ETFs: would you let a robot pick your investments?

Artificial intelligence capabilities have grown exponentially in recent years and are now set to disrupt the traditional asset management sector. But how have AI-driven ETFs performed to date and would you invest your money in a fund that is powered by a machine?

The value of investments can fall as well as rise, and you may get back less than you invested. Past performance is no guarantee of future results
Would you let a robot pick your investments?

How do AI ETFs work?

Artificial intelligence (AI) is a field of computer science that aims to create intelligent machines that operate and respond like the human brain. The exponential growth in this technology has led to various industries adopting AI to either assist or replace human workers.

AI is already being used by investment fund managers to attract assets from the more adventurous investor, and to attempt to beat both the market and human active fund managers. The vehicle of choice to deploy this type of strategy has so far been the exchange traded fund (ETF). Already there are a number of ETFs based on AI that picks stocks and constructs investment portfolios.

It is important to differentiate between an ETF that invests in companies that use, develop or sell AI-related products and services, and an ETF that uses AI to choose which companies to invest in and what weight to give that investment in its portfolio of assets. This article concentrates on the latter — what we will call AI-driven ETFs.

The main advantage of using AI in the investment process is the ability to efficiently process huge amounts of financial data to identify attractive investments. The data consumed by these algorithms can cover anything from company reports and technical analysis to the latest news and social media sentiment. As well as stock picking, AI can also be used to overcome a number of human cognitive and psychological biases that are common in the portfolio construction and management process.

How have AI ETFs performed?

The first AI-driven ETF was launched on 18 October 2017 by EquBot, a US company and member of IBM’s Global Entrepreneur start-up program. Their ETF is called the AI Powered Equity ETF (AIEQ US) and invests solely in US stocks which are chosen based on the results from IBM’s Watson AI technology.

AI Powered Equity ETF vs S&P 500

Source: Bloomberg

As you can see from the chart above, after a shaky start, AIEQ has outperformed the S&P 500 by 2.8% since its inception. After further analysis, the fund takes on slightly more risk than the S&P 500 with a relatively higher weight in US small cap stocks. The fund is also currently overweight in both the financial and real estate sectors relative to the S&P 500, with notably large positions in Nasdaq (NDAQ) and a minor real estate trust called Forest City Realty Trust (FCE).

Its current top ten holdings can be seen in the table below:


Another AI-driven ETF is Canada-listed Horizons Active AI Global Equity ETF (MIND), which launch two weeks after AIEQ. Instead of picking individual stocks, MIND invests in regional ETFs to form an ‘ETF of ETFs’. Compared with the MSCI World Index, it has underperformed by just over 2% since its inception.

If you are interested in investing in either of these ETFs, it is important to consider your exposure to currency risk since AIEQ and MIND are based in USD and CAD, respectively. UK residents must also be wary of the tax treatment of products that do not have Reporting Fund status. This could mean that capital gains made on Non-Reporting Funds are subject to income tax (maximum 45%) as opposed to paying capital gains tax (maximum 20%) on a Reporting Fund. A list of Reporting Funds can be found on HRMC’s website.

What is the future for AI-powered investing?

One of the biggest advantages with AI is that machines can learn from their mistakes and improve. An example of this ability is Google’s AlphaGo, a program which plays the board game Go. AlphaGo first beat a human professional player in October 2015 then took five months of learning before claiming victory against the reigning Go world champion Lee Sedol, under the name AlphaGo Lee.

Its most recent iteration — AlphaGo Zero — took just three days to beat AlphaGo Lee.

However, while Go itself is an incredibly complex game, financial markets do not have a defined rule book and will be far more complex for algorithms to conquer. In the short term, AI will most likely supplement human knowledge and help investment professionals make better decisions more efficiently.

In the long term, if AI can progress to overcome aspects such as being capable of explaining why it made particular decisions, investors may become comfortable with a machine being in total control of their investments if it is proven to deliver superior risk-adjusted returns.

With that I leave you with a quote not from Warren Buffet, but US professor Warren Bennis.

'The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment.'

This information has been prepared by IG, a trading name of IG Markets Limited. In addition to the disclaimer below, the material on this page does not contain a record of our trading prices, or an offer of, or solicitation for, a transaction in any financial instrument. IG accepts no responsibility for any use that may be made of these comments and for any consequences that result. No representation or warranty is given as to the accuracy or completeness of this information. Consequently any person acting on it does so entirely at their own risk. Any research provided does not have regard to the specific investment objectives, financial situation and needs of any specific person who may receive it. It has not been prepared in accordance with legal requirements designed to promote the independence of investment research and as such is considered to be a marketing communication. Although we are not specifically constrained from dealing ahead of our recommendations we do not seek to take advantage of them before they are provided to our clients. See full non-independent research disclaimer and quarterly summary.