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Klement draws on a research paper written earlier this year, with the very blunt title, “Ponzi Funds.” In that piece, authors Philippe van der Beck, Jean-Philippe Bouchaud and Dario Villamaina find a feedback loop, from ETFs to stocks, and then back to ETFs. “Investors are unable to identify whether realized returns are self-inflated or fundamental. Because investors chase self-inflated fund returns at a high frequency, even short-lived impact meaningfully affects fund flows at longer time scales,” they say.
The researchers are quick to emphasize that the ETF providers themselves are not operating literal Ponzi schemes as defined by the U.S. Securities and Exchange Commission. But they note that Archegos Capital Management — where Bill Hwang was just sentenced to 18 years in prison — was an example where returns from an investment fund trading concentrated positions can be driven by the fund’s own activity. And they say that, like Ponzi schemes, “the wealth reallocation from self-inflated returns unravels once the price impact in the underlying securities reverts and investors stop misinterpreting self-inflated returns as managerial skill.”
The researchers point to one “large thematic ETF” with a chart that is strikingly similar to the Ark Innovation ETF where its raw daily returns and flow-induced trades were over 40% correlated. Its positions were 20 times larger than the daily dollar volume in those securities, they said. That resulted in situations where the fund was buying 20% of the daily volume of the underlying stocks and stirring that feedback loop.
The issue is not limited to Cathie Wood alone. The researchers looked at 1,868 exchange-traded funds. “When the funds hold a liquid portfolio, there is virtually no relationship between daily flows and returns. However, for the most illiquid funds, the realized return increases monotonically with the flow,” they say.
These funds do typically devour themselves, but not right away. “On average, bubble ETFs do not crash within the first year of the run-up,” they say.
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