Non-U.S. Small Caps: A Call to Inaction
Key Takeaways
We extend our research on the performance of small-cap stocks in the United States1 to other developed markets (DM).
We attribute a recent 2 ½-year bout of weakness in DM ex-U.S. small caps to a confluence of transient macro and idiosyncratic risks. Assessing their outlook afresh, we view these stocks as fairly priced relative to large caps given expectations for fundamentals.
We conclude that investors should stay invested and active in non-U.S. small caps. This relatively inefficient market segment offers alpha generation opportunities that merit an overweight relative to the cap-weighted market portfolio.
Endnotes
- U.S. Small-Cap Performance: Relatively Bad but Absolutely Fine, Acadian, June 2024.
- Ang, Andrew, Amit Goyal, and Antti Ilmanen, “Asset allocation and Bad Habits.” Rotman International Journal of Pension Management 7, issue 2 (Fall 2014): 16-27.
- Across DM ex-U.S., there is a strong relationship across firms between their market capitalizations and revenue derived from their home region. For companies with market caps from $1-$10B, $10-50B, and $50B+, medians are 78%, 53%, and 44%, respectively.
- GRANOLAS is an acronym for high-quality European bellwethers that analysts coined in April 2020 (GlaxoSmithKline, Roche, ASML, Nestle, Novartis, Novo Nordisk, L'Oreal, LVMH, AstraZeneca, SAP, Sanofi). References to these and other companies should not be interpreted as recommendations to buy or sell specific securities. Acadian and/or the authors of this paper may hold positions in one or more securities associated with these companies.
- As of September 2024, MSCI’s U.K. Large Cap Index had a 21.7% in the two sectors versus only 8.3% for the Small Cap analogue. Source: MSCI factsheets.
- See U.S. Small-Cap Performance: Relatively Bad but Absolutely Fine, previously cited.
- The Capital Asset Pricing Model justifies a high bar for deviations from the market portfolio. Heaton, Polson, and White (2017) provide an alternative rationale. Based on a model calibrated to historical data, they argue that randomly selecting a subset of the market portfolio, similar to taking strategic underweights, can significantly increase the probability of long-term underperformance. See Heaton, J. B., N. G. Polson, and J. H. White, “Why Indexing Works.” Applied Stochastic Models in Business and Industry 33, issue 6 (November/December 2017): 690-693.
- To see earnings growth expectations back on an equal footing with large is consistent with longer-term history. Since 1990, price-to-cash-earnings multiples of non-U.S. small caps have both exceeded and trailed those of large caps for extended periods. In other words, market prices have not, over the long term, consistently impounded higher expected long-term earnings growth rates for small caps than large.
- If anything, the macro environment provides us with some near-term optimism regarding the relative prospects of small caps outside of the United States. Figure 3 shows that in Europe, Japan, and especially the U.K., consumer confidence has rebounded significantly from historically weak levels of 2022, surpassing what we see in the U.S. (Figure 3, top chart).
- To be clear, the variation in aggregate small-versus-large weighting does not require the forecasting model to include an explicit “small-versus-large” component. The aggregate small-cap weighting would also depend on variation in risk and transaction costs among small stocks versus large.
- Investors who are sensitive to size risk should consider long-short extensions as an alternative to long-only portfolios. While taking leverage involves risk and complexity, relaxing the long-only constraint allows for more flexibility to exploit the small-cap opportunity set by offsetting attractive longs with attractive shorts. For further discussion, see Thinking Broadly: Improving Active Performance Via Systematic Extensions, Acadian, October 2023.
Hypothetical
Acadian is providing hypothetical performance information for your review as we believe you have access to resources to independently analyze this information and have the financial expertise to understand the risks and limitations of the presentation of hypothetical performance. Please immediately advise if that is not the case.
Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between hypothetical performance results and the actual performance results subsequently achieved by any particular trading program.
One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
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