
See exactly how AMOM's revenue becomes profit — a Sankey that traces revenue (and its reported segments) through gross profit, operating expenses, and net profit, with the year-over-year change on every line.
The same diagram the Chart Builder draws, right on the Summary tab. Upgrade to unlock it for AMOM and 80,000+ other tickers.
Exchange Listed Funds Trust - QRAFT AI-Enhanced U.S. Large Cap Momentum ETF is an exchange traded fund launched and managed by Exchange Traded Concepts, LLC. The fund invests in public equity markets of the United States. It invests in stocks of companies operating across diversified sectors. The fund invests in momentum stocks of large-cap companies. It seeks to benchmark the performance of its portfolio against the S&P 500 Index. It employs proprietary research to create its portfolio. Exchange Listed Funds Trust - QRAFT AI-Enhanced U.S. Large Cap Momentum ETF was formed on May 20, 2019 and is domiciled in the United States.

Artificial intelligence has become one of the defining investment themes of this cycle. Yes, we may be hearing about the AI pullback as a valuation reset.

QRAFT AI-Enhanced U.S. Large Cap Momentum ETF (NYSEARCA:AMOM - Get Free Report) saw a significant growth in short interest in the month of December. As of December 31st, there was short interest totaling 9,362 shares, a growth of 23.9% from the December 15th total of 7,559 shares. Based on an average daily trading volume, of

Momentum investing is likely to be a winning strategy for those seeking higher returns in a short spell.

AMOM is an AI-powered ETF that holds a portfolio of 50 large-cap stocks selected for their momentum features. Its expense ratio is 0.75%, and AMOM has $23 million in assets. Since its launch six years ago, AMOM has yet to attract many investors, and the lack of interest could lead to liquidation sometime soon if results don't improve. Inconsistency is AMOM's main problem. The portfolio turns over about once every two months, and my factor-tracking over the last year suggests quality is not a focus for AI.

AIEQ: An Example Of AI Failure