Increasing awareness of human stock pickers Difficult to outperform Their benchmark index has spurred a significant surge in assets held by passively managed exchange-traded funds. Now, some companies want to show that artificial intelligence can ultimately give them an edge.
While this technology is evolving rapidly, at least two fund managers operating dedicated AI-powered ETFs, EquBot and Quraft Technologies, are keen to implement some of the AI model decisions. Claims early success, even if you need it.
For example, Qraft’s team, which offers four AI-powered ETFs listed on NYSE Arca, introduced technology to build a 14.7% weight on Tesla at the Qraft AI-Enhanced US Large Cap Momentum ETF (AMOM) last August. I witnessed it. When I rebalanced on September 1st, a year later, I sold everything.
ETFs began buying Tesla again in November and held a 7.6% stake by January this year, but rebalanced in February to sell their entire stake again. In each case, the sale was expected to cause Tesla’s price to fall sharply, and we were able to profit from the rise after the buyback.
“alpha [excess returns above the market] Francis Oh, managing director of Qraft and head of AIETF, pointed out that humans can be emotionally obsessed with certain stocks and hinder portfolio returns. “There is no human prejudice in our model.”
Academic research Indeed, it does show that while humans tend to be reluctant to crystallize losses, they, on the contrary, feel driven to realize profits.
However, the AI system used by Qraft and EquBot is supported by a large team of data scientists who are constantly enhancing their models, so it’s arguable whether it really can be said to eliminate human prejudice. .. EquBot is affiliated with IBM Watson and Qraft has a dedicated team in South Korea.
“The machine only has historical data,” said Greg Davis, head of behavioral science at Oxford Risk’s consultancy.
Chris Natividad, Chief Investment Officer of EquBot, agrees that “the system only knows what it knows and it’s historic,” and humans argue what new information should be given to the self-learning system. In addition to the decision, we also added a data scientist. We needed to see the results “to explain to investors”.
Both EquBot’s ETFs, the AI Powered Equity ETF (AIEQ) and the AI Powered International Equity ETF (AIIQ), have outperformed their respective benchmarks since their inception.
Similar success was further enhanced by Qraft’s suite of AI-powered vehicles. But so far this year, the outperformance description is less clear when compared to the plain vanilla SPDR S & P 500 ETF (SPY).
AMOM and other Qraft funds, the Qraft AI-Enhanced Large Cap ETF (QRFT), the Qraft AI-Enhanced US High Dividend ETF (HDIV), and the Qraft AI-Enhanced US Next Value ETF have returned 15.3% to 20.8%. Provided. Cents for 8 months until the end of August. While fine, none was a perfect match for SPY’s 21.6% revenue over the same period.
AIEQ also fell below SPY, recording a 21.3% increase in the eight months to the end of August, but AIIQ achieved only 12.2%.
Despite the remarkable revenue this year, Oh and Natibidad are confident that their model has a lot to offer.
“The speed, variety and volume of data is exploding,” said Natibidad, adding that ingesting new data sources is a bit like adding pixels to online images. “You get a clearer image,” he said, as asset managers and index providers were involved in an arms race for data.
Ah, the value and momentum factors are so short-lived and fragmented that AI systems have helped us find opportunities.
EquBot scrutinizes news, social media, industry and analyst reports and financial statements to build forecasting models. Also, check job information. Qraft also drives models using a variety of so-called structured and unstructured data sources.
However, despite the technology potential, the assets under management of both companies’ ETFs remain modest. While AIEQ and AI IQ have less than $ 200 million in assets, Natibidad said the partnership with HSBC, which used two EquBot indexes, had $ 1.4 billion to track the strategy.
Qraft’s ETFs have raised less than $ 70 million on all four vehicles, but Oh said the business model is once again focused on B2B advisory asset allocation modeling.
Track Insight ETF analyst Rony Abboud said investors probably want to know more. He emphasized the importance of due diligence and added: “The more data points you use, the more likely you are to get an error. So where do you get the data from and how accurate are you?”
Despite uncertainties, the adoption of AI technology is increasing in the investment world. “Natural language processing is certainly a growing area,” said Emerald Yau, Head of Equity Index Product Management for the Apac region of FTSE Russell. Its launch A series of innovation-themed indexes
However, Oxford Risk’s Davies warned that while the algorithm is good at finding arbitrage opportunities, it can’t deal with ambiguity.
“The problem in the investment world is that the rules are not static,” he said, adding that humans still maintain their dominance. “Once a person learns one thing in one context, he can move it to another.”
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