Indexology^® Blog

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Even though the performance of clean energy-related companies has recently faced some headwinds due to rising interest rates and inflationary pressures, the clean energy industry is still being driven by continuous policy support. As we approach the midpoint of 2024, we wanted to review the S&P Global Clean Energy Index Series rebalance from April and share some of the key developments from the beginning of the year in the clean energy space.

April Rebalance

Launched in 2007, the S&P Global Clean Energy Index has been the benchmark for measuring clean energy-related companies’ performance over the past 16 years. In April 2021, we launched the S&P Global Clean Energy Select Index to measure the 30 largest companies in global clean energy businesses that are listed on developed market exchanges.

Both indices went through a semiannual rebalance on April 19, 2024. The index methodology categorizes companies into four exposure score buckets ranging from 0 to 1, with a 0.25 increment, to measure their clean energy business purity. Exhibits 1 and 2 show the change in exposure before and after the April rebalance for both indices. For the S&P Global Clean Energy Index, the weighted average exposure score of the index dropped slightly from 0.95 to 0.93. This drop can be attributed to the addition of certain large market cap companies with an exposure score of 0.75 to the index, such as Iberdrola SA, Consolidated Edison and PT Barito Renewables Energy. As a result, the index weight for companies with an exposure score of 1 decreased. The S&P Global Clean Energy Select Index consists of 30 companies with an exposure score of 1 listed in the developed market exchanges (see Exhibit 2).

S&P Global Clean Energy Index Performance YTD in 2024

Underperforming the S&P Global BMI YTD, the S&P Global Clean Energy Select Index was down 19.96% and the S&P Global Clean Energy Index was down 14.90% in USD total return terms, and dispersion was high among constituents of the S&P Global Clean Energy Index. Sunnova Energy International (-72.39%), Plug Power (-48.67%) and Sunrun (-47.58%) were among the lagging performers, while NHPC (up 50.64%), SJVN (up 48.85%) and Nordex (up 23.41%) made positive contributions to offset some of the losses. It is worth highlighting that NHPC and SJVN, two Indian companies, have outperformed in 2024. This can be attributed to the Indian government’s ambitious targets in the clean energy sector.^[1]

Despite the recent performance challenges, the following developments indicate a positive future for the energy transition.

Key Developments

Clean Energy Is Boosting Economic Growth

In March 2024, the International Energy Agency (IEA) released its inaugural Clean Energy Market Monitor report. This report offers a timely and concise overview of clean energy deployment for select technologies. According to the report, “global clean energy deployment scaled new heights in 2023, with annual additions of solar PV and wind growing 85% and 60% respectively.”^[2] The adoption of clean energy contributed approximately USD 320 billion to the global economy, representing 10% of the overall growth in global GDP.^[3]

Government Investment in Clean Energy Continues to Increase

In March 2024, the Biden-Harris Administration unveiled a USD 4 billion tax credit initiative supporting more than 100 projects across 35 states. The goal is to boost domestic clean energy manufacturing and curb greenhouse gas emissions in industrial facilities. These projects, eligible for tax credits under the Qualifying Advanced Energy Project Tax Credit (48C), encompass large, medium and small businesses, as well as state and local governments. To qualify for a 30% investment tax credit, all participants must adhere to prevailing wage and apprenticeship requirements.^[4]

DOE Releases Roadmap to Accelerate Interconnection for Clean Energy Transition

The U.S. Department of Energy (DOE) has released the new Transmission Interconnection Roadmap, which proposes solutions to accelerate the integration of a clean energy transition.^[5] The roadmap sets ambitious targets for enhancing interconnection by 2030 and outlines tools to improve the process of connecting clean energy projects to the grid, supporting the Biden-Harris Administration’s goal of achieving 100% clean electricity by 2035. “DOE’s Grid Deployment Office invests in accelerating interconnection of clean energy generation through the $5 billion Grid Innovation Program, which supports deployment of projects that use innovative approaches to enhance grid resilience and reliability.”^[6]

^[1]   https://www.weforum.org/agenda/2024/05/india-emerging-advanced-energy-superpower/

^[2]   https://www.iea.org/reports/clean-energy-market-monitor-march-2024

^[3]   https://www.iea.org/commentaries/clean-energy-is-boosting-economic-growth

^[4]   https://www.energy.gov/articles/biden-harris-administration-announces-4-billion-tax-credits-build-clean-energy-supply

