In a recent blog post1, we discussed key considerations for managers incorporating Sustainable Development Goals (SDGs) into their portfolios. We showed that taking on more active risk led to higher potential SDG exposure and that one could achieve meaningful exposure even at a relatively low level of active risk—though the level of exposure varied by SDG.
Of course, making one set of tilts in a portfolio may lead to other exposures, some desirable and some less so. As a follow up to our original analysis, we looked at what some of those bets might be. Our analysis is written up in a whitepaper you can find here.
We used the end-of-year 2021 data from the Sustainable Development Investments Asset Owner Platform (SDI AOP) to run simple optimizations with the objective of maximizing exposure (defined by the percent of revenue) to all SDGs, with the STOXX® Global 1800 Index2 as our investment universe and benchmark. The only constraints we employed were to be fully invested with a 3% target tracking error. While we created four different sample portfolios for the whitepaper, we summarize our findings on one of these portfolios, one that maximizes exposure to all SDGs, in this blog post.
The STOXX Global 1800: well-diversified with some SDG exposure, but much more exposure was possible
The STOXX® Global 1800 Index by definition holds 1800 names, but the effective number of names at the end of 2021 was 1563, with 13.7% of the weight and almost 15% of the risk in the top five names, and just over a quarter of the weight and 27.3% of the risk in the top 25 (Exhibit 1). The portfolio designed to maximize exposure to all SDGs, in contrast to the STOXX® Global 1800, held 170 names, with an effective number of names of 89. The top-five weight was similar to that of the index, but the All-SDG portfolio was significantly more concentrated in the top 25 names.
Exhibit 1. Weight and Contribution to Risk, Top 5 and Top 25 Holdings, STOXX Global 1800 vs. All-SDG Portfolio
SDG exposure was not completely absent from the index, although it was relatively muted (Exhibit 2): 14% of the index weight met at least one Sustainable Development Goal. Another interesting note is that the percent of total portfolio risk in the index exposed to the “All SDG” category was lower than its weight, suggesting that companies meeting SDG criteria were also less risky than other names on average. Of course, the All-SDG portfolio had a much higher weight than the Global 1800 devoted to meeting one or more the SDGs (91%), and the contribution to risk of those names was also lower than the weight.
Exhibit 2. Weight and Contribution to Risk, All SDGs, STOXX Global 1800 vs. All-SDG Portfolio
Of course, SDG exposure came with some additional risk exposures
The optimized portfolio came with some active factor exposures as well as with stock-specific risk. About half of the All-SDG portfolio’s 3% tracking error was factor-based, with the other half stock-specific (Exhibit 3). In addition, most of the factor risk was Industry risk, with a little style risk as well.
Exhibit 3. Main Risk Exposures, All-SDG portfolio
The All-SDG portfolio had a big overweight in Health Care, offset by underweights in Financials and Info Tech, driving the industry risk (Exhibit 4). It also had a small-cap and low Dividend Yield bias (Exhibit 5). Other style exposures were relatively small. It had a big country underweight in US exposure (Exhibit 6), although country exposures contributed less than 2% of the active risk.
Exhibit 4. Active Sector Exposures, All-SDG Portfolio
Exhibit 5. Active Style Exposures, All-SDG Portfolio
Note: Style exposures are stated in standard deviations, so an exposure of -0.2 indicates the aggregate active exposure is 0.2 standard deviations below that of the benchmark.
Exhibit 6. Biggest Active Country Exposures, All-SDG Portfolio
Finally, we found that our All-SDG portfolio got much of its exposure from SDG-3, “Good Health and Well Being” (hence the Health Care overweight), although a few of the other SDGs also contributed (Exhibit 7). As noted earlier, while the contribution to overall risk from the SDGs was lower than what would be expected given their weight, that was not the case for some of the individual SDGs. For example, those companies meeting SDG-7, “Affordable and Clean Energy”, were riskier than the universe and therefore contributed more to the total risk.
Exhibit 7. Weight and Risk Contribution, Selected SDGs, All-SDG Portfolio
Many investors want to incorporate Sustainable Development Goals in their portfolios. This objective is eminently achievable, and the added risk exposures may well be worth the higher SDG exposure. Companies that derive a significant portion of their revenues from a given SDG are often concentrated in a few industries, which will be reflected in a portfolio seeking to maximize exposure to the SDG. Some of those industries may also be more prevalent in certain countries, leading to significant active country exposures. Those companies with the most SDG revenue may also be smaller than average, resulting in a small-cap bias for these portfolios.
Still, it is quite possible to create a portfolio that significantly improves the exposure to SDGs without taking on too much active risk. For some SDGs, companies that rank better also seem to have lower risk, which, all things being equal, should improve the risk-return ratio. An optimizer can help manage that active risk to a level at which the asset manager or asset owner is comfortable, and a risk model provides guidance on how much risk a given active bet actually entails. It is essential to understand the tradeoffs, i.e., there will be active risk, but it should be commensurate with the increase in sustainability associated with any or all SDGs.
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 A global developed-markets index.
 This represents the inverse of the Herfindahl-Hirschman index, which is a measure of market concentration. If the effective number of names is very low (i.e. the index is very concentrated) it suggests it will be more difficult to be well-diversified.
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