Roundhill NVDA WeeklyPay ETF vs VNET Group Inc — how do they compare? Roundhill NVDA WeeklyPay ETF trades at $38.55, while VNET Group Inc trades at $7.39 (market cap $2.14B). The key difference: Roundhill NVDA WeeklyPay ETF is trading nearer its 52-week high, VNET Group Inc nearer its low. Which is the better fit depends on your goals.
| NVDW | VNET | |
|---|---|---|
Sector | Income / Options Overlay | Technology |
52-Week High | $52.59 | $14.03 |
52-Week Low | $31.88 | $6.29 |
Market Cap | — | $2.14B |
Enterprise Value | — | $5.29B |
Signals from Pluang's Aura AI — not financial advice
No Aura AI signal available yet.
VNET trades at $7.565, up 1.14% today, with a neutral technical signal. The stock shows mixed fundamentals: revenue grew to $9.95B in 2025, but net losses deepened to -$256.77M. Recent news highlights strategic investor entry and AI-driven data center demand, yet earnings misses and a class action settlement pose concerns. Cash flow remains positive from financing, but profitability metrics like ROE at -43.21% signal challenges.
Outlook is cautious; analyst consensus is 62.5% buy with a 54% upside target, but persistent losses and high debt-to-asset ratio of 50.18% heighten risk. Investors should weigh growth potential from AI expansion against execution and competitive pressures in China's data center market.
Trailing returns across standard periods
NVDW is an actively managed ETF that seeks to provide weekly distributions and returns equal to 1.2 times (120%) the calendar week performance of Nvidia (NVDA) common shares. It combines modest leverage with a high-frequency payout schedule, designed for investors who want amplified exposure to Nvidia alongside a consistent weekly income stream.
Read more on NVDW →VNET Group, formerly 21Vianet, is a leading carrier-neutral data center services provider in China. It operates a dual-core strategy: a large-scale retail business serving over 7,000 enterprise customers and an aggressive wholesale segment (Hyperscale 2.0) designed to meet the high-density power and cooling demands of large-scale AI and cloud platforms.
Read more on VNET →