Indexology^® Blog

There was a notable reversal of fortunes across the commodities complex in May. The S&P GSCI was down 8.2% for the month but remained up 8.5% YTD. The Dow Jones Commodity Index (DJCI) was down 3.6% in May and up 3.7% YTD, reflecting its lower energy weighting. A sharp correction in petroleum prices combined with ongoing weakness in industrial metal prices weighed on the broad commodities indices’ performance over the month. The U.S. Administration’s penchant for utilizing trade restrictions as a negotiation tool for everything from lowering illegal immigration, to penalizing the unauthorized use of intellectual property, to reestablishing dominance over its closest neighbors has undoubtedly muddied the fundamental supply and demand dynamics of the majority of commodities markets.

Oil prices fell abruptly in May, as trade wars fanned fears of a broad economic slowdown. The S&P GSCI Petroleum dropped 13.8% in May, when the supply issues that had preoccupied the energy markets for much of the year gave way to concerns regarding the resilience of demand and the long-term implications of the reinvigorated trade dispute between the world’s two largest economies, the U.S. and China. Oil market participants will now turn their attention to the upcoming OPEC meeting, scheduled for June 25, 2019, where it is becoming increasingly likely that there will be an agreement among the OPEC+ members to continue, or even deepen, production cuts with the lofty goal of maintaining global oil market stability.

The S&P GSCI Industrial Metals gave back all of its YTD gains in May, falling 5.5% for the month. The S&P GSCI Copper and S&P GSCI Zinc led the way down, falling 9.1% and 9.2%, respectively, in May. These two metals are highly correlated with trade war sentiment, which deteriorated markedly over the month. Zinc continued to fall from its highs in Q1 2019 after revised expectations for a supply surplus this year, with China’s zinc output forecast rebounding by 5.3%. Associated with the trade war, heightened risks of a global growth slowdown also weighed on industrial metals, with China’s manufacturing PMI reading below expectations at 49.4 in May.

With the present ambiguity across commodity and equity markets, it is somewhat surprising that gold only attracted lackluster interest from investors in May. The S&P GSCI Gold was up 1.7% over the month, leaving its YTD performance only marginally positive. The U.S. dollar slowed its year-long appreciation, moving sideways in May and adding to the list of reasons why the gold market has been relatively featureless.

The S&P GSCI Agriculture rallied 9.7% in May. Having severely lagged the energy and industrial metals markets during the first four months of the year, a spark was lit under the grain markets in May. Wet and rainy conditions have severely delayed the grain planting season in the U.S., and this encouraged a level of excitement in the markets that has not been witnessed for a number of years. The most recent USDA crop report showed that only 58% of the corn crop had been planted by May 26, 2019, down from 92% last year and from the 90% five-year average. Both the S&P GSCI Corn and S&P GSCI Wheat were up 18% for the month. In contrast, the S&P GSCI Cotton fell 11.1% in May, plagued by the trade conflict between China and the U.S. China is the largest importer and user of raw cotton and the U.S. is a top buyer of Chinese textile products.

The frenzy in the grains market spilt over into the livestock markets in May, but with the opposite effect, given that grain is a major component of livestock feed. The S&P GSCI Livestock was down 6.5% in May.

Coming into month-end, and as the street prepares its monthly summaries, (all figures are as of May 29^th), the S&P 500 looks set to complete the month with a loss of around 5%.  So, what went wrong?  Global markets started the year very positively: the S&P 500 was up 18% by the end of April, while the S&P Global BMI had gained 16%.  Yet, the adage to “Sell in May and go away” looks to have been prescient advice this year.  Macro themes have returned, driving a wide spread in sector, factor, and country performances; volatility has also returned … although not as significantly as you might think.

Macro fears

The ongoing trade dispute between China and the United States provided the dominant theme in May, as both sides dug in their heels and prepared for a prolonged battle – creating uncertainty in both the investor and business communities.  Bond markets in particular demonstrated the flight to safety, as the 10-Year U.S. Treasury yield hit a twenty-month low, closing at 2.24%, and the 10-Year German Bund yield dropped to -0.18%.  Further, despite the U.S. economy growing 3.2% in Q1, the inversion in the U.S. yield curve continued to strengthen, stirring fears of recession.  While the current backdrop of economic strength seems like an unlikely environment for additional monetary stimulus, some believe there will be a rate cut from the U.S. Federal Reserve later this year – which added to the degree of inversion in the belly of the curve.

Divergence

While the broader market declined, sector, factor and single-country performances provided opportunities for selective investors.  Broadly speaking, defensive sectors outperformed, while trade-sensitive sectors struggled.  The S&P 500 Information Technology and Materials sectors declined 8% and 7%, respectively, while the Energy sector dropped 9% on oversupply concerns coupled with slowing global demand.

As was the case in sectors, defensive factors came back in vogue, with Low Volatility leading the way and High Beta bringing up the rear.  Momentum outperformed, which sounds counterintuitive but actually makes sense when you consider the timing of the mid-March rebalance for the index, when defensive constituents boasted market-beating one-year trailing returns.