^[5]   https://www.energy.gov/eere/i2x/doe-transmission-interconnection-roadmap-transforming-bulk-transmission-interconnection

^[6]   https://www.energy.gov/articles/doe-releases-first-ever-roadmap-accelerate-connecting-more-clean-energy-projects-nations

In our previous blog, we introduced the newly launched S&P 500^® Economic Moat Index by reviewing its methodology, index characteristics and historical performance. In this blog, we will examine the specific quantitative metrics used to identify the companies with the widest economic moats. Furthermore, we will discuss the complementary nature of the metrics, which has historically led to strong performance when combining the metrics into a multi-factor score.

Quintile Analysis

In addition to having a solid economic rationale, we believe that metric selection should also be based on empirical research. For Exhibits 2-4, we tested each metric on a standalone basis by dividing S&P 500 constituents into quintiles based on their metric z-score and equal weighting them, with quintiles 1 and 5 being the lowest and highest ranked quintiles, respectively. Exhibit 5 shows the results after combining the three metrics into a multi-factor score. Like the S&P 500 Economic Moat Index, the quintiles are rebalanced semiannually in June and December. Performance is calculated using daily returns from June 21, 2013, to March 31, 2024.

Sustained High Return on Invested Capital

Sustained high return on invested capital (ROIC) is a strong indicator of business quality since it measures how efficiently capital is utilized. This is arguably the strongest single indicator of a moat since companies with wide moats tend to have higher ROIC than those with narrow or no moats.

Exhibit 2 shows that long-term annualized returns steadily increase for each quintile, with quintile 5 providing an annualized return of 14.38% versus 10.56% for quintile 1. Conceptually, this makes sense as companies that can sustainably earn higher ROICs should grow their earnings and intrinsic value at a faster rate over the long term. Moreover, volatility tends to also decrease for higher ranking quintiles, with quintile 5 exhibiting a 15.81% annualized volatility versus 18.51% for quintile 1.

Sustained High Gross Margin

Two metrics are used to assess sustained high gross margin: gross margin over the past 12 months and gross margin stability over the last 5 years. These metrics are used to assess pricing power, i.e. those companies able to charge a premium price over the cost of production, which may indicate the presence of an economic moat.

Like Exhibit 2, Exhibit 3 shows that long-term annualized returns steadily increase based on companies’ gross margin. Furthermore, due to volatility diminishing for companies with higher sustained gross margins, the risk-adjusted return significantly improved from 0.48 to 0.91 for quintiles 1 and 5, respectively, representing a substantial 90% improvement.

High Market Share

A high market share may indicate a strong moat resulting from economies of scale, network effects and brand power. This metric is most useful when combined with other metrics since high market share may not indicate high profitability or sustainable competitive advantages. This metric is calculated using Syntax’s Market Share Score.

Although Exhibit 4 does not show perfect sequential improvement in quintile performance like Exhibits 2 and 3, the trend remains evident that companies with high market share significantly outperform those with low market share. In addition to posting the highest absolute return of 14.64%, quintile 5 also exhibited the lowest annualized volatility (15.00%), translating to an impressive 0.98 risk-adjusted return.

Complementary Metrics

Although each selection metric shows efficacy on a standalone basis, the metrics may not always accurately identify an economic moat if used in isolation. One way to enhance the effectiveness of identifying an economic moat is to use the three metrics in combination, since it mitigates the risk of distortion when relying on a single indicator. For example, software companies may have high gross margins simply due to their structurally lower cost of goods sold (COGS) and in certain industries such as airlines, high market share has not historically translated to the presence of an economic moat.

Another benefit of using multi-factor selection is strong risk-adjusted performance. As Exhibit 5 shows, quintile 5 provided the highest annualized return and the lowest volatility at 15.43% and 14.48%, respectively. This impressive set of results translates to a risk-adjusted ratio of 1.07. It is quite challenging to achieve a risk-adjusted ratio above 1, and even more uncommon when accompanied by a long-term annualized return in the mid-teens.

Conclusion

Due to the financial reward typically associated with identifying a company with a wide economic moat, there is a great deal of investor attention directed toward this concept. We posit that the strong back-tested performance in this blog supports the notion that financial statement metrics can be used to identify a wide economic moat, and that a purely quantitative approach helps overcome the limitations of a subjective selection process.

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