model releases added further evidence that Chinese developers were not simply competing by offering inferior intelligence cheaply. They were moving closer to the frontier while preserving attractive economics.
That became The Boom Changes Owners.
There was an obvious portfolio response.
Buy more China.
We didn’t.
The Thesis Strengthens. The Weight Does Not. explains the reason.
The Thesis Strengthens. The Weight Does Not.
The strongest thesis in the room can still be the wrong place for the next dollar.
Alpha Tier already owned MCHI 0.00%↑ , KWEB 0.00%↑, BABA 0.00%↑ and PDD 0.00%↑ , while Alibaba also represented a meaningful underlying exposure inside the ETFs themselves.
A stronger thesis did not change that arithmetic.
There is a difference between becoming more confident that something should be owned and concluding that it should become a larger position. The latter requires the next dollar of capital to offer a better expected return than every alternative available to the portfolio.
We did not think China had crossed that threshold.
The research produced one of the lines that best captures our approach:
Fundamentals tell us what deserves to be owned. Price tells us when conviction deserves more capital.
So we kept the China exposure where it was and followed the scarcity argument somewhere else.
The digital boom meets a physical constraint
Cheap intelligence should encourage more intelligence consumption.
That means more models, more agents, more inference and more automated workflows. Each individual task may become cheaper while the total number of tasks expands enormously.
Eventually, all of that software requires electricity.
And electricity does not scale like software.
That became The Fuel Beneath the Boom.
The uranium thesis was already attractive before AI entered the equation. The existing nuclear fleet consumes more uranium than the world mines each year. New reactors, restarts and life extensions are increasing future demand, while governments increasingly care about the security of the fuel supply itself.
India is contracting uranium for generating capacity that has not yet been built. China has been securing long term supply. Even producer nations are considering strategic inventories.
We increasingly think uranium is beginning to behave less like an ordinary commodity and more like a strategic reserve asset.
Yet while the fundamental argument improved, uranium equities corrected violently.
URNM 0.00%↑ had fallen almost 45%.
Unlike China, this was an opportunity where the portfolio did not already carry substantial concentration. The correction restored the asymmetry we wanted.
Alpha Tier initiated the position.
By 28 August, URNM was approximately 15% above our reference price.
Again, early days. But July’s three new recommendations, HALO 0.00%↑ , REGN 0.00%↑ and URNM 0.00%↑ , had all begun working.
That is what made July particularly satisfying. The research was not only prolific. It was actionable.
And then came the TACO Zone
Running alongside all of this was the macro hypothesis we introduced in June: the market remained vulnerable to a Dovish Shock.
July did its best to disprove it. War returned to the Middle East, oil spiked, Kevin Warsh remained hawkish and Gold and Silver both broke technical support.
Yet other parts of the evidence refused to cooperate with the bearish story.
Bitcoin held. Oil struggled to sustain its geopolitical advance. The market remained heavily positioned for tightening, but the probability distribution began moving slightly away from the most hawkish outcome.
Then long term Treasury yields moved into what we called the TACO Zone.
We explained the idea in The Treasury Yield Signals That Predicted Trump’s Ceasefire.
The Treasury Yield Signals That Predicted Trump’s Ceasefire
This Weekly Update was first published for Tier One subscribers on 25 July 2026.
At sufficiently high long term yields, the pressure spreads into mortgages, equities, fiscal arithmetic and the broader political economy. That creates incentives for Washington to reduce whatever part of the pressure it can influence.
The ceasefire provided the first validation.
Scott Bessent’s subsequent focus on reducing pressure at the long end has made the framework more interesting still.
The Treasury Secretary appears to understand the problem.
Kevin Warsh is not there yet.
We think he will get there in time.
The Dovish Shock was never built around the idea that Warsh suddenly becomes a dove. It requires something much less dramatic. A market priced for further tightening merely has to discover that the tightening it expects may never arrive.
If Bessent has already understood where the pain begins, we suspect the Federal Reserve will eventually have to confront the same reality.
Stay tuned.
Your July reading map
If you want to retrace everything we published publicly from July’s work, this is the order I would use:
July produced a lot of research because the same idea kept travelling.
Cheaper intelligence led us towards proprietary biology. Better healthcare evidence led us into two individual businesses. Stronger China fundamentals tested our willingness to concentrate further. Digital abundance led us back towards scarce electricity and uranium. Rising Treasury yields eventually brought monetary policy and political incentives back into the picture.
The links above give free readers almost the entire intellectual trail.
What they do not fully reproduce is the moment when research becomes a portfolio decision.
That is where VMF Research’s paid publications begin.
And in July, those decisions have already started paying us.
Important Disclosure
This article contains general investment research and market commentary produced by Vasco Marques de Freitas, CFA, CMT, Founder and CEO of VMF Research, Lda. It is provided for informational purposes only and does not constitute personalised investment advice, portfolio management, or a solicitation to buy, sell, subscribe for or hold any financial instrument, security, cryptoasset, commodity exposure, fund, ETF, ETP or other investment product.
The article summarises research published by VMF Research during July 2026 across VMF’s Strategic Asset Allocation, VMF’s Security Selection and Alpha Tier, together with related excerpts subsequently published on VMF’s Market View. References to securities, portfolio allocations and investment decisions are intended to explain VMF Research’s research process and should not be treated as a complete investment thesis or as a substitute for the underlying paid publications, which contain the relevant assumptions, risks, valuation work, sizing considerations and monitoring criteria.
References to the subsequent performance of securities discussed in this article, including Regeneron Pharmaceuticals, Halozyme Therapeutics and the Sprott Uranium Miners ETF, are calculated from the published Model Portfolio reference prices and do not represent client results or transactions executed by VMF Research. Model Portfolios are illustrative research portfolios and do not represent managed accounts or client assets. Reported performance excludes, unless otherwise stated, taxes, transaction costs, custody charges, bid ask spreads and foreign exchange effects. Past performance and Model Portfolio performance are not reliable indicators of future results.
The views expressed are stated as of the publication date and may change without notice as prices, fundamentals, policy expectations or other evidence evolve. Forward-looking statements and hypotheses, including the Dovish Shock and TACO Zone frameworks, are inherently uncertain and may not materialise. All investments involve risk, including the possible loss of capital.
Disclosure of interests: legal entities controlled by the author hold long positions in the KraneShares CSI China Internet ETF and Altius Minerals Corporation, both of which are referenced in this article. Legal entities controlled by the author also hold listed ETPs providing economic exposure to Bitcoin, Ether and Solana. These interests may create actual, potential or perceived conflicts and should be considered when evaluating the analysis. Neither VMF Research nor the author received compensation from any issuer discussed in this article in connection with its preparation.
Readers should conduct their own due diligence and, where appropriate, consult an authorised financial intermediary or other suitably qualified professional before making any investment decision.