ETFs gather $4B a day as stocks slump
When stocks fall, investors typically pull money out of the market. But when U.S. equities suffered their worst two-day slump since May, some traders didn’t blink an eye.
ETFs took in $78.5 billion in January, exceeding the previous monthly record by nearly 30%. ETFs saw close to $4 billion a day in inflows even on the stock market’s down days, according to Eric Balchunas, a Bloomberg Intelligence senior ETF analyst, who cited the example of the index-tracking SPDR S&P 500 ETF Trust (SPY).
“This is unusual, especially for the highly liquid ETFs such as SPY, where flows usually correlate to the market,” Balchunas said. He identified two reasons for the divergence: “First, the low ETF volume during the selloff foreshadowed that it wasn’t that much of a panic situation and would be a ‘buy the dip’ type of selloff. Second, many investors may have used it as an excuse to move out of their mutual funds into an ETF.”
In price wars wars, the firm bolts ahead in the race to zero by nearly tripling its roster of commission-free funds.October 19
The launch from EventShares provides investors access to economic and policy-driven themes.October 20
Investors may be growing impatient with implementation of the administration’s agenda, an analyst says.November 9
The thinking goes that the migration of cash from more expensive mutual funds to ETFs can sometimes be exacerbated on down days, as investors take their profits. To Balchunas, it’s a sign of what could happen should this bull market sour.
“This provides a window into the seismic shift into ETFs that could occur in the next bear market, when investors who are currently ‘locked in’ to active mutual funds via their unrealized gains can finally leave for the cheaper, more tax-efficient ETF structure,” he said.
State Street was the chief beneficiary in January, taking in the most money through flows for the second straight month. Before December, the last time the Boston-based firm came out on top was November 2016, according to Bloomberg data.