Semiconductors

Sector thesis

Semiconductors are the tiny chips that power everything from your phone to data centers. They're the physical foundation of computing—without them, there's no AI, no cloud, no modern electronics. Right now, the sector is riding a massive wave: AI training and inference require enormous computational power, and that power comes from specialized chips. This isn't hype; it's structural. Every major tech company is building out AI infrastructure, and that infrastructure runs on semiconductors. Within semiconductors, there are three main buckets worth understanding. First, there's AI compute chips—the high-end processors designed specifically for training large language models and running AI workloads. Second, there's memory (RAM and storage chips), which AI systems consume in huge quantities. Third, there's the broader chip ecosystem: older, mature chips that power cars, industrial equipment, and consumer devices. That third bucket is less glamorous but often more stable. The biggest risks are real. Chip manufacturing is capital-intensive and cyclical—companies spend billions on factories, and if demand softens, they're stuck with excess capacity. Competition is fierce, especially from international players. Supply chains are fragile. And valuations in this space can get stretched; investors sometimes price in years of growth upfront, leaving little room for disappointment. For a retail portfolio, semiconductors aren't a "buy and forget" play. Watch for quarterly earnings reports—specifically, whether companies are actually selling the chips they're making, or just building inventory. Pay attention to gross margins (the percentage of revenue left after manufacturing costs). If margins are shrinking, that's a warning sign. Consider whether you want exposure through a diversified chip maker or a more focused AI-chip specialist. This sector rewards patience and discipline, not FOMO.