Why the Benefits of Betting on Industries and Countries Are Few and Far Between
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Evidence for pursuing premiums at the industry and country levels is not convincing when compared with pursuing premiums at the stock level.
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The size, value, profitability, and momentum premiums of individual stocks do not consistently carry over to the industry and country levels.
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Those few premiums found to have potentially reliable value relative to stock-level premiums lack robustness or require high turnover.
Size, value, profitability, and momentum are well-known drivers of stock returns. Since they work for individual stocks, shouldn’t they also work in the aggregate? Do industries and countries that are smaller, deeper value, more profitable, and experiencing upwards momentum outperform on average? If so, should you overweight them in your asset allocation?
In a recent paper, we examined these questions through the scientific scrutiny we believe any investment idea should undergo. In short, we found the benefits of pursuing systematic premiums “top down” to be few and far between, especially for investors already pursuing the premiums “bottom up.”1 Exhibit 1 illustrates our main results using US value and growth portfolios at the industry and stock levels.
Value vs. Growth at the Industry Level vs. the Stock Level
Past performance is no guarantee of future results.
Any Priors?
Before diving into the data, it’s a good idea to form a prior about what you might see. This can mitigate the risks of a blind search for patterns that might occur simply by chance.
Is it reasonable to expect premiums at the industry and country levels? On one hand, the size, value, profitability, and momentum premiums are well documented among individual stocks. It’s therefore not a big stretch to imagine them carrying over to industries or countries.2 On the other hand, there are far fewer industries and countries than individual stocks. So, using industries and countries as building blocks can lead to relatively poorly diversified portfolios, prone to noisier realized returns. Which of these effects dominates is ultimately an empirical question.
Let the Data Speak
We looked at the historical performance of the industry-level size, value, profitability, and momentum premiums in the US, in non-US developed markets, and in emerging markets. We did the same for the corresponding country-level premiums in developed markets (including the US) and emerging markets. The period is 1975–2021 for the US industry premiums and 1994–2021 for the remaining premiums.3
Across all the premiums we considered, only the ones associated with profitability and momentum showed some statistical reliability, though not consistently so. More profitable industries reliably outperformed less profitable ones in the US, and the same was true for countries in developed markets, but not for industries outside the US or for countries in emerging markets. Similarly, winner industries reliably outperformed loser industries across all markets, and the same was true for countries in developed markets, but not for countries in emerging markets.
Is It Additive?
Looking at the reliability of return spreads is important, but it’s only the first step. Anything can appear useful in a vacuum, but that doesn’t mean it’s additive to what we already know. We need to see if those few reliable return spreads add reliable value for an investor already pursuing the premiums bottom up. That is, if they have reliable “alpha” relative to the stock-level premiums.4
Doing so shortens the list of potentially useful industry and country premiums to just two: the country-profitability premium in developed markets and the industry-momentum premium in emerging markets.
Is It Robust?
For an investment strategy to be viable, it should be robust. It’s a red flag if a slight change to a strategy’s construction leads to a material deterioration in performance.
This lack of robustness is the case for the country-level profitability premium in developed markets: Its performance is highly sensitive to the inclusion of Japan. Over our sample, Japan is never in the high-profitability portfolio, but it has a lot of influence on the performance of the low-profitability portfolio. Excluding Japan, the premium becomes statistically unreliable, and the same is true for its alpha.
Is It Practical?
Research portfolios like the ones in our paper are useful for studying the long-term performance of premiums in a simplified setting. But there’s a long way from paper portfolios to real-world strategies.
Recall that we found a reliable alpha for industry momentum in emerging markets. A major practical hurdle for capturing momentum premiums, however, is their rapid decay. Experiencing upwards or downwards momentum is typically a short-lived state, which means chasing momentum premiums requires a lot of turnover. High turnover can result in high trading costs that materially attenuate the returns achievable in practice.
Assuming monthly rebalancing, as is typical in the academic literature for momentum portfolios, the annualized one-way turnover averaged 500% for industry momentum in emerging markets. This means the underlying portfolios on average fully replaced their holdings five times per year. For comparison, the annualized one-way turnover for academic portfolios pursuing the stock-level size, value, and profitability premiums is typically 15%–35%.5 If one instead assumes semiannual or annual rebalancing to curb the momentum portfolios’ high turnover, the alpha is more than halved and is no longer reliable. This makes it impractical to chase industry momentum.
