Pump and Circumstance

Picks and Shovels

Soundbite: The AI capex story continues to show up in our rankings, but not where the cocktail-chatter version puts it. The sector-level Technology overweight is real, but a sharper read points to the supply chain that gets built before a single training run happens: semiconductor manufacturing capital equipment, power generation products, interconnect components, and commercial and industrial electric products. These industries do not lead the headlines, but they sit at the top of our 12-month return distribution by a wide margin.

From an industry perspective, Semiconductor Manufacturing Capital Equipment posts a median 12-month return of 122 percent in our universe, Semiconductor Manufacturing Services 96 percent, Power Generation and Support Products 75 percent, Commercial and Industrial Electric Products 61 percent, and Interconnect Electronic Components 57 percent. The leadership is not centered on mega-cap AI names, but to the upstream supply chain feeding the buildout. The rankings are favoring the firms whose order books are full because someone else is committing capital.

The geographic dimension reinforces the read. Among countries with at least 200 names in our universe, Taiwan, Canada, Israel, Italy, Sweden, and South Korea sit at the top of the average rankings, most of them representing either upstream hardware or commodity-leverage exporters. South Korea is the standout cluster as our Finance scores carry a median 12-month return of 116 percent, Industrials 99 percent, and Technology 73 percent within the country. That breadth is unusual and points to country-level demand pull, not just a single-sector run.

Power demand is the bridge between these themes and the prior commentary on data center buildout. Goldman's revised 2030 power demand estimate, which we discussed in earlier works, is showing up in the rankings as Power Generation Products and Commercial Electric Products outperformance. These names sit upstream of both the commodity-cycle trade and AI-narrative trade. They are the part of the buildout that has to physically exist before either thesis converts to revenue.

The implication for our model is that the Technology tilt at the sector level reflects a specific industry pattern beyond the broad AI trade. The names earning their way to the top supply the mega-cap AI stocks that dominate marketing pitches and index weights.

Inflation Beyond the Pump

Soundbite: Fuel prices are not the entire inflation picture, and the model is reading that breadth more emphatically than the energy-versus-tariff framing alone might suggest. Materials, particularly precious and base metal mining, are running hotter in our 12-month return distribution than even oil and gas exploration. The inflation reflation extends well beyond the barrel.

Precious Metal Mining sits at a median 12-month return of 118 percent and Base Metal Mining at 110 percent, both ahead of even Oil and Gas Operations Support Activities at 87 percent and Americas Fossil Fuel Exploration and Production at 56 percent. The commodity tilt is broad. In our country rankings, Canada, Australia, Brazil, and South Africa all sit in the top group, and the Non-Energy Materials sector posts its highest country-level 12-month return in South Africa at 118 percent and Canada at 105 percent.

The bottom of the distribution tells the other half of the inflation story. The five worst-performing industries with at least 50 names are Enterprise Management Software at negative 16 percent median 12-month return, Consumer Data and Services at negative 9 percent, Administrative Services at negative 3 percent, Travel Arrangement and Reservation Services at negative 3 percent, and Information Technology Consulting at negative 2 percent. None of these are obvious losers on the fundamentals. Enterprise Management Software, for example, posts a median seven percent revenue growth rate. They are losers in the rankings because the spending that supports them, both corporate IT budgets and discretionary services consumption, is the spending that gets cut first when goods inflation tightens budgets.

The sector-level read carries the same fingerprint. Consumer Cyclicals and Consumer Services are the only sectors with negative average rankings in our universe, and both are overrepresented in our bottom decile relative to their universe weight. The "unit volumes down while dollar volumes hold" gap that the inflation framing calls out is exactly what the bottom of the distribution is pricing ahead of the prints.

The result is a market that has rerated up on the visible commodity inflation channel and rerated down on the invisible spending-power channel. Both are inflation. The rankings are reading both, and the leadership pattern is consistent with the macro thesis rather than against it.

Where the Multiple Is Doing the Work

Soundbite: India is the cleanest single-market proxy for the rerating risk that a discount-rate move would crystallize. Among the major country markets, India shows the highest median return on equity at 14.4 percent and the highest median revenue growth at 8.2 percent, both meaningfully ahead of the United States at 9.0 and 0.1 percent and of Germany at 7.4 and 0.0 percent. India also trades at a median PE of 30.6, the highest in our country universe and roughly double the United States median of 15.4. Yet after all of that, India's median 12-month equity return in the model is zero percent.

Strong fundamentals at a high multiple, in a tape where capital has already exited, is the profile most exposed to the discount-rate compression discussed above. A one percentage point upward move in the 10-year Treasury yields takes 1.33 turns off the broad market PE, a compression that hits high-multiple markets disproportionately. The same dynamic shows up inside the United States within Technology and Healthcare, where our within-sector analysis finds essentially no relationship between 12-month returns and either return on equity (ROE) or revenue growth.

The numbers behind that statement: within Technology, our model shows 12-month returns correlating to price-to-book at 0.35 and to PE at 0.30, while correlating to revenue growth at negative 0.03 and to ROE at 0.02. Healthcare looks similar, with 12-month returns correlating to price-to-book at 0.35 and to ROE at essentially zero. These are sectors where the multiple is doing the work, and where a discount-rate move would land first. By contrast, within Finance, ROE correlates to 12-month return at 0.21 and PE at 0.19, and within Industrials, ROE correlates at 0.11 and PE at 0.30. There is meaningful fundamental support in those parts of the market.

The flip side of the India observation is Japan, where the country-level ranking sits at negative 0.04 despite a respectable nine percent median ROE and a 17x PE. Switzerland and Australia carry the same pattern, with negative average rankings against fundamentals that do not justify it on the metrics alone. Capital has been moving away from these markets in our universe regardless of what the underlying businesses are delivering.

Reading these three observations together, the rankings are doing what they are designed to do. The leadership tilts toward upstream AI hardware, commodity-leverage exporters, and quality-of-earnings names. The laggards cluster in high-multiple growth markets where the multiple has been carrying the return, and in consumer-discretionary corners where the invisible inflation channel is being priced before the headline numbers confirm it. If the Fed cannot get ahead of the tariff pass-through and yields back up, the rerating compression lands hardest where the model is already underweight.

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By Stephen Evans

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