Fabrinet vs SK Hynix — how do they compare? Fabrinet trades at $491.63 (market cap $17.46B), while SK Hynix trades at $170.74 (market cap $891.31B). The key difference: SK Hynix is far larger — about 51× Fabrinet's market cap, and SK Hynix pays a 0.06% dividend while Fabrinet pays none. Which is the better fit depends on your goals — on Pluang, investors hold Fabrinet for 30 Days and SK Hynix for 10 Days on average.
| FN | SKHY | |
|---|---|---|
Market Cap | $17.46B | $891.31B |
Volume | 1,199,886 | 22,268,296 |
Sector | Technology | Technology |
52-Week High | $746.47 | $198.63 |
52-Week Low | $361.94 | $126.79 |
Typical Hold Time | 30 Days | 10 Days |
Enterprise Value | $16.59B | $841.45B |
Dividend Yield | — | 0.06% |
Signals from Pluang's Aura AI — not financial advice
Fabrinet (FN) trades at $486.8, down 2.25% on the day, amid a mixed technical picture with a bullish moving average signal but overbought RSI levels. Fundamentally, the company shows strong growth with Q2 2026 EPS of $4.10 beating expectations, revenue projected to rise to $4.6B in 2026, and robust profitability metrics including a 21.33% ROE. Recent news highlights surging AI data center demand driving expansion.
The outlook is positive given analyst consensus of a $769.50 price target and 75% buy ratings, though risks include customer concentration and high capital expenditures impacting cash flow. The stock offers exposure to AI infrastructure growth but requires monitoring of execution and competitive pressures.
No Aura AI signal available yet.
Trailing returns across standard periods
What Pluang investors did over the last 30 days
Latest headlines on both assets
Fabrinet provides advanced optical and electromechanical manufacturing services to original equipment manufacturers. It specializes in complex products for telecom, automotive, and medical industries.
Read more on FN →SK hynix is a South Korean semiconductor company that manufactures memory products, including DRAM and NAND flash. Its high-bandwidth memory (HBM) products are designed for high-performance computing and AI applications.
Read more on SKHY →