Indexology^® Blog

2022 was a challenging year across asset classes, including equities. Exhibit 1 shows that there were declines across the U.S. equities market cap spectrum. For example, the S&P 500^® fell 18% for the whole year; the gains in the fourth quarter were not sufficient to overcome the declines during the first three quarters.

Amid the turbulent environment, S&P DJI’s U.S. equity indices fared well relative to their Russell counterparts, generally outperforming in most months over the past year. For instance, the S&P 500 outperformed the Russell Top 200 by 1.7% in 2022, its largest margin since 2011. The S&P SmallCap 600^® outperformed the Russell 2000 by 4.3%, far above its average annual outperformance since 1995 (1.7%), and the S&P 900 and S&P Composite 1500^® outperformed their Russell counterparts by 1.3% and 1.4%, respectively, both the third-highest margins since 1996.

Information Technology exposure was a key reason for the outperformance of S&P DJI’s indices last year. Exhibit 3 shows that the choice of Information Technology companies (selection effect) accounted for over 80% of the overall S&P SmallCap 600 outperformance against the Russell 2000. Other major S&P DJI’s indices tell a similar story: S&P DJI’s U.S. equity indices benefited from less exposure to, and better selection in, the Information Technology sector in 2022.

The outperformance from S&P U.S. Core Indices helped S&P Style Indices’ relative returns (see Exhibit 4). Most notably, the S&P MidCap 400 Growth outperformed Russell MidCap Growth by 7.8%, the largest margin since 2003. The S&P MidCap 400 Value outperformed Russell MidCap Value by 5.1%, the third-highest margin since 1996.

More broadly, Exhibit 5 shows how the frequency of outperformance by the S&P Style Indices generally increased with the frequency of outperformance by the S&P Core Indices. The frequency of outperformance is based on annual total returns of the S&P DJI indices and their Russell counterparts since 1996. The blue bars represent benchmark indices, while the other two colors represent S&P DJI’s outperformance conditional on the benchmark outperformance of respective style indices. For example, the S&P MidCap 400 outperformed the Russell MidCap index in 51.9% of years between 1996 and 2022. And in years when the S&P MidCap 400 outperformed, the S&P MidCap 400 Growth always outperformed the Russell MidCap Growth.

The past year was an extremely challenging time for the U.S. equity market, but the S&P Core and Style Indices generally outperformed their Russell counterparts. Once again, such differences in return highlight the potential impact of differences in index construction and how different index characteristics can impact relative returns.

The S&P GSCI, the world’s leading commodities benchmark, could not escape the volatile markets experienced in February, as the index fell 3.83% for the month. Despite recent declines, inflation remained high, which kept the U.S. Fed steadfast in its rate-hiking campaign, and expectations for a possible easing by year-end 2023 were squashed in the latest Fed commentary. A strong retracement higher of the U.S. dollar from the weakness seen in January put pressure on all major commodities, which are priced in U.S. dollars globally.

Within the petroleum complex, S&P GSCI Heating Oil took the biggest hit, down 9.33% after a flat January. Warmer-than-expected weather in the U.S. played a role in decreasing demand for the crude oil byproduct. Crude oil supply was ample, with no change in OPEC’s production announced and record volumes of crude exports to China and India from Russia’s Pacific terminals. Russian crude exports to northern European countries ceased after EU sanctions took effect on Feb. 5.

The S&P GSCI Industrial Metals fell 7.82% in February with broad weakness across all metals. Despite China’s easing of COVID-19 restrictions, demand from the world’s leading importer of industrial metals has not recovered yet. China’s latest forward-looking Manufacturing PMI reading showed the fastest growth in a decade, however. The S&P GSCI Nickel fell the most among the industrial metals, down 18.27%. The International Nickel Study Group announced that in 2022, the global nickel market flipped from a deficit to a surplus for one of the key metallic inputs to electric vehicles. The London Metal Exchange’s nickel contract is still in question after last year’s spike in prices, leading other exchanges like the CME to announce in February that they would launch an alternative nickel contract by the end of March.

The S&P GSCI Gold gave back all of its gains from January, ending February with a flat YTD performance. The S&P GSCI Silver fell 12.06% in sympathy with gold. Silver prices tend to be much more volatile than gold, to the downside as well as the upside. The pressure from the industrial metals space was also felt with silver’s global demand making up about 50% of its use.

