AIQ: Suitable Niche Investment For Those Dead-Set On An AI-Themed ETF

Artificial intelligence as an investment theme has gained in popularity lately, spurred on by the potential of the technology across multiple industries. Market projections put global AI growth north of 35% annually through 2030. The Global X Artificial Intelligence & Technology ETF (NASDAQ:AIQ) has been one beneficiary of the hype. The following fund flows chart shows that AIQ has gained a little over half a billion in assets over the last five years with a large percentage of flows occurring only in the past year or so.

The passively managed fund uses a market-cap weighting to track the Indxx Artificial Intelligence & Big Data Index. The current top 10 holdings are shown in the table below and are highlighted by several big-name tech companies.

This article analyzes the performance of AIQ against several market benchmarks and peer ETFs to determine whether it's a good choice to invest in broadly or as a means to target the AI space.

Performance vs Market Benchmarks

AIQ launched in May 2018 so there isn't a whole lot of historical data to gauge long-term performance but we can still see how the fund performed against benchmark ETFs over the period. The following chart compares the total return for AIQ against the SPDR S&P500 ETF (SPY), Invesco QQQ Trust (QQQ), and iShares Russell 2000 ETF (IWM) since May 2018.

The chart shows that AIQ beats the S&P500 benchmark over the period but lags the tech-heavy QQQ by almost 40%. Further analysis attempts to view underlying trends that factor in risk to provide a more complete comparison. First off, it's very noticeable from the graph that AIQ follows the same general trends as the benchmark ETFs over the period. The following table shows the correlation between AIQ and other funds. Notice that AIQ's strong correlation to QQQ.

The methodology employed for performance analysis utilizes all available one-year return data over a period instead of using a single start and end date. So in analyzing historical returns for AIQ since May 2018, we use over 1,100 individual 1-year return periods instead of just one start and end date reference. The following chart shows the individual 1-year rolling returns for AIQ since launch.

Although charts are nice, it's more useful and easier to interpret the results in tabular form. The following table outlines return metrics for AIQ over the period 5/16/2018 - 10/19/2023. A variety of returns are given along with risk metrics supplied by standard deviation.

At first glance, the high average return and high standard deviation give an initial impression of a high-risk high reward investment. This is further supported by the halving and doubling performance in the lowest and highest returns with a -42.50% drawdown and 115.46% gain. Breaking the performance up into positive and negative components gives further insight. The average positive return outweighs the average negative return by a good amount and is something we should look for in an investable ETF product. More importantly, the spread between positive volatility over negative volatility is roughly 8%.

Comparing AIQ's return metrics with market benchmarks further reveals it as a more volatile investment. The following table supplements AIQ data with that of benchmark ETFs. Note that Return/Risk is defined as the average return divided by negative volatility and not total volatility.

The average return of 16.28% compares very favorably against the benchmark ETFs but also comes with the highest standard deviation of 30.53%. However, as implied earlier, a long investor's primary concern for volatility as a measure of risk is to the downside. In this respect, AIQ clearly shows the highest downside risk with a negative volatility of 12.20%. It also has the lowest volatility spread but we still need another performance measure that takes into account the return potential on a more equal footing with risk. In an attempt to provide a metric that takes equal account of returns and risk, I define a risk-adjusted return as the average of the average return and spread between the average return and negative volatility.

Risk-Adjusted Return = (Average Return + Average Return - Negative Volatility) / 2

The following tables highlight the results of a risk-adjusted return measure for AIQ and market benchmark ETFs.

When gauging performance on an equal footing with risk, AIQ's results begin to interact more favorably with benchmark ETFs and put AIQ on par with the S&P 500 benchmark SPY. The performance of QQQ still outperforms by a wide margin and given the strong correlation to AIQ shown earlier marks the better choice for a core holding than AIQ. The following peer analysis can help determine whether AIQ remains an option for a smaller portfolio allocation for those determined to add specific AI exposure.

Peer Analysis

In order to provide a peer analysis for ETF alternatives in the AI space, I used the top five funds most mentioned in articles with AIQ according to Seeking Alpha. Those include ProShares MSCI Transformational Changes ETF (ANEW), TrueShares Technology, AI and Deep Learning ETF (LRNZ), Robo Global® Artificial Intelligence ETF (THNQ), First Trust Nasdaq Artificial Intelligence and Robotics ETF (ROBT), and iShares Robotics and Artificial Intelligence Multisector ETF (IRBO). Some high-level fund data is shown in the following table.

In order to directly compare the peer group, we have to use the least common denominator for the time period reference, which is ANEW having launched in October 2020. The following table shows that over the timeframe from October 2020 to present all of the funds are highly correlated with AIQ.

So while there may be some differences in top 10 holdings, it hasn't mattered all that much as the peer group moves largely in unison.

The return data over the period October 2020 - present is outlined in the following table.

Even though the period analyzed is relatively short it does give an opportunity to review a timeframe that produced negative returns. It's clear that AIQ procured the best average return along with the best risk-adjusted return. For investors looking to add a targeted AI-themed ETF to their portfolio, AIQ is the top choice.

Conclusion

AI-themed ETFs haven't been around that long, but the space continues to grow giving investors more choices. Those choices, however, haven't seemed to add much value over AIQ based on the peer performance comparison. More generally, one could easily argue that holding QQQ would be a better alternative given the high correlation to AIQ but with stronger performance metrics. In the end, AIQ could be a good choice for a small portfolio allocation for investors dead set on having an AI-themed ETF in their lineup.