Judgment Call
It’s unrealistic to expect an investment idea to work everywhere all the time. There are exceptions to every rule, and the volatility of returns implies noisy inference.
Nonetheless, for an investment idea to be viable, we believe it should have convincing evidence in its favor when subjected to scientific scrutiny. The idea of pursuing well-known style premiums at the industry and country levels does not, in our view, clear that hurdle, especially compared to pursuing the premiums at the stock level.6 Stated differently, pursuing the premiums at the stock level appears to be sufficient.
Building portfolios from industries and countries is ultimately like settling for a low-resolution image of the stock market. If you squint, you might be able to recognize what’s underneath the blur, but there’s an undeniable loss of information.
Footnotes
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1 See Dong, Huang, and Medhat (2023).
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2 For the size, value, and profitability premiums, we have simple economic intuition for why we see them in the data. Together, a company’s size, relative price, and profitability capture the price you pay and the cash flows you expect to receive from holding a stock. All else being equal, the less you pay or the higher the expected cash flows, the higher your expected return. Therefore, smaller, deeper value, and more profitable stocks are expected to outperform. For the momentum premium, the jury is still out on why exactly we see it in the data, but its pervasiveness as an empirical finding is undeniable, at least before trading costs.
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3 The premiums are measured as the average monthly return spreads between the highest- and lowest-ranking portfolios from sorts on aggregate market cap (size), book-to-market equity (value), operating profits-to-book equity (profitability), past one-month performance (“1–1” momentum), and past one-year performance skipping the most recent month (“12–2” momentum). Each of the high and low portfolios contains roughly 30% of the number of investable industries or countries. The industry sorts are done country by country, then aggregated to the regional level. Monthly portfolio returns are market-cap-weighted averages. We use USD returns and market-cap values throughout.
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4 There’s a general point to be made here: Any claim of “alpha” should be followed immediately by the question “relative to what?” Many strategies that have alpha relative to the market do not have alpha relative to well-known premiums, meaning they are merely a way to repackage those premiums, not an additional source of returns. See, for instance, Fama and French, (2010, 2016).
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5 See, for instance, Novy-Marx and Velikov (2016).
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6 Does this mean we can conclude that no industry or country bet will add value for a given investor? Not necessarily. The scope of our paper is limited to systematic industry and country bets corresponding to premiums well-known at the stock level. An investor might have practical or tactical reasons for favoring certain industries or countries, and this might in fact appear to add value over certain time periods. But, by its very nature, it’s difficult to test in a scientific manner whether any such value-add is a result of luck or skill. As a start, investors should ask whether the realized performance of industry or country bets correspond to a measurable alpha relative to stock-level premiums.
index Description
Fama/French US Value Research Index: Provided by Fama/French from CRSP securities data. Includes the lower 30% in price-to-book of NYSE securities (plus NYSE Amex equivalents since July 1962 and Nasdaq equivalents since 1973).
Fama/French US Growth Research Index: Provided by Fama/French from CRSP securities data. Includes the higher 30% in price-to-book of NYSE securities (plus NYSE Amex equivalents since July 1962 and Nasdaq equivalents since 1973).
References
Dong, A. and M. Huang and M. Medhat. 2023. “Few and Far Between: Why Pursuing Premiums at the Industry and Country Levels Does Not Add Value.” Available at SSRN: https://ssrn.com/abstract=4398439.
Fama, E. F. and K. R. French. 2010. “Luck versus Skill in the Cross-Section of Mutual Fund Returns.” Journal of Finance 65, no. 5: 1915–1947.
Fama, E. F. and K. R. French. 2016. “Dissecting Anomalies with a Five-Factor Model.” Review of Financial Studies 29, no. 1: 69–103.
Novy-Marx, R. and M. Velikov. 2016. “A Taxonomy of Anomalies and Their Trading Costs.” Review of Financial Studies 29, no. 1, 104–147.
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