Within agriculture, S&P GSCI Wheat prices fell the most, down 8.20% YTD. According to S&P Global Commodities Insights, global wheat prices are expected to see further declines due to the likely rise in supplies across producer countries such as Australia, Canada and Russia. After a year of tightened supplies from the start of the Russia-Ukraine conflict, supplies are likely to normalize.

The S&P GSCI Livestock rose 1.29% and was the only sector to end the month in positive territory, with feeder cattle and live cattle leading the way. Cattle prices have risen steadily since their low in May 2022 due to a progressively smaller global herd and global demand remaining strong.

Traditional investors think of portfolios (whether active or indexed) as collections of stocks. We can equally well think of portfolios as collections of factors—defining factor in the academic sense, as an attribute with which excess returns are thought to be associated. If we’re correct in assessing these attributes, it should be possible to explain portfolio performance by reference, not to the stocks that the portfolio owns, but rather to the factors that it embodies.

One way to illustrate this is with reference to factor indices.  It’s obvious, e.g., that a well-constructed value index is tilted toward cheap stocks (i.e., toward the value factor), but it’s equally true, if less obvious, that a value index might have other tilts as well—for example, toward smaller companies, or higher yields, or lower quality. If this is true, then the performance of factor indices might be explained, in part, by reference to multiple factor exposures.

We’ve noted before that one of the most salient features of 2022 factor index performance was the reversal of several multi-year trends. Equal weight beat cap weight, Low Volatility beat High Beta, and most strikingly, Value outperformed Growth. The Value–Growth differential was so large, in fact, that it explained nearly 80% of the variance in returns across other factor indices, as Exhibit 1 illustrates.

Exhibit 1, though interesting, relies on data from only 17 factor indices. Some stocks will be represented in several of these indices, while others might not be included in any. What happens if we ask how factor exposure affected performance at the individual stock level?

We can approach this question by ordering the constituents of the S&P 500 by the factors of interest, grouping into quintiles, and then measuring returns by quintile. The difference between top and bottom quintiles (i.e., between the average return of the stocks most exposed to the factor and the average return of those least exposed) gives us a convenient way to summarize each factor’s influence. Exhibit 2 shows results for 2022.

Yield was the year’s strongest factor by far, as the market’s highest dividend payers beat non-payers by nearly 29%. Value was in second place, with defensive stalwarts Quality and Low Volatility filling out the top four places. The difference between the performances of Value and Growth is quite consistent with the observations we made in Exhibit 1.

Other things equal, as granularity increases, the importance of factors declines. An individual stock will be more heavily influenced by idiosyncratic factors than will be a diversified portfolio. Even at the stock level, however, understanding factor exposures can produce useful performance insights.

I confess some superhero powers underwhelm me (really, Hawkeye, arrows?) or stretch credulity further than Hulk’s hyper-elastic jeans. However, one I can appreciate is Mystique, the shape-shifting mutant who constantly alters her appearance to stay one step ahead.

If factors were superheroes, I’d argue the S&P 500^® Momentum Index (“Momentum”) and Mystique share commonalities, both misunderstood and powerful through constantly morphing into something new. As a reminder, the momentum factor refers to the tendency of outperforming stocks to continue outperforming in the near term.

Thirty years after the publication of perhaps the most cited paper on momentum, researchers continue exploring why it works. To some, the momentum premium is simply compensation for risk, while others attribute it to human behavioral biases such as loss-aversion or self-attribution. In other words, markets are made up of people who don’t always act rationally, and many don’t understand momentum. Let’s bust three common misperceptions about momentum using data from the S&P 500 Momentum Index (Mystique-blue in the charts below, naturally).

Myth 1: Momentum Is Just Risky or High Beta Stocks

While the S&P 500 High Beta Index (“High Beta”) selects the 100 highest beta stocks from the S&P 500, Momentum selects constituents with top-quintile risk-adjusted price return momentum scores. Resulting differences between High Beta and Momentum indices have historically led to only a 2% overlap and a -0.54 relative return three-year correlation. Performance also underscores the uniqueness of each factor. Just during January 2023, the performance of High Beta and Momentum differed by 17%—their fourth-highest spread since 2010.

