Investors Favor Bonds as Buffer ETFs Gain Interest

Panelists at a Goldman Sachs Asset Management media event in New York on May 27 described a gap between corporate results and investor behavior. First-quarter earnings increased 28% overall and 14% when excluding large technology firms, but most new fund flows have gone into fixed income and cash equivalents rather than equities.

Greg Calnon, head of public investing at Goldman Sachs Asset Management, said roughly 90% of companies had reported results for the quarter. He noted non-tech sectors posted their strongest earnings growth in a decade and cited inflation, oil prices and shifting Federal Reserve rate expectations as factors that have kept some investors cautious.

Graham Day, president of Innovator ETFs, reported flow data showing that for every $16 moving into ETFs and mutual funds, about $15 has been allocated to bond and money-market funds, leaving roughly $1 for equities. He also referenced survey findings that 80% of ultra-high-net-worth investors express a desire for risk management while only 8% believe their advisors deliver it.

Panelists discussed buffer ETFs as a strategy advisors are using with risk-averse clients. These products offer defined downside protection over a set outcome period, with typical buffer levels in the range of about 9% to 20% depending on the product and term. The structure allows a clear, stated limit on potential losses during an outcome period, a characteristic panelists contrasted with traditional 60/40 portfolios.

Day pointed to an RIA in Southern California that increased assets under management from $200 million to $400 million after incorporating buffer strategies and focusing client conversations on preservation. He also noted that bonds did not provide the expected hedge in 2022, when both stocks and bonds fell at the same time.

Osman Ali, global co-head of quantitative investment strategies at GSAM, described the firm’s long-running use of artificial intelligence tools to analyze investment information, including pattern recognition and content extraction. He cautioned that AI analysis requires well-structured inputs: “You have to have data, and not just data, but data that’s been cleaned and curated and modeled in a way that the AI can analyze.”

Calnon added that advisors now have more portfolio construction tools than in the past decade and that many are moving beyond a simple split of stocks, bonds and cash. Panelists said buffer ETFs provide a measurable option for advisors working with clients who remain heavily allocated to cash and fixed income despite stronger corporate earnings.