In our previous post we touched on the potential of an ETF bubble. The exponential growth of ETFs, especially from younger investors who want to set-it-and-forget-it, means there’s an opportunity for providers to increasingly use Artificial Intelligence in smart alpha and active products. But what can AI do for your business and investment strategy?
Like Humans, Only Better, Faster, Smarter
AI tools can intake data, learn from it, and act on it to meet specific objectives. But they can do it more quickly and efficiently. In fact, machines running AI algorithms can process large amounts of data in the blink of an eye. Market data is dynamic. Machines can react instantly to fluctuations to best identify ideal investment strategies. They can also read through thousands of pages of market reports in seconds, while simultaneously connecting new market signals with recent ones detected in other markets. It would take a fund manager hours to do the same thing a machine can do in split seconds.
AI Has No Ego or Emotion
Investors tend to make poor decisions because it’s their money they could lose. Money is emotional. But machines don’t get stressed, tired, or angry. There’s no winning or losing. They operate in a purely logical manner and make decisions based only on evidence and indicators. When you remove emotion from the equation, you make better decisions. There’s no holding onto a position because you think it might change. There’s only analyzing the facts and deciding based on what is happening, not what might happen.
Disrupting the ETF Industry
ETF positions are decided on by an AI system that processes market signals, news articles, and social media posts. Daily trade recommendations in an AI capacity are not only easy, but cost-effective. Smaller fintechs and individual developers have unprecedented access to this technology. Perhaps you read about AIIQ from EquBot, the first exchange-traded fund to use AI technology to pick stocks from developed markets outside of the U.S. It leverages IBM’s Watson capabilities to build predictive models that identify 30-70 U.S. stocks every day that have the best appreciation potential.
IBM’s open APIs and developer-friendly portals charge per API call once a product is live. This sort of scalability makes AI accessible to anyone, regardless of size or motivation. And, as you can see from the below chart, ETF providers who aren’t taking advantage of AI are losing out on revenue.
All About the Alpha
Experienced traders are turning to AI in order to maximize profits in up markets and minimize risk in down markets. Because AI leverages Natural Language Processing, Sentiment Analysis, and Numerical Data Processing to analyze social sentiment with lightning speed and precision, it can maximize alpha. It takes a human three seconds to analyze a tweet, but it takes AI less than one millisecond to analyze a tweet as bullish or bearish.
Since AI doesn’t need to sleep, it can be working 24/7, even when the markets are closed, trying strategies that might be difficult to execute for traders. And because of the amount of data available, risk is mitigated because AI will know when to get out before it’s too late. An AI system can make daily stock recommendations that the ETF manager can then use to shift positions, increasing alpha.
Compete or Go Home
An important aspect of any AI strategy is partnering with external developers. Because, in order to compete with the top financial firms in your sector, you need to leverage machine learning or risk being left behind. In fact, you might already be.
Are you leveraging AI in your business? We’d love to hear about it.