StockSnips AI-Powered Sentiment US All Cap ETF
Key Statistics
Historical Performance
Total return including reinvested distributions, from adjusted closing prices.
Price History
Price history is being compiled for this fund.
Top Holdings
Top 25 holdings as of Jan 30, 2026 · source: SEC N-PORT. Full holdings & prospectus →
About NEWZ
The Fund is an actively-managed exchange-traded fund (“ETF”) that seeks to achieve its investment objective by utilizing an investment strategy that leverages artificial intelligence (“AI”) and natural language processing to derive a proprietary News Media Sentiment Signal (the “Sentiment Signal”). AI refers to the application of computer systems to perform tasks that typically require human intelligence, discernment and adaption, such as decision-making, reasoning and learning from past experiences. The Fund’s sub-adviser, Stock Snips, Inc. (“StockSnips” or the “Sub-Adviser”), uses an investment process based on a proprietary ranking and selection process, which is designed to identify stocks with the most positive news coverage, as described in more detail below. Under normal circumstances, the Fund invests at least 80% of its net assets (plus the amounts of any borrowings for investment purposes) in securities of U.S.-listed large, mid and small capitalization companies. The Fund invests in equity securities of such companies, including common stock and American Depositary Receipts (“ADRs”). The Sub-Adviser’s quantitative security selection process begins with an investment universe of all U.S. listed equity securities. The investment universe is then screened for securities of issuers included in the following industries, as defined by Zacks sector and industry classifications: Computer/Office Equipment, Computer Software/Service, Non-Food Retail, Drugs, Miscellaneous Technology, Business Services, Food/Drug-Retail, Medical Care, Soaps/Cosmetics, Electronic-Semi-Conductor, Telecommunication Services, Media, Beverages, Investment Brokers/Investment Management, Insurance, Medical Products, Transportation, Other Consumer Discretionary, Electronics, Telecommunications Equipment, Utilities - Gas Distribution, Food, Utilities - Electric Power, Finance, Consumer Products - Miscellaneous Staples, Tobacco and Business Products. These industries may be modified on an annual basis when the investment universe is reconstituted. The Sub-Adviser then excludes any securities that have (i) less than $2 billion in market capitalization, (ii) high volatility as compared to the market as measured by a beta of equal to or greater than 1.5, (iii) a return on equity, which measures how much net income a company generates per dollar of invested capital, that is less than 15%, and (iv) less than a defined volume of news coverage. This process typically yields a universe of approximately 350 securities. The Sub-Adviser then utilizes its algorithms to select sentiment leaders amongst the remaining investment universe.The Sub-Adviser believes that quantification of news sentiment can be a proxy for investor sentiment. The Sub-Adviser employs quantitative modeling, which leverages the Sentiment Signal and a trending Sentiment Momentum signal (the “Sentiment Momentum Signal”). The Sentiment Signal uses natural language processing to derive investor sentiment using news articles, blogs and other textual information. The Sentiment Momentum Signal refers to the trend or direction of investor sentiment over time for a particular stock. A positive Sentiment Momentum Signal indicates growing optimism among investors, often leading to upward price movements. Conversely, a negative Sentiment Momentum Signal indicates increasing investor pessimism, which can lead to price declines. The Sentiment Signal and the Sentiment Momentum Signal are each derived using natural language processing and machine learning algorithms that transform unstructured textual data from News Sources (as defined below) into quantified real-time sentiment signals. Machine learning refers to technologies that enable a computer to learn from data it has processed to incorporate different assumptions or past experience into future computations or analysis. In the context of the StockSnips sentiment signals, machine learning is used to classify “financial oriented” sentences (news snippets) attributed to a company as being positive, negative or uncertain. StockSnips gathers news information on a daily basis and evaluates such information along with a proprietary historical sentiment dataset covering approximately 5,000 US equities. The algorithms rank the securities in the investment universe based on the amount of positive news available about a company and its sentiment momentum. The top 30 to 50 stocks are included in the Fund and are equal weighted. The Sub-Adviser expects that under normal market conditions, up to 95% of the portfolio assets will be invested in the securities recommended by the algorithms.The news snippets are collected from reliable online sources, including news articles, blog posts, SEC filings, earnings transcripts and analyst reports from Zacks, Motley Fool, Associated Press, CNBC and other financial news sources (collectively “News Sources”). The Sub-Adviser considers a News Source to be reliable if it is obtained from a publication or other source that has authors/analysts who research and write opinions or reports on events relating to U.S. equities. Some New Sources are licensed by the Sub-Adviser and others are publicly available.The portfolio is rebalanced and reconstituted on a monthly basis.
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Data for NEWZ is aggregated from third-party providers (Tiingo, Nasdaq, Finnhub) and SEC filings, may be delayed at least 20 minutes, and may be incomplete or contain errors. Nothing here is investment advice. Verify with the official prospectus before investing.