Why AI Powered ETFs Can Surpass Thematic ETFs

The U.S. Exchange Traded Fund (ETF) industry has become a behemoth in the stock market in recent years, surpassing a record high of $5.5 trillion dollars in assets under management in 2020.

Part of its proliferation is due to a growing popularity in thematic investing – more specifically, with thematic ETFs, which account for 1.9% of the total ETF market share (Palanrani, 2021). They allow investors to ride a trend that essentially carries an entire sector. Trends like clean energy, cybersecurity, and cloud computing have spiked interests and proven to be successful ETF products.

With increasing adoption of new technologies and trends, some may agree the possibilities for thematic ETFs are endless. However, research shows that investors should think twice before buying another trendy thematic ETF.

What are Thematic ETFs?

To start, thematic ETFs focus on macro-level trends[1] and identify areas of growth in disruptive and evolving industries. According to the Thematic ETF Report Q4 2020 by the Global X ETFs’ research team, there were a total of 148 thematic ETFs with $104.1B in assets under management in Q4 2020. according to Global X, this is up 78% from Q3 of 2020. (Palanrani, 2021)

Disruptive technologies may include Fintech, Digital Content, Big Data, Robotics, and Mobility – many of which have underlying themes like Electric Vehicles, Blockchain, Cybersecurity, and AI. Other evolving industries include consumer trends like Cannabis or Sports Betting and environmental issues like Clean & Renewable Energy and CleanTech.

The Problem with Thematic ETFs

The potential issue with thematic ETFs comes down to risk. The current landscape of specialized ETFs, particularly thematic ETFs, have attracted greater media exposure than broad-based ETFs[3] and thus may have driven the price up with irrational expectations. According to the research paper, financial innovation in the ETF industry, once the hype or trend dies down, most thematic ETFs end up underperforming the market and delivering negative risk-adjusted returns[2]. (Ben-DavidItzhak, 2021) For example, browse through any financial news online and you’ll quickly find that Cathie Wood has been grabbing headlines with ARK ETFs. With that being said, most thematic ETFs are narrowly focused and not diversified enough and the greatest pain point might be that they depend heavily on certain sectors to drive growth.

Looking at the exponential growth of ARK investments, you’ll find the company owns significant amounts of stock in a single sector, carrying all the risk of that sector. As of 09/13/21, ARK Innovation ETF (NYSE: ARKK) holds more than 10% in Tesla stocks so far. If the tech sector suddenly drops in price, ARK funds will most likely have a dramatic impact. This is just one example. Other thematic ETFs cover stocks related to COVID-19 vaccines, work from home trend, and even Black Lives Matter movement. Once the underlying factors for those trends die down, there is a potential risk of their price dropping significantly.

On the other hand, broad-based ETFs are likely more favored by institutional investors. Broad-based ETFs are funds that track broad market indices. They are considered more beneficial in that they reduce transaction costs and provide higher diversification. While specialized ETFs may attract unsophisticated investors who chase performances and disregard fundamentals, broad-based index-tracking ETFs often offer low-risk and low-cost exposure to greater market segments.

The Impact of AI on Actively Managed ETFs

Some may argue that thematic ETFs, while risky, do offer higher returns than broad-based ETFs, at least in the short-term. This is true in many cases, where some investors just want to ride market momentum until the trend is over.

But what if there’s an alternative way to find excess return without taking excessive risk? In the broad-based active ETF category, there is such a thing called AI powered ETFs. AI powered ETFs are managed directly by AI. In other words, no humans manage the fund.

What is an AI powered fund? To put it simply, it is a fund that uses AI technology to construct an investment strategy, apply that to a universe of stocks (e.g.: large cap stocks), choose the stocks that meet the strategy, and finally give the weights of those stocks in the ETF portfolio.

With the broad-based, active approach, AI powered ETFs can potentially provide excess returns compared to their index. Additionally, due to the potential lower volatility of allocating in multiple sectors, it can potentially provide better risk-adjusted returns as well.

Qraft AI ETFs, which consist of four listed AI powered ETFs on the New York Stock Exchange, built a proprietary AI technology that automatically finds alpha factors to potentially bring excess returns.

Qraft’s core research technology, called Alpha Factory[5], leverages AutoML[6] and Deep Learning[7] technology to find market factors apply them to the large cap holdings in the fund. The AI automatically rebalances the weightings of the stocks each month to favor potential outperformance against the benchmark index.

Once example of this is when Qraft AI-Enhanced U.S. Large Cap Momentum ETF (NYSE: AMOM) held Tesla as its biggest position for three consecutive months starting in November 2020. However, Qraft’s AI system automatically reduced Tesla shares to zero beginning of September when the stock plummeted by 13.9% and did not buy back until November when the stock became bullish again. This may very well be just a mere coincidence. However, this could also be indicative of the potential predictive power of AI’s solution for building high performing ETFs.

For information purposes only. Not meant to represent the Fund. Past performance does not guarantee future results. For AMOM top ten holdings, click https://qraftaietf.com/amom.

Key Takeaway

With all investments in the stock market, there will always be a risk factor involved. In the advent of thematic ETFs, investors are exposed to trendy themes with the possibility of holding attention seeking and overvalued stocks that may potentially result in lower risk-adjusted returns. As a viable alternative to specialized ETFs, investors can add AI ETFs that are broad-based and provide diversification with the added benefit of AI integrating alpha factors in search of excess return strategies.

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[1] Macro level trends – A macro trend is a pervasive and persistent shift in the direction of some phenomenon on a global level. Examples of current macro trends include urbanization, automation, and changing demographics.

[2] Risk-adjusted returns – A risk-adjusted return is a calculation of the profit or potential profit from an investment that takes into account the degree of risk that must be accepted in order to achieve it.

[3] Broad-based ETFs – Broad-based ETFs are all ETFs that track broad market indices.

[4] Alpha – Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index.

[6] Factor Factory – Qraft’s core AI technology that automatically finds factors that could bring excess returns. Factor Factory is able to produce at least 10 factors per day without any human intervention.

[7] AutoML – Short for Automated Machine Learning, AutoML is the automation of the machine learning process to make machine learning jobs simpler, easier, and faster.

[8] Deep Learning - a type of machine learning based on artificial neural networks in which multiple layers of processing are used to extract progressively higher level features from data.

References

Ben-David, I. a. (2021). Competition for Attention in the ETF Space. Swiss Finance Institue Research Paper Series, 66.

Palanrani, P. (2021, January 7). Thematic ETF Report: Q4 2020. Retrieved from Globalxetfs Website: https://www.globalxetfs.com/thematic-etf-report-q4-2020/