EquBot’s exchange-traded fund, the AI Powered Equity Fund (AIEQ) uses machine learning as part of its portfolio selection using IBM Watson and Google DeepMind. One of the ways it learns is to read databases full of newspaper articles to see how companies perform in different environments.
“Each day,” says its prospectus, “the EquBot model ranks each company based on the probability of the company benefiting from current economic conditions, trends, and world events and identifies approximately 30 to 70 companies with the greatest potential over the next 12 months for appreciation and weights those companies to seek a level of volatility comparable to that of the broader U.S. equity market.” Humans then rebalance the portfolio.
By picking the best mix of stocks for the current environment, based on performance and risk, it’s not wrong to compare it to the shifting baseball teams in Moneyball, say its managers. The algorithm learns to put words like “steel tariffs” in context to decide whose ox gets gored by them.
“AI is specifically useful where there is a significant amount of data,” says the firm’s CEO, Chida Khatua, a former director of engineering at Intel. “And there is a way we can find or train the systems to understand the correlations.” That means evaluating both Excel spreadsheets and newspaper stories.
The $167 million fund’s AI model is based on how investors do due diligence on a company. They look at management, financials and how insight from news will influence companies’ profitability or equity prices. The idea is that the market trains the system to work better.
The fund charges a 0.75% expense ratio. The firm launched an international fund in June (AIIQ).
Robots Hunting Clients
Advisors are also using AI for marketing. Shirl Penney, CEO of RIA services firm Dynasty Financial Partners, recently told attendees at a Pershing Advisor Solutions’ RIA Symposium in New York that one of his firms on the West Coast did an entire marketing campaign based around artificial intelligence to bring in some $21 million in new client money.
“We wrote some simple white papers, very short and easy on ISOs, stock options, for Snapchat employees,” Penney said. The firm then used LinkedIn to target executives at the company. “The strategy was very simple: To position this group of advisors as experts in stock option cash-flow analysis, diversification, etc., running a concentrated position, in this case for Snap. And then we had a very simplistic AI tool that interacts with the client.” The advisors set the software and then let it do its work, Penney said. If a client clicked through (“raises a hand”) the software sent more educational materials on options. Ultimately, a meeting could be inked in.
“In the last campaign that we ran, [we got] 16,000 impressions. Nine hundred times the employees clicked through. It automatically, through the system, set up 15 meetings. Of the 15 meetings, the advisors closed seven of them. It was $21 million in new assets. Let me show you how much that campaign cost: $600.”