A booming $4.9 trillion branch of the U.S. asset management industry is funneling investor cash into funds that are pricier and worse-performing than alternatives, new research claims.
So-called model portfolios—off-the-shelf investment strategies often comprising bundles of ETFs—are ridden with conflicts of interest that undermine one of the hottest and most opaque businesses on Wall Street, a trio of academics argues.
These allocation blueprints, usually created by asset managers and deployed by financial advisers, have exploded in popularity in recent years as easy, one-stop solutions for investors of all stripes.
Yet the firms designing them tend to favor their own exchange-traded funds, Jonathan Brogaard, Nataliya Gerasimova and Ying Liu wrote. And advisers are steering client money to them with seemingly little regard to what that means for performance.
“These affiliated ETFs, on average, have lower past returns and higher fees than unaffiliated funds,” the team said. “We also do not find evidence that the affiliated ETFs provide superior performance after they are recommended.”
These are big claims against a business with ever-growing clout over the billions gushing in and out of ETFs every day. Model portfolio assets have more than doubled over the last five years and Broadridge Financial Solutions projects they can double again to $10 trillion by 2025.
Many providers of models are asset managers, who stand to benefit from new cash flowing to their funds. Meanwhile, financial advisers have embraced them as a way to outsource allocation decisions so more time can be spent attracting and serving clients.
Yet investors are hardly innocent victims. Many appear to be blindly following model recommendations and taking little notice of the fees and performance, the paper said.
“Investors who chase the recommendations also behave differently, as they pay less attention to both the price and the performance of the ETFs,” the study found.
Brogaard at the University of Utah, Gerasimova at the Norwegian School of Economics and Liu at the Shanghai University of Finance and Economics tracked the effects of model changes in Morningstar data between 2010 and 2020.