In aggregate, markets included in the S&P Developed BMI outperformed those in the S&P Emerging BMI, but single-country performances were particularly dispersed.  Unsurprisingly, given the trade uncertainties, China struggled, with the S&P China BMI declining 12%.  Indian equities rebounded following the confirmation that Prime Minister Modi would get a second term, gaining 0.3% and outperforming all other Emerging Market country equity markets except for Russia and Greece, which gained 2% and 1%, respectively.  Frontier market Argentina beat them all, gaining 15% (all figures in USD terms).

Volatility … or a lack thereof

VIX® closed last night at 17.90, higher than it has been recently but not high by historical standards.  Given the perceived panic of trade concerns, it feels surprising that VIX isn’t higher.  One perspective is that the divergence in the performance among market segments has improved the level of diversification in the S&P 500; or it could be that – despite the cruelty of May – market participants think we’ll weather the storm and get back to growth in June.

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The S&P/TSX 60 gained 15.5% YTD[i] and many companies included in the index have benefitted from business prospects in the U.S. While nearly all stocks in the index are domiciled in Canada, 49%[ii] of combined revenues come from within Canada’s borders, while another 30% are sourced in the U.S. As shown in Exhibit 1, stocks with significant U.S. exposure have outperformed, contributing to gains of the S&P/TSX 60.

The S&P/TSX 60 U.S. Revenue Exposure Index, which is designed to measure companies from the S&P/TSX 60 with higher than average exposure to the U.S., outperformed the benchmark by 5.8 percentage points YTD. Meanwhile, the S&P/TSX 60 Canada Revenue Exposure Index, which is designed to measure companies from the S&P/TSX 60 with higher than average exposure to Canada, underperformed by 1.5 percentage points as of May 27, 2019.

Sector weight variations of each index, as shown in Exhibit 2, help explain the recent performance differences. Canadian Financials and Communication Services companies tend to gain a larger proportion of revenues from domestic sources. Energy and Information Technology companies, meanwhile, gain greater revenues outside of Canada.

Greater domestic focus of Communication Services and Financials sectors—shown in Exhibit 3—have been a hindrance to the S&P/TSX 60 Canada Revenue Exposure Index in 2019. Meanwhile, the outperformance of Energy and Information Technology companies have led to the improved returns of the S&P/TSX 60 U.S. Revenue Exposure Index.

While the S&P/TSX 60 comprises top companies in leading Canadian industries, over half of combined revenues are sourced from outside the country. Those companies earning significant revenues outside of Canada have boosted the YTD gains of the flagship index.

[i]   Source: S&P Dow Jones Indices LLC, total return data in CAD as of May 27, 2019.

[ii]   Source: Revenue exposure data from Factset, LLC, data as of May 27, 2019.

Australian Listed Equities

The Australian listed equity market has two characteristics not to be overlooked when constructing a domestic index: its relatively small number of stocks and relatively large exposures to a few specific sectors. These factors alone often mean that the application of a specific indexing methodology can produce more pronounced effects compared with the equivalent approach being applied to a global universe.

1. Number of Constituents

The S&P/ASX 200’s relatively low number of companies imply that each company has a larger-than-average weight in the index for a given size. Therefore, any exclusionary indexing approach could cause relatively larger levels of tracking error and index volatility compared with more diversified benchmarks.

This indeed turns out to be the case. The S&P 500 ESG Index—an index with more constituents of lower average index weights—had a marginally higher standard deviation than the benchmark over five years, at only 0.03%, compared with the S&P/ASX 200 ESG Index’s larger 0.23% margin (see Exhibit 1). The Australian benchmark also had a higher five-year tracking error than its U.S. counterpart.

Companies in the S&P ESG Indices are selected for inclusion, targeting 75% of the eligible universe’s weight, at the GICS^® industry group level. However, by looking at the sector-level proportions of benchmark market caps covered in the ESG index compared with the 75% target, some sectors over- or undershoot the target by a significant margin.

These margins in all but two sectors are larger for the S&P/ASX 200 ESG Index than for the S&P 500 ESG Index, which may be expected given the relatively higher weights of the average stock in the Australian index. The marginal inclusion of comparatively smaller-weighted stocks, on average, would likely leave the final industry group market capitalization closer to the 75% target. The same result can also be expected when considering coverage at the sector level (see Exhibit 2).

2. Sector Concentrations

Any index benchmarked to the S&P/ASX 200 would also be sensitive to how its methodology treats companies in the Financials (32.10%), Materials (18.12%), Health Care (8.40%), and Industrials (8.22%) sectors due to their significant weights.[1]

The S&P/ASX 200 ESG Index’s sector weights differ slightly from their weights in the benchmark due to the exclusions made when defining the index’s eligible universe. The two largest sector weight differences are found within the Health Care and Financials sectors.