Looking over a longer time horizon, data show an often inverse relationship between excess returns for High Beta and Momentum (see Exhibit 1).

Longer-term performance also highlights the differences (see Exhibit 2).

A keen eye finds that Momentum outperformed on a relative basis for the 2022 calendar year, perhaps busting the second part of Myth #1 that the factor is inherently higher risk. In reality, the S&P 500 Momentum Index selects stocks that rank highly on risk-adjusted performance, leading to an index with annualized risk that has historically been similar to or below that of the S&P 500 (see Exhibit 3).

If momentum indices can actually be constructed with similar or less volatility than the broader market, then we can begin addressing the second myth.

Myth 2: Momentum Only Works in Bull Markets

When the S&P 500 declined 18.1% in 2022, the S&P 500 Momentum Index outperformed, falling 10.5%. Curious about Momentum’s resilience, we examined its average excess performance during one-month periods when the S&P 500 was rising or falling. As seen in Exhibit 4, Momentum outperformed in both on average.

Clearly for momentum to work in different conditions, it must transform as the factor itself moves across different parts of the market. The most market-based among factors, Momentum has a historically high turnover, which leads to our final myth. 

Myth 3: The Momentum Factor Can’t Be Indexed.

Put differently, can indices continue to harness a factor like momentum through time? Affirmation comes from the fact that many “passive” indices (such as factors) are quite dynamic in how they rebalance.

Momentum “shapeshifts,” dramatically changing security and sector weights at rebalances to maintain high exposure to the targeted factor (see Exhibit 5).

Like Mystique taking on different forms, the S&P 500 Momentum Index is always changing by design, evolving in response to market conditions and maintaining a high exposure to the factor along the way.

As the world continues to focus on sustainability and the energy transition, it is understandable that market participants are seeking to incorporate sustainability considerations into their commodities portfolios. To that end, on Feb. 23, 2023, S&P Dow Jones Indices (S&P DJI) launched the S&P GSCI Climate Aware, utilizing a new environmental dataset developed in collaboration with S&P Global Sustainable 1. It is the first broad-based commodity index in the market to incorporate environmental metrics.

The S&P GSCI Climate Aware measures performance through futures of a long-only climate-aligned and climate-transition strategy across the constituents of the S&P GSCI. The index follows a portfolio optimization approach to compute constituent weights by seeking to reduce the environmental footprint of the index, while minimizing weight and sector deviations from the S&P GSCI. The optimized constituent weights are constrained to help maintain diversification, investability and liquidity for the index. The index seeks to achieve a 25% reduction in total environmental impact per dollar invested compared with the S&P GSCI, along with a 5% year-over-year decarbonization target, while maintaining total food production and ensuring land and water environmental impact per dollar invested are no higher than the S&P GSCI. Exhibit 1 provides back-tested performance and summary statistics for the index compared with the benchmark.

As environmental considerations come under the scope, market participants have expressed interest in maintaining diversified exposure to an inflation-sensitive asset in line with the benchmark S&P GSCI, while shifting allocations between commodities that may be substitutes, reflecting as closely as possible behaviors in the physical market that may be central to the transition. As such, the index redefines new commodity “sectors” to reflect the changing dynamics of the global economy, dividing the constituents into three economic sectors based on their impact on the environmental transition and currently available substitutions within each category: energy systems, food supply and other. As anticipated, the new index reallocates weights away from high-intensity fossil fuels to those metals important to the energy transition (see Exhibit 2).

The index utilizes a new set of environmental data—the S&P Global Commodity Environmental dataset—which provides physical and financial impact data on greenhouse gas emissions, water consumption and land use at the commodity level, based on life cycle impact assessment factors and natural capital valuation metrics. More information on the dataset can be found here.

S&P DJI continues to be the leader when it comes to bringing innovative, sustainability-focused index offerings to the market. The S&P GSCI Climate Aware is another example of how we look to drive transparency and incorporate sustainability criteria into our benchmark indices. To learn more, please visit the index webpage, or read about incorporating environmental considerations into commodities indices in our research paper published in February 2023.