Worth Asset Management LLC Takes $260,000 Position in iShares U.S. Tech Independence Focused ETF $IETC

Worth Asset Management LLC purchased a new position in iShares U.S. Tech Independence Focused ETF (BATS:IETC) in the second quarter, according to its most recent filing with the Securities & Exchange Commission. The firm purchased 2,768 shares of the company’s stock, valued at approximately $260,000.

Several other institutional investors and hedge funds have also recently bought and sold shares of the company. McIlrath & Eck LLC bought a new position in iShares U.S. Tech Independence Focused ETF during the 4th quarter worth approximately $25,000. Gradient Investments LLC bought a new position in iShares U.S. Tech Independence Focused ETF during the first quarter worth $7,985,000. Parsons Capital Management Inc. RI bought a new position in iShares U.S. Tech Independence Focused ETF during the first quarter worth $246,000. Kozak & Associates Inc. boosted its holdings in iShares U.S. Tech Independence Focused ETF by 2.5% in the first quarter. Kozak & Associates Inc. now owns 679,194 shares of the company’s stock worth $50,254,000 after purchasing an additional 16,405 shares during the period. Finally, RMR Wealth Builders bought a new stake in iShares U.S. Tech Independence Focused ETF during the first quarter valued at $632,000.

iShares U.S. Tech Independence Focused ETF Stock Performance

Shares of BATS:IETC opened at $102.42 on Friday. iShares U.S. Tech Independence Focused ETF has a 1-year low of $64.06 and a 1-year high of $98.03. The company’s fifty day moving average is $98.14 and its two-hundred day moving average is $87.88. The stock has a market capitalization of $737.40 million, a price-to-earnings ratio of 37.47 and a beta of 1.18.

About iShares U.S. Tech Independence Focused ETF

The iShares Evolved U.S. Technology ETF (IETC) is an exchange-traded fund that is based on the MSCI USA IMI Information Technology index. The fund is an actively managed fund of US stocks in the information technology sector according to an alternative classification system defined by machine learning algorithms.