Link Copied!
Back

Expectations, expectations, expectations

It's been a good year for risk assets, but performance across sectors and regions has been highly uneven. Amid the AI boom the market has raised the bar: strong earnings growth is no longer enough to deliver returns, because expectations rule.

José Ignacio Villarroel

José Ignacio Villarroel

2 min read
July 30, 2026

It has been a good year for risk assets. Global equity markets are up more than 8% in dollar terms, the economy has proven remarkably resilient despite the geopolitical noise, and corporate earnings keep growing at an accelerated pace.

However, performance across sectors and regions has been quite uneven. Amid the AI boom, the market seems to have raised the bar, and the winners and losers aren't necessarily the ones you'd have expected.

Consider the industries tied to artificial intelligence. First, the software sector—despite earnings growth of nearly 20% versus last year—has returned -20% so far in 2026. Rising competition and a deteriorating outlook are significant medium-term challenges for these companies, and the market has quickly priced them into its projections.

Meanwhile, hardware and semiconductor companies, essential building blocks for running AI models, have seen their earnings grow 30% and 103% year over year, yet their share prices have risen "only" 26% and 46%, respectively.

Finally, the hyperscalers (cloud-computing providers such as Google and Amazon), which grew their earnings by 28%, are down more than 5% in 2026.

The market seeks to capture future expectations and price them in. Strong earnings growth alone isn't enough to deliver outstanding returns. Companies have kept growing strongly, but the market has already raised the bar—and expectations rule.

Column written by José Ignacio Villarroel for Diario La Segunda.

José Ignacio Villarroel

José Ignacio Villarroel

Founding Partner | Civil Engineer, UC

He previously served as a Senior Strategist at IM Trust. He has 13 years of experience in investment banking, developing financial engineering and asset allocation models.