Since April 2023 (about 2 weeks after Chat GPT-4 was released to much fanfare) through this most recent New Years Eve, the most straightforward decision for investors would have been to put everything into the S&P 500 and forget it. Which is to say, investing had gotten pretty boring the last few years. The winners kept winning and the losers kept losing and any attempt to pick up value or mean reversion was run over by the continuing momentum of the AI trade.
Now we are finally entering the realm of the infamous Chinese curse,[1] “may you live in interesting times.” In this case, may you invest in interesting markets.
Are U.S. Sectors Undergoing a Portfolio Rotation?
Source: Bloomberg. Data from 1/1/2015 to 2/27/2026. S&P 500 is represented by the State Street SPDR S&P 500 ETF (SPY). Sectors are represented by the State Street SPDR Series of sector ETFs including XLB, XLC, XLE, XLF, XLI, XLK, XLP, XLRE, XLU, XLV, and XLY.
As shown in the chart above, going back to 2008, on any given day, around 5 out of the 11 US equity sectors were outperforming the S&P 500 index on a trailing 1-year basis. From the beginning of the second quarter in 2023 to the end of 2025, only 3 sectors on average were beating the S&P 500 index on any given day. International equities, both developed and emerging, have not performed any better than the lagging US Sectors. That has shifted in 2026 though as most recently 6 of 11 sectors were leading the S&P 500 on the trailing year.
Percent of Days Sector was Beating S&P 500 on Trailing 3-Month Return
Source: Internal analysis of Bloomberg data. State Street SPDR Sector ETFs depicted here include: Basic Materials = XLB; Communication Services = XLC; Consumer Discretionary = XLY; Consumer Staples = XLP; Energy = XLE; Financials = XLF; Healthcare = XLV; Industrials = XLI; Real Estate = XLRE; Technology = XLK; Utilities = XLU. Data from 4/1/2023 to 2/27/2026.
The sectors that have most frequently trailed the S&P 500 since the start of the year (relative to the prior ~2 years) also tend to be those most directly tied to the AI trade, with the frequency of underperformance generally declining as AI exposure decreases. Technology has fallen behind the most, followed by Communication Services (Meta and Google), Financials, Utilities, and Consumer Discretionary (Amazon and Tesla). These are the companies either building the foundational models, writing applications on top of the foundation models, manufacturing the hardware needed to build the models, providing the infrastructure to power the equipment, or lending the money to make the capital spending possible. As shown in the table above, Energy and Industrials are the primary two sectors with some exposure to the AI trade that are performing better this year than they have since early 2023.
At this time, a move so highly correlated looks to me like more of a general sector rotation or de-risking than a changing of conviction in the market laggards. Once what I suspect is a general portfolio rebalance has permeated, which it may have as we pass the mid-point of the first quarter, we are looking to see if the constructive money is going to flow to new opportunities or return and “buy the dip” in the sectors that have worked the best in recent history.
Money Emigrating from US Equities to International Equities?
International equity has been making a strong move relative to the US over the last 2-3 months. That includes international equities of all types, emerging markets, developed markets, small cap, large cap and everything in between. The chart below shows, for the Emerging Markets ETF (EEM), EAFE ETF (EFA) and MSCI All-World ex-US ETF (ACWX), a green bar for every day that ETF was leading the S&P 500 on the trailing year, and a red bar for every day they lagged the S&P 500.
Source: Data from 1/1/2015 to 2/27/2026. SPY is the State Street SPDR S&P 500 ETF. EEM is the iShares MSCI Emerging Markets ETF. EFA is the iShares MSCI EAFE ETF. ACWX is the iShares MSCI ACWI ex-US ETF. For informational purposes only. For clarity of charting, this data only depicts Wednesdays and Fridays. Green = positive relative performance, Red = negative relative performance.
International equities have been putting up their best simultaneous streak of S&P 500 outperformance since 2018. This is true across almost every individual country ETF that we track data on.
Percent of Days Country was Beating S&P 500 on Trailing 3-Month Return
Source: Internal analysis of Bloomberg data. BlackRock iShares ETFs depicted here include: Chile = ECH; Denmark = EDEN; Finland = EFNL; Indonesia = EIDO; Ireland = EIRL; Israel = EIS; Norway = ENOR; New Zealand = ENZL; Philippines = EPHE; Poland = EPOL; Peru = EPU; Australia = EWA; Canada = EWC; Sweden = EWD; Germany = EWG; Hong Kong = EWH; Italy = EWI; Japan = EWJ; Belgium = EWK; Switzerland = EWL; Malaysia = EWM; Netherlands = EWN; Austria = EWO; Spain = EWP; France = EWQ; Singapore = EWS; Taiwan = EWT; United Kingdom = EWU; Mexico = EWW; South Korea = EWY; Brazil = EWZ; South Africa = EZA; China = FXI; India = INDA; Saudi Arabia = KSA; Qatar = QAT; Thailand = THD; Turkey = TUR; United Arab Emirates = UAE. Global X ETFs depicted here include: Argentina = ARGT; Colombia = COLO; Greece = GREK. Van Eck Vectors ETF depicted here is Vietnam (VNM). Data from 4/1/2023 to 2/27/2026.
