Home Finance Can an ETF Perform Better with IBM's Watson AI?

Can an ETF Perform Better with IBM’s Watson AI?

Artificial intelligence (AI) creeps in again, but this time it’s making a direct line to the investment portfolio world.

Traditionally, investment portfolios have always been managed by well-educated, savvy, business-like people, but times have changed and will continue to do so if AI has anything to do with it.

When you think about AI you may think about robots and automated manufacturing machinery, but it is so much more than that.

It covers all aspects of intelligent behavior by machines including deep learning and machine learning and is an area of computer science that’s due to become heavily researched and implemented over the next few decades.

READ MORE: 10 Applications of Machine Learning in Finance

READ MORE: Pioneer AI Hedge Fund – DE Shaw

The company behind the new AI innovation is San Francisco-based EquBot LLC and according to a recent company statement, it’ll soon be launching the very first ever exchange-traded fund to incorporate artificial intelligence into its application.

The name of the new AI-powered exchange-traded fund is AIEQ and it’s using IBM’s Watson to work off in an attempt to replicate the work of a team of equity research analysts.

“There has been an explosion of information,” said Art Amador, co-founder of EquBot. “AI provides a more informed way of investing.”

Having joined forces with ETF Managers Group of Summit, New Jersey, the fund will scan in excess of 6,000 U.S. publicly traded companies every day using advanced AI and machine learning techniques.

In using AI the company can be sure a diversified fund will be created at the end of it. AIEQ will filter through millions of news stories, sentiment gauges, regulatory filings, financial models, and company management profiles in order to establish a well-diversified portfolio featuring around 30 to 70 stocks in total.

MORE – IBM Watson: What you Need to Know

After the stocks have been selected, a group of ETF managers will use these selections to rebalance the portfolio. In theory, this could be every day if the computer suggests changes are required.

“When something is in our portfolio, we know why it’s in there,” said Amador. “We have an investment thesis about that position, and we can explain all the reasons why we own it or all the reasons why we’re going to get rid of it.”

Original source Bloomberg

Subscribe to our newsletter

Signup today for free and be the first to get notified on the latest news and insights on artificial intelligence

KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
- Advertisment -


AI Model Development isn’t the End; it’s the Beginning

AI model development isn’t the end; it’s the beginning. Like children, successful models need continuous nurturing and monitoring throughout their lifecycle. Parenting is exhilarating and, if...