iShares U.S. Consumer Focused ETF (BATS:IEDI) Trading 0.6% Higher – Still a Buy?

Shares of iShares U.S. Consumer Focused ETF (BATS:IEDIGet Free Report) shot up 0.6% during trading on Tuesday . The company traded as high as $54.07 and last traded at $53.53. 4,382 shares traded hands during trading, The stock had previously closed at $53.19.

iShares U.S. Consumer Focused ETF Stock Performance

The company’s fifty day simple moving average is $55.14 and its two-hundred day simple moving average is $53.47. The stock has a market capitalization of $29.44 million, a P/E ratio of 29.06 and a beta of 0.96.

Institutional Investors Weigh In On iShares U.S. Consumer Focused ETF

Several hedge funds have recently bought and sold shares of IEDI. Moors & Cabot Inc. bought a new stake in iShares U.S. Consumer Focused ETF in the fourth quarter worth $502,000. Mountain Hill Investment Partners Corp. purchased a new position in shares of iShares U.S. Consumer Focused ETF in the fourth quarter worth about $32,000. Tower Research Capital LLC TRC lifted its stake in shares of iShares U.S. Consumer Focused ETF by 312.8% in the 4th quarter. Tower Research Capital LLC TRC now owns 33,001 shares of the company’s stock valued at $1,763,000 after acquiring an additional 25,007 shares during the last quarter. Susquehanna International Group LLP purchased a new stake in iShares U.S. Consumer Focused ETF during the 4th quarter valued at about $1,877,000. Finally, B. Riley Wealth Advisors Inc. grew its position in iShares U.S. Consumer Focused ETF by 11.4% during the 4th quarter. B. Riley Wealth Advisors Inc. now owns 4,924 shares of the company’s stock worth $263,000 after acquiring an additional 502 shares during the last quarter.

iShares U.S. Consumer Focused ETF Company Profile

(Get Free Report)

The iShares Evolved U.S. Discretionary Spending ETF (IEDI) is an exchange-traded fund that is based on the MSCI USA IMI Consumer Discretionary index. The fund is an actively managed fund of US stocks in the discretionary spending sector according to an alternative classification system defined by machine learning algorithms.

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