The Best Clean Energy ETF

Clean energy stocks were all the rage in 2020. ETFs that focus on this area had eye-popping returns, including Invesco Solar ETF (TAN) +233.9%, Invesco WilderHill Clean Energy ETF (PBW) +204.8%, First Trust NASDAQ Clean Edge Green Energy ETF (QCLN) +184.0%, and iShares Global Clean Energy ETF (ICLN) +141.8%. While these trailing 12-month performance figures may imply the possibility of some correction ahead, their long-term underpinnings will remain in place in 2021 and beyond. The incoming Biden administration looks like the most eco-friendly administration ever, and it is likely to go to great lengths to favor clean energy through subsidies, tax breaks, and regulation. Public sentiment towards clean energy has probably never been more positive, and is reflected in the massive $35 billion energy R&D package that extended tax credits for solar, wind, and other clean energy projects passed by Congress on December 22, 2020. The bill is widely described as bi-partisan. It’s clear which way the political winds are blowing.

Clean Energy ETFs

I am an investor in ETFs. I like their diversification of stock-specific risk, their low expense ratios, and their tax efficiency. A quick inquiry to ETF.com and ETFdb.com reveal the following ETFs on their clean energy ETF lists:

Source: ETF.com and ETFdb.com

Obviously, clean energy ETFs have been popular enough to attract a lot of issuers to the space. In fact, the choices are somewhat overwhelming. The funds with the smallest AUM at the bottom of the list may pose too high a risk of closure and may be quickly eliminated for that reason. A bid-ask spread of over about .20% is, in my opinion, too high a transaction cost to warrant further investigation. I do not like paying a high expense ratio for a passively managed fund, and my pain tolerance starts to get stretched at much over .50%. Finally, I do not have a strong preference for one particular type of clean energy, and therefore would prefer one that combines wind and solar rather than focusing on one or the other.

That leaves iShares Global Clean Energy ETF (ICLN) as my first choice among the clean energy ETFs. It has the largest AUM, the lowest bid-ask spread, nearly the lowest expense ratio, and is widely diversified to include solar, wind, and other clean energy-related companies.

ICLN Description

ICLN tracks the S&P Global Clean Energy Index, a market-cap weighted index of 30 clean energy stocks. The definition of “clean energy” is a broad one that includes solar, wind, hydroelectric, geothermal, ethanol, and biofuels. Both companies that produce energy and those that support them through technology and equipment are included. This is a “global” fund, and U.S. companies comprised 31.6% of the overall portfolio according to the most recent fund web page (12/31/2020). The current fund holdings are listed below. Clean energy is very much a global undertaking, so the location information does not necessarily imply where revenues are sourced. Also, industry and sector descriptions in this space vary quite a bit and it is often difficult to accurately categorize these companies.

Source: iShares

The Momentum Anomaly

Numerous academic studies have concluded that momentum constitutes one of the most important factor anomalies in investing. Starting most famously with Jegadeesh and Titman’s 1993 Journal of Finance paper, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” these studies find compelling evidence that past stock returns are helpful in predicting future stock returns—winners tended to keep winning and losers tended to keep losing.  

Most published studies have focused on momentum among individual stocks. However, in a 2005 article in the Financial Analyst’s Journal entitled “Understanding Momentum,” Scowcroft and Sefton found that momentum is mostly a sector or industry effect. “Analysis of the value-weighted large-capitalization universe represented by the MSCI World Index indicates that price momentum is driven largely by industry momentum, not individual-stock momentum.”

Clifford Asness and his co-authors from AQR Capital Management have done extensive research on momentum investing. They find that momentum works well across all kinds of investment categories and time period, including international stock market indexes, government bond market indexes, commodities, and currencies:

“The existence of momentum is a well-established empirical fact. The return premium is evident in 212 years (yes, this is not a typo, two hundred and twelve years of data from 1801 to 2012) of U.S. equity data, dating back to the Victorian age in U.K equity data, in over 20 years of out-of-sample evidence from its original discovery, in 40 other countries, and in more than a dozen other asset classes. Some of this evidence predates academic research in financial economics, suggesting that the momentum premium has been a part of markets since their very existence, well before researchers studied them as a science.” (“Fact, Fiction and Momentum Investing,” Asness, et. al., Journal of Portfolio Management, Fall 2014.)

The evidence for a momentum anomaly is so strong that even those high priests of market efficiency, Fama and French, in a 2008 Journal of Finance article called it "an anomaly that is above suspicion…the premier market anomaly."

