We wrote in last month's letter that the U.S. stock market had to meet lofty earnings expectations to maintain its strong performance relative to global benchmarks, while the latter had a lower bar because of considerably cheaper valuation multiples and higher dividend yields. Over the last month, investors have started to come around to this idea as well, with European and global non-U.S. stocks handily outperforming the S&P 500 and the Nasdaq 100 in February. The month also saw a major rally in yields as growth and inflation expectations were both revised downward on the month.
The good news is that, with Q4 earnings season wrapping up, S&P 500 firms have done well, with earnings coming in 7.15% above expectations on average. However, as a reflection of the lofty earnings expectations already baked into markets, sectors like technology (yellow arrow) which came in with positive sales and earnings surprises—1.1% and 4.16% for the tech sector respectively—still were met with a negative 1.4% price response on the day following the earnings release on average.
Though important, earnings news have been a bit overshadowed by the fast and furious pace of policy developments coming out of the Trump White House. There are endless reports of concerns about DOGE efficiency initiatives, tariff threats to economic growth, and the recent debacle of a meeting between Presidents Trump and Zelensky. Lost a bit in the recent news flow, however, is the Trump deregulatory agenda and the fact that—means of getting there aside—ending the war in Ukraine would be very beneficial for geopolitical stability, global markets, and Europe in particular. There are, of course, legitimate concerns about Trump’s policies—for example, potential interference in Fed policy and dollar interventions—but net-net our view is that the market positives may yet outweigh the market negatives.
Interestingly—as one of our clients pointed out earlier this week—investor sentiment measured by the AAII Investor Sentiment Survey hit an (almost) all-time low in February, surely a reflection of many of the above concerns.
This got us thinking about the market impact of this observation. Traditionally, this would have involved writing a bit of Python code to see what the historical implications of such low investor sentiment readings have been for year-ahead market returns. Instead, though, we collected the AAII sentiment data along with S&P 500 returns into a spreadsheet, and posed the question to Gemini. After a bit of back-and-forth about how to display the information, Gemini produced the following:
This table shows the AAII bullish sentiment survey deciles and the associated average one-year ahead returns in each decile, using data going back to 1986. The historically low level of investor sentiment puts us into the first decile bucket, which has historically been associated with high average year-ahead returns (of 22.9%). So perhaps the current brouhaha over President Trump’s policies will subside and markets will resume their upward march based on things like AI productivity boosts to the economy (and to this newsletter).
Based on the above analysis, we have now incorporated the AAII Investor Sentiment Survey series into our machine learning forecasting models at QuantStreet. So this is something our process will now consider without any further manual effort on our part.
Portfolio positioning
Our portfolio changes for the month ahead were relatively minor. We took our small India exposure down to zero based on a very poor trend in that country’s stock market. And we added to the Europe allocation which we initiated last month, based largely on our long-term valuation analysis, as well as potential positive catalysts from the end of the Ukraine war and a new, more business friendly government in Germany.
On the subject of portfolio positioning, over the last year, we’ve reviewed the portfolios that several of our clients had with other advisors. A few general observations:
- Client portfolios are often in very high fee (0.75% per year and often much higher) mutual funds or alternative investments. The strategies employed by these products are complex, often illiquid, and generally underperform lower cost, liquid ETFs offered by the likes of Vanguard and BlackRock. (The average fee of funds held in QuantStreet’s portfolios is around 0.045% per year.)
- In addition, clients often have separately managed accounts (SMAs) that run tax-loss harvesting strategies. Often these accounts lag the performance of benchmark indexes, like the S&P 500, and have a high cost (e.g., 0.35% per year or so) which arguably swamps any tax benefit that accrues from these SMAs for many investors.
- The net result of these investment choices is that client portfolio underperform lower cost benchmarks, as well as similar risk-level QuantStreet portfolios. Often the degree of underperformance is 3% per year (!) or even higher. As usual, you can see our performance numbers here.
If you think your portfolio with another advisor looks like the above, talk to us ([email protected]). We would be happy to review your portfolio and give advice on how it can be improved.
Working with QuantStreet
Harry Mamaysky is a professor at Columbia Business School and a partner at QuantStreet Capital.
QuantStreet is a registered investment advisor. It offers wealth planning, separately managed accounts, model portfolios and portfolio analytics, as well as financial consulting services. The firm’s approach is systematic, data-driven, and shaped by years of investing experience. To work with or learn more about QuantStreet, join our mailing list or contact us at [email protected].
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