Qraft Technologies has partnered with LG AI Research to launch an AI-powered ETF that invests in U.S. large-cap core stocks. The actively managed LG Qraft AI-Powered U.S. Large-Cap Core ETF (NYSE Arca: LQAI) trades on the New York Stock Exchange.
Qraft and LG have developed an artificial intelligence (AI) forecasting model to power the fund. LQAI seeks to exceed the return of U.S. large-cap stocks over time by investing in 100 stocks. It targets the U.S. large-cap stocks its AI model sends signals about with the highest conviction in each rebalancing period. The fund is rebalanced every four weeks.
Transforming Large-Cap Core Investing Through AI
The AI forecasting model is driven by a deep neural network to analyze a vast amount of data. This includes macro variables, fundamental data, and market trends. It will seek patterns and signals that may be challenging for humans to identify at that speed and scale. It proactively identifies the relative strength of individual stocks by analyzing data far faster than humans can process.
LQAI’s AI-backed strategy integrates various predictive scenarios, aiming for alpha generation throughout all market phases. The model constantly works to optimize risk-adjusted returns and seize evolving investment opportunities. And it does this while predicting and positioning the portfolio to shield assets against potential market risks.
Qraft’s founding CEO Marcus Kim said LQAI is “setting the stage for a revolutionary transformation in how investors approach large-cap core investments.” The fund could also “harness the potential of AI to drive positive returns for investors.”
Leveraging AI Tech for Better Returns
Qraft is no stranger to AI investing. In addition to LQAI, the fintech firm has also launched the QRAFT AI Enhanced U.S. Large Cap ETF (QRFT ) and the QRAFT AI-Enhanced U.S. Large Cap Momentum ETF (AMOM ).
“Advisors are gaining comfort with investment strategies that leverage artificial intelligence,” said VettaFi’s Head of Research Todd Rosenbluth. “Qraft has demonstrated expertise in leveraging the technology for security selection in the past.”
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