• In April 2019, Health Care had a 2.26% larger sector weight in the S&P/ASX 200 ESG Index compared with benchmark.
• In contrast, Financials was underweight in the S&P/ASX 200 ESG Index by 2.81 (see Exhibit 3).

The S&P/ASX 200 ESG Index – Index Performance

Despite some of the nuances of the Australian listed equities market described above, the S&P/ASX 200 ESG Index achieves its objective. The index delivers a substantial index ESG score improvement, while providing a benchmark-like risk/return profile.

In fact, for the period studied, the S&P/ASX 200 ESG Index provided better relative returns and index ESG score improvement compared with its benchmark than its U.S. counterpart (see Exhibit 4). Overall, the S&P/ASX 200 ESG Index had an index ESG improvement of 28% compared with benchmark, while providing the same five-year annualized returns.

The ESG improvement at the sector level ranged from 14% to 66% (see Exhibit 5). The Real Estate and Consumer Discretionary sectors’ ESG score improvements were the largest. In the case of the Consumer Discretionary sector, this large improvement might have been expected considering that the ESG index’s coverage of the eligible benchmark sector market cap was the lowest (63%, see Exhibit 2). This implies that the average company included in this sector was among the higher ESG scoring samples in the top of the distribution of eligible companies. Similarly, the relatively low level of ESG score improvement experienced by the Utilities sector was correlated with its overshooting of the 75% benchmark market capitalization target.

CONCLUSION

The S&P/ASX 200 ESG Index is designed to present the Australian equities market with an alternative and investable ESG option to the widely adopted S&P/ASX 200. It can provide an increased exposure to the companies with better ESG characteristics in the S&P/ASX 200, with a similar risk/return profile. By bringing this ESG strategy to the flagship benchmark, investing through an ESG lens has never been easier.

For more information on the S&P/ASX 200 ESG Index, please visit https://spindices.com/indices/equity/sp-asx-200-esg-index-aud

Additional Resources on the S&P ESG Index Series

• FAQs: S&P ESG Index Series
• Steadman, Reid, and Perrone, Daniel. “The S&P 500^® ESG Index: Integrating Environmental, Social, and Governance Values into the Core.” S&P Dow Jones Indices. April 2019
• The S&P ESG Index Series Methodology
• Part One of this Blog

[1]   Weights denote these GICS sector weights in the S&P/ASX 200 as of the adjusted close on April 30, 2019.

Although there seems to be more research on economic forecast and market analysis than manager selection, selecting investment managers is just as challenging as direct investing and requires considerable experience and expertise. In this blog, we investigate the return distribution of fixed income and equity funds to highlight the challenge of successfully selecting outperforming active managers. Specifically, we incorporate risk-reward analysis by calculating the ratio of the median of positive excess returns over the median of negative excess returns. This ratio provides an intuitive comparison between the magnitude of upside gains and downside losses from selecting outperforming versus underperforming active managers. All else equal, the common belief is that a ratio greater than or equal to two is desirable.

The underlying data for the analysis comes from our headline SPIVA^® U.S. Scorecard, which uses the University of Chicago’s Center for Research and Security Prices (CRSP) Survivor-Bias-Free US Mutual Fund Database, the only complete database of both active and liquidated or merged mutual funds. The analysis focused on funds’ return distribution, and therefore eliminated funds that had missing returns for the entire reporting period.

Exhibits 1 and 2 show 5-year and 10-year net excess return distributions for equity and fixed income managers by category. We calculated excess return as the net-of-fees return of each fund subtracting its relevant benchmark index return.

The following are the key highlights from the exhibits.

1. Equity managers had a harder time beating the benchmark than bond managers. The blue shade indicates the quartiles with positive net excess returns. For fixed income categories such as investment grade short and intermediate funds, global income funds, and municipal bond funds, more than half of the managers delivered positive excess returns. On the other hand, in most of the equity fund categories, except large-cap value funds, even top quartile managers were unable to outperform the benchmarks in both 5- and 10-year periods.
2. No equity funds were able to demonstrate a risk-reward ratio greater than one. The yellow shade highlights risk-reward ratios greater than two. California municipal debt funds stood out as the only fund category for which the median upside of selecting outperforming managers doubled the median downside of selecting underperforming managers for both 5- and 10-year returns. In contrast, no equity manager had a ratio greater than one.
3. Fixed income funds returns were more tightly clustered than equity funds. The interquartile range is a measure of statistical dispersion, calculated as the difference between the first and third quartile. In our case, it measures the range of alpha generated by the middle half of the managers within each fund category. The pink shades indicate that the interquartile range greater than 2% were more common for equity funds.

Consistent with prior research by S&P Dow Jones Indices,[1] we found that on a net-of-fees return basis, average managers did not outperform the benchmark over mid- to long-term horizons across all equity fund categories and many bond fund categories. Furthermore, the risk-reward analysis for picking outperforming managers versus underperforming ones demonstrated the challenge of manager selection and the expertise required to be successful in this field.

[1]   https://spindices.com/documents/spiva/spiva-us-year-end-2018.pdf