Tuesday, August 14

New ETF aims AI at developed markets outside US

LinkedIn Google+ Pinterest Tumblr +

EquBot launched AIIQ, a new actively managed ETF that targets developed international markets outside the US.

Securities are selected based on the results of proprietary, quantitative, AI-driven model, which runs on IBM’s Watson platform.

Each day, the EquBot model ranks thousands of stocks based on the probability of each company benefiting from current economic conditions, trends and world events.

It then identifies between 80 and 250 companies for inclusion in the portfolio that have the greatest potential for price appreciation over the next 12 months.

“In considering the next iteration of our AI-driven investment approach, expanding the focus to include all of the developed markets outside of the US was the next logical step,” said Chida Khatua, CEO and co-founder of EquBot in a statement.

 

Read the latest on AI in ETFs from MarketBrains

 

The model also seeks to incorporate a volatility screen, with a goal of maintaining portfolio volatility comparable to that of the broader developed markets ex-US.

AIIQ may invest in companies of any market capitalization, and the weight of any individual company in the underlying portfolio is capped at 10%.

Its expense ratio is 0.79 percent, according to the company. The average ETF carries an expense ratio of 0.44%, which means the fund will cost you $4.40 in annual fees for every $1,000 you invest, according to a guide by the Wall Street Journal.

The average traditional index fund costs 0.74%, according to Morningstar Investment Research as cited by the WSJ.

 

Read what the buy-side says about AI in ETFs

 

EquBot’s technology is driven by its proprietary algorithms, which operate across multiple AI cognitive computing platforms.

In asset management and portfolio construction, EquBot’s technology combines both fundamental and qualitative analysis while formulating new investment insights through the use of AI and massive amounts of data to build predictive financial models on more than 15,000 publicly traded companies in the US and in international developed markets.

“In order to fully understand the factors impacting an individual equity, you must be able to locate, synthesize and analyze thousands, sometimes millions, of pieces of data,” added Khatua. “That is where the power of AI comes into the equation.”

Share.

About Author

Leave A Reply