Sector and Industry Momentum

If stock momentum works mainly because of the momentum of industries or sectors rather than individual stocks, then the most efficient way to exploit the momentum anomaly is through momentum in sector and industry ETFs. My own research confirms that investing in sector and momentum ETFs using momentum produces significant risk-adjusted returns.

However, I believe that it is important to risk-adjust returns both in measuring momentum itself and in measuring the returns that it produces. Sector and industry ETFs have varying risk exposures, and controlling for them allows for a more accurate picture of sector- and industry-specific returns.

At Sapient Investments, our research has found that four broad risk factors capture most of the risks in nearly any fund:

• Stock market risk (MKT), as measured by the S&P 500 Index
• Interest rate risk (LTB), as measured by the 10-Year Treasury Benchmark Index
• Currency risk (DLR), as measured by the U.S. Dollar Index
• Commodity risk (OIL), as measured by the West Texas Intermediate Crude Oil Index

It is very important to measure the sensitivity of each fund to these four risk factors simultaneously, using multiple regression analysis that includes all four risk factors.  It is also very important to use exponentially-weighted multiple regression analysis.  The exponential weighting helps make the calculations more sensitive to changes, and thus more forward-looking.

Once the effects of risk have been stripped out of the historical returns of an ETF, the risk-adjusted returns become the raw material for measuring momentum. Our methodology is as follows: 

At each month-end, the monthly returns for the past 12 months are averaged using exponential weights that give more weight to the more recent returns such that 50% of the weight is assigned to the most recent three months. Importantly, the most recent month is not omitted, as would be the case for individual stock returns. Stocks are subject to a short-term reversal effect whereby they tend to revert back toward their group (sector or industry) average if they deviate from it in the short-term. In contrast, the most recent monthly return for sectors and industries is a powerful positive indicator of near-term future excess return.

The graph below is one way of depicting the power of risk-adjusted momentum in selecting sectors and industries. The universe of ETFs consists of 86 sector- and industry-specific ETFs. (The count was 56 on 12/31/2007, the beginning of the test period.) At each month-end, two equally-weighted portfolios were formed:  1) the 10 ETFs with the highest 12-month exponentially-weighted risk-adjusted return (long positions) and 2) the 10 ETFs with the lowest such returns (short positions). The risk-adjusted return for both portfolios was calculated and added to the cumulative return to form the three cumulative risk-adjusted return lines depicted below:

1. Top 10 ETFs (blue line)
2. Bottom 10 ETFs (orange line)
3. Top 10 ETFs – Bottom 10 ETFs (green line)

The cumulative risk-adjusted return for the long portfolio was 1.8% per year on average. This may not at first seem like a very impressive number, but it is important to remember that these are risk-adjusted returns—the four major risk factor exposures, including market risk, have been stripped out. Insofar as the four-factor risk model does an adequate job of controlling for risk, any positive residual return is pure alpha. 1.8% per year is quite a lot of pure alpha.

We usually find that there is a lot more alpha in ours shorts, perhaps because there is so much less market capital invested in shorts as compared to longs. The 10 ETFs with the lowest risk-adjusted momentum suffered enormous negative residual returns over the ensuing months, with an average residual return of -14.7% per year. Combined, the long and short portfolio averaged a residual return of 16.5%. Again, this is risk-adjusted return, or alpha.  

ICLN Momentum

Clearly, sector and industry ETFs that have dramatically outperformed or underperformed the overall market tend to continue those trends over the following month, and typically a lot longer. As shown in the graph below, clean energy ETFs currently hold the top three spots for outstanding trailing 12-month exponentially-weighted risk-adjusted return.

Based purely on momentum, Invesco Solar ETF (TAN) would be the preferred play, but TAN has a noticeably higher level of volatility than does ICLN. As mentioned above, I prefer iShares Global Clean Energy ETF (ICLN) among the various clean energy ETFs because it includes a broad array of solar, wind, and other clean energy companies and because of its low expense ratio and bid-ask spread. 

Summary

• The strong performance of clean energy companies appears likely to continue because of the incredible political support for this sector.
• iShares Global Clean Energy ETF (ICLN) is my first choice among the clean energy ETFs because of its:
  • breadth (including solar, wind, and other clean energy companies)
  • low expense ratio (.46%)
  • low bid-ask spread (.04%)
• Stock momentum has been shown to be mostly a sector or industry phenomena.
• Among sector and industry ETFs, risk-adjusted momentum is a powerful predictor of future alpha.
• ICLN has incredible risk-adjusted momentum going into 2021.