So far in 2026, only 4 countries have trailed the S&P 500 by a greater percentage of days than they had in the prior period. When averaging each of the ETFs trailing performance by region, every single region is beating the S&P 500 on the trailing 3-month on every single day in 2026.
In this table, India and China are notable for underperforming US equities so far this year, and as the two most populous countries in the world with dynamic economies, they may present the most opportunity looking forward.
Will Low-Beta Securities Recover to Their Historical Norms?
This may begin to sound like beating the same drum over and over, but similar to the other trends, it was really hard to identify a basket of equities that did better than large cap US growth and momentum.
Source: Bloomberg. Data from 1/1/1992 to 2/27/2026. Beta is a statistic that measures the expected increase or decrease of an individual stock price in proportion to movements of the stock market. This is provided for informational purposes only.
Over the last few years S&P low volatility stocks have had anomalously low participation in equity market moves (i.e., they underperformed by more than expected) while high beta stocks have participated at their long-term average level (i.e., they overperformed exactly as expected). Because these betas were realized in a positive momentum-driven market, the low realized beta has been a hands down negative. That lower beta has become more of a positive characteristic lately, however, as growth (typically higher beta) has underperformed relative to value (typically lower beta) for much of the year to-date and it has paid to move out of step with the market.
Since roughly the beginning of the year, the low volatility equities have made up ground against the high beta equities (~34%), however, this is coming off the largest performance gap since the dotcom era.
Source: AIM internal analysis of Bloomberg data. S&P 500 Low Volatility uses the SPLV ETF; S&P 500 High Beta uses the SPHB ETF. Period depicted is 5/4/2012 (inception date of the ETFs) to 2/27/2026.
There have certainly been periods where low volatility has recovered slightly against high beta before continuing on its longer downward trend, so it’s quite possible this upward blip we’re seeing at the beginning of the year is one of those fake outs. However, it does coincide with other “broadening” movements including outperformance of foreign equities and better performance among laggard US equity sectors.
Conclusion
Our investment team likes to see more opportunity to find alpha in niche corners of the market. However, if this rotation is occurring, it’s going to be painful for a lot of investors that have gone all-in on the US growth/AI trade the last few years. Hence, the “Chinese” curse as our epigraph for this blog post. Interesting times create opportunity and pain. We are seeking to find more of the former as the markets continue to roil at the outset of 2026.
For more insights on all different topics, visit our blog: algomodels.com/our-thinking
Authored by Andrew Rice
Disclosures:
The information presented in this report is based on data obtained from third party sources. Although it is believed to be accurate, no representation or warranty is made as to its accuracy or completeness. The charts and infographics contained in this blog are typically based on data obtained from third parties and are believed to be accurate. The commentary included is the opinion of the author and subject to change at any time.
There is no guarantee that the investment objectives will be achieved. Past performance is no guarantee of future results.
Certain information contained herein constitutes “forward-looking statements,” which can be identified by the use of forward-looking terminology such as “may,” “will,” “should,” “expect,” “anticipate,” “project,” “estimate,” “intend,” “continue,” or “believe,” or the negatives thereof or other variations thereon or comparable terminology. Due to various risks and uncertainties, actual events, results or actual performance may differ materially from those reflected or contemplated in such forward-looking statements. Nothing contained herein may be relied upon as a guarantee, promise, assurance or a representation as to the future.
This material is provided for informational purposes only and does not in any sense constitute a solicitation or offer for the purchase or sale of a specific security or other investment options, nor does it constitute investment advice for any person.
The S&P 500 Index is an unmanaged index consisting of 500 large capitalization U.S. companies and is widely regarded as a measure of large cap U.S. equity performance. The MSCI Emerging Markets Index is an unmanaged index designed to measure the equity market performance of large and mid capitalization companies across emerging market countries. The MSCI EAFE Index is an unmanaged index designed to measure the equity market performance of developed markets outside of the United States and Canada including Europe Australasia and the Far East. The MSCI ACWI ex USA Index is an unmanaged index designed to measure the equity market performance of developed and emerging markets outside of the United States. The S&P 500 Low Volatility Index measures the performance of the 100 least volatile stocks within the S&P 500 Index based on realized volatility. The S&P 500 High Beta Index measures the performance of the 100 stocks within the S&P 500 Index that have the highest sensitivity to market movements as measured by beta.
[1] The source of this curse, popularly known as Chinese, is most likely early 20th century England.
