Indexology^® Blog

As high inflation, rising interest rates and geopolitical risks dominated the headlines in 2022, technology stocks had a particularly difficult year. Given the many headwinds facing the sector, the S&P Total Market Index (TMI) Information Technology returned -30.20% in 2022. In spite of the challenging market environment, the S&P Technology Dividend Aristocrats^® Index fared relatively well, dropping about one-half the amount of the S&P TMI Information Technology, representing an outperformance of 14.66%. In this blog, we will analyze the S&P Technology Dividend Aristocrats index methodology as well as examine its dividend emphasis and style tilts.

Methodology Overview

The universe for the S&P Technology Dividend Aristocrats Index is the Information Technology sector and the Internet & Direct Marketing Retail, Interactive Home Entertainment, and Interactive Media & Services GICS sub-industries in the S&P TMI.

To be selected, a company must have increased its dividends per share (DPS) every year for at least seven consecutive years. If the number of constituents is less than 25, the DPS increase history can be shortened to four years.¹ The emphasis on increasing dividends per share could provide a ballast for investors, since the ability to consistently grow dividends through different economic environments can be an indication of financial strength and discipline.

All constituents are equally weighted. This ensures broad diversification and reduces concentration risk. Lastly, the index is rebalanced annually and reweighted quarterly.

Risk/Return Profile

The S&P Technology Dividend Aristocrats Index outperformed both the S&P TMI Information Technology and the S&P TMI over the one- and three-year periods. Furthermore, on a risk-adjusted basis, the S&P Technology Dividend Aristocrats Index outperformed both benchmarks over all periods shown, except for the five-year period versus the S&P TMI Information Technology (0.50 versus 0.51). Importantly, the S&P Technology Dividend Aristocrats Index had lower volatility than the S&P TMI Information Technology for all periods.

Historical Dividend Growth and Dividend Yield

From Dec. 31, 2014, to Dec. 31, 2022, the S&P Technology Dividend Aristocrats Index increased its annual dividends by an annualized 14.72%, while S&P TMI Information Technology and S&P TMI Index increased their annual dividends by an annualized 11.30% and 6.42%, respectively.

Exhibit 3 shows the annual trailing one-year dividend yield from Dec. 31, 2014, to Dec. 31, 2022. In every year over this period, the S&P Technology Dividend Aristocrats Index had a higher dividend yield than both the S&P TMI Information Technology and S&P TMI. On average, the S&P Technology Dividend Aristocrats Index had a dividend yield of 1.96%, while the S&P TMI Information Technology and S&P TMI had dividend yields of 1.12% and 1.73%, respectively.

Factor Exposure

In Exhibit 4, the S&P Technology Dividend Aristocrats Index demonstrated a value and dividend yield tilt versus the S&P TMI Information Technology. Specifically, the S&P Technology Dividend Aristocrats Index had higher Axioma Risk Factor Z-scores for the book-to-price and dividend yield factors, similar exposure to earnings yield and lower exposure to growth factors. The value and dividend tilt proved beneficial in the rising interest rate environment in 2022. Holding all else equal, value and dividend stocks offered relatively more protection in a rising interest rate environment compared with growth stocks, due to their lower durations.

Furthermore, both the S&P Technology Dividend Aristocrats Index and S&P TMI Information Technology showed higher quality characteristics (lower leverage and higher profitability) than the S&P TMI.

Industry Composition

Exhibit 5 shows the industry composition of the indices as of Dec. 31, 2022. The S&P Technology Dividend Aristocrats Index underweighted Software (driven by an underweight in Microsoft) and Technology Hardware Storage/Peripherals (driven by an underweight in Apple), and had a material overweight to the Electronic Equipment Instruments/Components industry.

Conclusion

Due to its emphasis on selecting companies with steady dividend increases, the S&P Technology Dividend Aristocrats Index has historically provided a solid risk-adjusted outperformance over both short- and long-term periods, a superior dividend yield and a value factor tilt in comparison with the S&P TMI Information Technology. For market participants who are interested in the technology sector and would like to have the potential for both dividend income and capital appreciation, the S&P Technology Dividend Aristocrats Index might be worth consideration.

¹ Please refer to the S&P Technology Dividend Aristocrats Index Methodology for more details.

Some commentators have argued that today’s market environment—characterized by rising rates and economic growth concerns—is a ripe environment for stock pickers.

This argument is conditionally correct, as long as we remember that having the opportunity to add value does not guarantee that value gets added. In today’s environment, active managers have good potential to add value. Dispersion and correlation provide an analytic context:

• Active managers should prefer above-average dispersion because stock selection skill is worth more when dispersion is high.
• The role of correlation is more nuanced. When correlations are high, the benefit of diversification falls. Therefore, managers should prefer above-average correlations because they reduce the opportunity cost of a concentrated portfolio.

