Generated August 15, 2026.
Figures quoted in this analysis are from its generation date and may lag the live snapshot table above, which always shows the latest data.
Overview
GPIQ and QYLD are both ETFs that hold Nasdaq-100 stocks and sell monthly call options to generate income—but they differ fundamentally in how they run the strategy. GPIQ, launched in late 2023 by Goldman Sachs, targets a 10.12% distribution rate using a proprietary approach with slightly out-of-the-money calls and beta close to 1.0. QYLD, Global X's decade-old fund with $8.23B in assets, tracks the Cboe Nasdaq-100 BuyWrite Index, selling at-the-money calls and delivering an 11.70% distribution rate, though its lower beta of 0.49 signals more capped upside capture.
How they differ
The biggest structural difference is call strike selection and its effect on upside. QYLD writes at-the-money calls tied to a published index methodology, which caps gains but locks in predictable monthly income. GPIQ uses what appears to be a slightly out-of-the-money approach—evidenced by its beta of 1.0964 versus QYLD's 0.49—meaning it retains more upside participation but at the cost of lower premium capture and a 10.12% yield versus QYLD's 11.70%.
Cost of ownership matters too. GPIQ charges 0.29% in expenses, QYLD 0.61%—a 32-basis-point spread that compounds over time, though QYLD's higher yield more than offsets it on a cash-flow basis. QYLD has proven track record: it's been running this strategy since December 2013, with $8.23B in AUM. GPIQ is brand new (October 2023) with $5.37B, so its sustainability under various market conditions remains untested.
Both funds face NAV erosion risk at their stated yields, but QYLD's 11.70% distribution rate is higher relative to typical underlying Nasdaq-100 earnings growth, suggesting a heavier reliance on call premiums and potential capital decline over extended periods.
Who each is best for
GPIQ: Fits investors seeking monthly covered-call income from large-cap tech but willing to accept a lower yield in exchange for modestly higher total-return potential—useful for accounts where some capital appreciation matters alongside regular income.
QYLD: Designed for income-focused investors prioritizing a consistent, above-market monthly distribution and accepting the tradeoff that call caps will limit upside, especially in rallying Nasdaq-100 markets; suits those who've already made peace with capped appreciation.
Key risks to know
- NAV erosion at high distribution rates. QYLD's 11.70% yield substantially exceeds typical Nasdaq-100 dividend and buyback yield (~2%), implying heavy reliance on call premium capture and potential steady NAV decline if realized returns disappoint.
- Call cap limits upside in strong equity rallies. Both funds sacrifice Nasdaq-100 gains above the strike; QYLD's at-the-money strikes will cap gains more severely than GPIQ's higher beta approach, but both underperform the index in directional bull moves.
- Limited track record for GPIQ. Launched October 2023, GPIQ has not yet weathered a full market cycle or significant volatility regime, leaving its premium-collection strategy untested under stress.
- Index assignment and options liquidity. QYLD tracks a formal index (Cboe BuyWrite) and relies on liquid one-month rolling options; any shift in index methodology or a spike in options bid-ask spreads could affect execution quality.
- Nasdaq-100 concentration. Both funds hold identical 100 large-cap tech and growth stocks; overlapping holdings mean similar sector and single-name risk exposure regardless of yield difference.
Bottom line
If you prioritize tested longevity and maximum monthly cash flow, QYLD's established track record and 11.70% yield stand out—but accept that nearly 12% is unlikely to come from underlying index returns alone. If you value slightly more flexibility to participate in Nasdaq rallies while still collecting 10%+ monthly income, GPIQ's lower expense ratio and higher beta offer a different tradeoff, though the fund's newness means less data on how it performs during downturns. Past performance does not predict future results.
AI-generated analysis for educational purposes only. Verify important details independently; past performance does not guarantee future results.