iShares MSCI Singapore ETF vs NEOS S&P 500 High Income ETF — how do they compare? iShares MSCI Singapore ETF trades at $31.87, while NEOS S&P 500 High Income ETF trades at $53.69. Which is the better fit depends on your goals.
| EWS | SPYI | |
|---|---|---|
Sector | Broad Market / Factor | Income / Options Overlay |
52-Week High | $32.09 | $54.07 |
52-Week Low | $26.47 | $47.98 |
Signals from Pluang's Aura AI — not financial advice
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SPYI trades at $53.66, up 0.19% today, with a bullish technical signal from moving averages. The ETF has surpassed $10 billion in assets under management as of June 2026, driven by strong inflows. Recent dividends include $0.52-$0.54 per share, supporting its high-income appeal. The fund's covered-call strategy aims to deliver monthly distributions while retaining partial upside.
Outlook remains positive due to robust investor demand for income solutions, though risks include potential return of capital and fee impact. The ETF's 12% yield attracts retirees, but tax implications and market volatility require careful consideration. Competition with JEPI highlights the need for strategy differentiation.
Trailing returns across standard periods
Latest headlines on both assets
EWS tracks the MSCI Singapore 25/50 Index, providing targeted exposure to large and mid-cap companies in Singapore. It is heavily weighted toward the financial, industrial, and real estate sectors, serving as a liquid tool for accessing Singapore's stable, dividend-oriented developed economy.
Read more on EWS →SPYI is an actively managed ETF designed to generate high monthly income through a data-driven call option strategy on the S&P 500 Index. Unlike traditional covered call funds that often forfeit significant upside, SPYI utilizes a 'call spread' approach—selling near-the-money calls while buying out-of-the-money calls—to capture a portion of equity appreciation in rising markets. It prioritizes tax efficiency by utilizing Section 1256 contracts and tax-loss harvesting to provide investors with high-yield monthly distributions.
Read more on SPYI →