In Exhibit 1, we observe that the 12-month average dispersion of the S&P 500^® has widened since 2014, while correlations have been relatively high. Higher dispersion also offers greater opportunities for active rotational strategies among countries, sectors and factors. In January 2023, we saw the highest spread between the best and worst equity factor indices since February 2021.

Active managers typically assume incremental volatility in the hope of earning incremental returns. How high must those returns be to justify the additional volatility active managers take on? The cost of concentration helps answer this question. When correlations are low, concentrated active managers incur substantially more volatility than diversified index funds. A higher cost of concentration implies a larger foregone diversification benefit, translating into a higher hurdle for active managers to overcome.

Multiplying the cost of concentration by a rate of return consistent with the market’s historical performance, we arrive at the required incremental return shown in the top half of Exhibit 2 for the S&P 500. Driven by the higher correlations seen in Exhibit 1, this measure declined by almost half in the last 12 months, to levels not seen since mid-2012, indicating that active managers gave up a much smaller diversification benefit in 2022 compared to 2021.

The bottom half of Exhibit 2 divides the required incremental return by dispersion to translate the measure into dispersion units. We can interpret a lower number of dispersion units to mean easier conditions for active management. As both dispersion and correlations were generally higher in 2022, we observe a relatively auspicious environment for active management.

While favorable conditions do not guarantee favorable active results, last year’s relatively fortuitous conditions for stock selection may have aided manager outperformance. Just 51% of large-cap active managers lagged the S&P 500 in the first half of 2022, compared to 85% in 2021. When SPIVA^® results for year-end 2022 become available, it would not be surprising to see U.S. large-cap equity funds post their lowest underperformance rate since 2009.

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Index funds, which hardly existed 50 years ago, now play a prominent role in global financial markets. But passive investing does not dominate in every market segment. Recently, we have seen exponential growth in so-called “thematic” investing, with a proliferation of themes in areas like cybersecurity, robotics and electric vehicles. This more granular space is sometimes perceived to offer greater opportunities for active stock selection, as opposed to an index-based approach.

In traditional categories, passive investors have benefited substantially by saving on fees and avoiding active underperformance. Our recently released paper, The Case for Indexing Thematics with the S&P Kensho New Economies, shows that very similar principles may apply to the thematics space.

In the case of broad equity markets, one important cause of the difficulty in outperforming through the selection of single stock “picks” is that in most markets, the distribution of single stock returns is positively skewed, with the result that only a minority of constituent stocks outperform the index, particularly as the time horizon extends. The universe of stocks defined by the S&P Kensho New Economies Composite Index proves to be no exception. Exhibit 1 plots the distribution of cumulative returns of the index constituents over the past four years: the median return of -9.7% is far less than the average of 17.3% and, during the period, only 37% of stocks outperformed the index.

This highlights the difficulty for thematic active managers seeking to outperform with concentrated portfolios, because when faced with a distribution of returns that is positively skewed (like in Exhibit 1), holding more stocks increases the likelihood of outperformance. The problem is of particular concern in the thematics space because, given the inherently granular nature of certain themes, the challenge of avoiding undue concentration is especially germane. For example, there are only 31 constituents within the S&P Kensho Robotics Index, one of the 25 subsectors that make up the 559 constituents within the S&P Kensho New Economies Composite Index (as of Dec. 30, 2022). In addition to being diversified across themes, the composite index’s concentration is further mitigated by a modified equal-weight approach applied in the construction of each subsector. The result of all of which is an index that is less concentrated than would be the case if a simple market-cap weighting scheme were followed.

Exhibit 2 illustrates the relative difference in concentration levels observed in the S&P Kensho New Economies Composite Index, its market-cap-weighted equivalent, and the average of the 20 largest actively managed thematic funds. We use a simple measure of concentration, namely the aggregate weight of the 10 largest constituents, because it is freely available for the active funds; interested readers can find further analysis of index concentration in our paper.

The largest active funds appear, on average, much more concentrated that the S&P Kensho New Economies Composite Index, with on average 35% of their portfolios’ weight in the top 10 holdings, compared to only 10% for the index. Meanwhile, if the composite index was capitalization weighted, its concentration levels would have been even higher, with 43% of its weight in the top 10 holdings.

Considerations such as these help explain why thematic investing may be ripe for “indicization,” in which the well-known benefits of passive investing might be captured through benchmarks such as those in the S&P Kensho New Economies.  In short, thematics appears to be yet one more segment of the investment landscape where, to put it simply: indexing works.