4 AI-Powered ETFs: Pros And Cons

Artificial intelligence seems like it’s all the rage these days, so it’s not so surprising that investors would try to use AI to get an edge when it comes to investing. But AI is not an idea that’s limited to well-connected experts. Anyone can buy exchange-traded funds (ETFs) that use machine learning tools to analyze stocks, predict which stocks will rise and then invest in them.

Here are some key things to know about AI-powered funds and which AI funds are trading now.

What is an AI-powered fund?

AI-powered funds are those that use machine learning to research and select stocks or other investments. So these funds are not necessarily investing in AI companies (such as Nvidia), but rather using the technology to find patterns in the data and then selecting which stocks to buy.

In many cases, AI gathers public data points to help determine the market’s sentiment on stocks. The AI may gather info on stocks from social media, news, financial statements, analyst reports, online message boards and any other source that shows the market’s pulse. Depending on its objective, the AI may carefully examine financial data and predict which businesses are likely to continue performing well, and may distill its research into a list of stocks for fund managers.

Some AI models may not only select attractive stocks but also recommend how much to buy, even if they leave the final decision-making up to human fund managers.

AI models may simplify the process of finding attractive investments, potentially identifying traits that are correlated with outperformance and increasing the productivity of the fund’s managers. So AI can leave managers with more time to examine the in-depth research and determine which stocks are worth further investment of time and money.

What are the pros and cons of AI funds?

AI-powered funds have the potential to be game-changing, but would-be investors shouldn’t overlook the drawbacks. Given how new these funds are, the benefits are mainly potential in nature until they’re proven out in practice (or not).

Pros of AI funds

  • Potentially low costs: An AI-powered fund may be able to replace a team of stock analysts or at least leverage their expertise more efficiently, reducing the expense ratio of the funds and therefore the ultimate cost to investors.
  • Potential outperformance: If the AI-fund is managed and programmed well, the fund may be able to outperform the market as a whole. However, it could turn into an arms race, as the increasing prevalence of AI-powered funds erodes their advantage. It remains to be seen whether they can consistently outperform passive investing.
  • Flexibility: AI-powered funds may be more flexible in responding to market conditions than traditional human traders. For example, AI may recognize changes in market volatility and respond by buying stocks that could outperform in that environment.

Cons of AI funds

  • Limited track record: Many AI-powered funds have been in existence for a year or two, so their ability to deliver good returns is unclear at best. Investors should want to see at least a few years of performance data and then compare it with a basic S&P 500 index fund, which has a long-term track record of about 10 percent annual returns.
  • Low assets under management: Many AI funds have very low assets under management, meaning there’s relatively little interest in the fund (for now). That could make it somewhat harder to get out of the fund without affecting the price much.
  • Relatively high cost: Another potential consequence of a small fund is that it may have a higher expense ratio. A small fund doesn’t have as many assets to spread its costs over, resulting in higher ongoing costs for holders. With these funds’ limited track record, investors may end up paying more for underperformance.

4 AI-powered funds

Here are four AI-powered ETFs and some of their relevant information, as of August 16, 2023.

AI Powered Equity ETF (AIEQ)

This fund may be what you’re thinking about when you think about AI picking stocks. The fund uses IBM Watson to select stocks after examining social media, news, financial statements, analyst reports and more about thousands of American companies. The AI then identifies 30 to 200 stocks that are poised to outperform over the coming twelve months.

Assets under management: $110 million
Expense ratio: 0.75 percent

VanEck Social Sentiment ETF (BUZZ)

The ETF is technically passively managed, tracking the BUZZ NextGen AI US Sentiment Leaders Index, which includes 75 large-cap stocks that have the most positive investor sentiment. Sentiment is gathered from “millions” of data points across news, social media, financial news and even blogs. The fund has been in existence since March 2021.

Assets under management: $59 million
Expense ratio: 0.75 percent

WisdomTree International AI Enhanced Value Fund (AIVI)

This fund uses an AI model to research and identify value-priced stocks, though it includes only mid- and large-cap stocks from developed markets outside the U.S. and Canada. This fund focuses on income and capital appreciation, and changed its strategy (and name) in January 2022 to use AI to help sift the market for stocks with lower valuations.

Assets under management: $72 million
Expense ratio: 0.58 percent

Qraft AI-Enhanced U.S. Large Cap Momentum ETF (AMOM)

While humans are still overseeing the shop at this fund, it’s AI that’s combing deeply through the market and recommending what to buy and how much. The AI looks for large-cap momentum stocks, those that have performed well in the recent past and are likely to continue doing so in the near future. This fund began in May 2019.

Assets under management: $13 million
Expense ratio: 0.75 percent

Bottom line

The idea of AI-powered stock selection is thrilling, but the real implementation is in the early stages. Investors considering going with an AI stock-picker should carefully consider their own needs as well as the fund’s potential performance and its cost, compared to traditional ETFs.

Editorial Disclaimer: All investors are advised to conduct their own independent research into investment strategies before making an investment decision. In addition, investors are advised that past investment product performance is no guarantee of future price appreciation.

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