
April Review - Forged under pressure: AI and structural tailwinds

Horacio Coutino, Multi-asset Strategist
The world breaks everyone, and afterward many are strong at the broken places.
— Ernest Hemingway, A Farewell to Arms, 1929
April delivered the reckoning's mirror image. After March's geopolitically driven repricing, the S&P 500 advanced 10.42% over the month, with nine of eleven sectors in positive territory and Communication Services and Information Technology leading at 18.43% and 17.44%, respectively.
The recovery was concentrated, but it was not accidental. It was the market beginning to discount what Q1 earnings season would shortly confirm, that the AI infrastructure cycle has graduated from narrative to evidence, that hyperscaler capital expenditure plans are being deployed against backlogs that have doubled in a single quarter and that the structural tailwinds beneath the index are sufficient, at least for now, to absorb the energy and tariff cross-currents that defined the prior month.
The Q1 earnings print bears this out. The blended growth rate has accelerated from 13.1% at quarter-end to 27.1% with 62.4% of the index reported, the strongest print since Q4 2021, underpinned by a blended net profit margin of 14.7% that, if it holds, will mark the highest level since FactSet began tracking the metric in 2009. Concentration is real, but so is breadth: 16.4% earnings growth ex-Magnificent Seven. What follows is an attempt to anatomise that resilience, to identify where it remains most exposed and to draw out the emerging themes worth carrying into Q2.
This report will analyse:
- S&P 500 earnings growth and estimates for Q1
- Sectoral revisions for Q1 and net profit margins
- Sector-specific monthly performance for US andEuropean equities
Tento článek je poskytován pouze pro informační účely a neměl by být považován za nabídku nebo výzvu k nákupu nebo prodeji jakýchkoli investic nebo souvisejících služeb, jejichž odkazy se v něm můžou vyskytovat. Obchodování s finančními nástroji je spojeno se značným rizikem ztráty a nemusí být vhodné pro všechny investory. Dřívější produktivita není spolehlivým ukazatelem budoucí produktivity.
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