The Hidden Election Candidate - ESG

The countdown continues, with just over a week until the 2020 US Election. Last week we identified Beta as a major driver of systematic volatility during US elections. Based on this finding, we created an investable basket of stocks targeting Beta to take advantage of the risk-on/risk-off election theme. This week, we’ll take a different approach and look to some of the popular points of contention between the two lead presidential candidates in order to design election themes which can translate into investment ideas.

‍Taking a stance on whether or not to tackle ESG issues (mainly environmental and social) has formed several of the major platform issues for both front-running presidential candidates. While we won’t pontificate on how these issues will play out in the election, we do believe that they will have the potential to impact portfolios and drive performance in a major way, regardless of which side of the bet investors choose to side with.

For our purposes, we’ll be focusing specifically on the “green theme”. To capitalize on this theme, we will outline how to construct several green baskets by leveraging our platform along with the MSCI ESG Ratings and the MSCI Barra US Total Market Equity Model.

Green Basket Design Methodology

To start, we looked to MSCI’s industry leading ESG ratings framework to design our green baskets. MSCI’s ESG Ratings are available via the Omega Point ecosystem, making it easy to leverage this content for portfolio construction. The MSCI ESG dataset provides extensive and detailed data across all three ESG pillars; however, we’ll be focusing on the 4 themes that make up the Environment Pillar: Climate Change, Natural Resources, Pollution & Waste, and Environmental Opportunities. The table below shows the key issues that are considered in each theme.

To create a green basket related to each of these themes, we followed the same 3 steps for creating a factor-targeted basket we had discussed in last week’s article:

1. Build a Tradable Universe
2. Create Equal-Weighted, Market-Neutral, Factor-Targeting Portfolios
3. Purify Factor-Targeting Portfolios

1) Build a Tradable Universe

‍Our universe includes all securities covered by the MSCI Barra US Total Market Equity Model for Medium-Term Investors, with market capitalization greater than or equal to $500 million and average daily trading volume greater than or equal to $5 million.

2) Create Equal-Weighted, Market-Neutral, Factor-Targeting Portfolios

‍For each of the key issues shown in the table above, MSCI offers a 0-10 score to evaluate how well or poorly a company is addressing the issue in their operations, with 10 being the best and 0 being the worst . For each theme, the scores for the underlying key issues are combined to create a weighted average score at the theme level. Similar to past analysis we’ve done, we created 4 high-minus-low (HML) portfolios to get as much exposure to each of the themes as possible.

The "high" side of the portfolio is an equal-weighted long book using the top decile of securities based on a given theme score and the "low" side of the portfolio is an equal-weighted short book using the bottom decile of securities for the same score. The long and short sides were combined together to form 4 final market-neutral portfolios which target each of the themes and we can see the high net exposure to the respective theme for each basket.

3) Purify Factor-Targeting Portfolios

‍In order to ensure that each of the themes is represented cleanly and does not pick up undesirable factor traits, we optimized each of the market-neutral portfolios using our SmartTrade^TM technology with the goal of minimizing factor risk. We also included trading constraints so that the resulting portfolios are not too concentrated in any individual names. The resulting optimized portfolios form our final 4 green baskets.

Does Purifying the Basket Really Matter?

To demonstrate the power of “purifying” our green baskets, we’ll compare the current risk profile of the equal-weighted portfolios from step 2 to the current risk profile of the optimized portfolios from step 3.

‍Equal-weighted portfolios from step 2:

Optimized portfolios from step 3:

Across the board we can see that the total risk for the optimized portfolios is on average reduced risk by 33% of total risk (relative) than the equal-weighted portfolios. In almost all cases, we were able to significantly increase specific risk and greatly reduce the factor risk. Higher specific risk is desirable here in order to get a purer signal on the green themes and minimize systematic factors driving the volatility the basket.

Factor Traits of the Green Baskets

As with any thematic basket, it’s important not only to gain exposure to the theme you’re targeting, but also to ensure that you don’t pick up any unwanted systematic factors along the way. Many arguments have been made that targeting green themes in portfolio construction can translate to sector bets on Information Technology and Energy, given how ESG tends to impact companies in those sectors. However, when we drill into the sector weights, we can see a different story emerge.

The top 5 industry group weights for each basket show that while there are large tilts, there are no single standout industries. Additionally, the long Info Tech / short Energy expectation doesn’t hold here. There are no energy industries showing up within the top 5 for any of the baskets and we see technology industries on both the long and short side. Depending on investors’ sector preferences, these baskets could also be constructed to be sector-neutral.

Not only do we want to consider sector bets within our baskets, but we’ll also look at any major style bets that might be driving risk. Looking into some of the top style risk contributors across all of the green baskets, we can see that most of the factors have very little contribution. There are some meaningful factor contributions, namely the Size factor for the Natural Capital & Climate Change baskets. However, for the most part, the factor risk is relatively low, and the typical factor offenders such as Momentum, Residual Volatility, or Beta generally do not show up as major contributors.

It Ain’t Easy Being Green... Or Is It?

Using the three steps we’ve outlined above, investors can easily create green tilts in their portfolio while avoiding undesirable systematic factors. For investors who believe that ESG will play a major role in the election, any of the thematic baskets that we’ve created, or baskets created in a similar fashion using other ESG factors, could be key to coming out on the right side of the volatility that is sure to ensue post-election. Not only will this be an important consideration in the short-term with the upcoming election, but also in the long-term a the investment management community increasingly leverages their financial resources to push for ESG-awareness within their portfolio companies.

US & Global Market Summary

US Market: 10/19/20 -10/23/20

• The S&P 500 saw a positive move on Friday but ended a three-week winning streak. Stocks generally stayed rangebound as investors continued to wait to hear if and when a deal would be reached on the next US COVID stimulus package.
• U.S. House Speaker Nancy Pelosi remains hopeful a deal on coronavirus relief can be reached with the White House soon, as congressional committees worked on a potential agreement over the weekend.
• 3Q earnings have taken a backseat to the ongoing stimulus talks, but next week we’ll see some heavy hitters report, including AAPL, FB, GOOGL, and more than a third of the S&P 500’s constituents.
• Thus far, Factset data shows that nine of the 11 sectors in the S&P 500 have reported a YoY decline in earnings, led by energy (-123.6%).
• Investors will also look for the first reading of 3Q GDP on Thursday, with consensus expectations of a +31.8% annualized number.

‍Normalized Factor Returns: Axioma US Equity Risk Model (AXUS4-MH)

• Profitability was the week’s biggest winner as it continued to revert from its recent depths of -1.09 SD below the mean on 10/7.
• Momentum hit a recent high of +0.46 SD above the mean on 10/20 and appears to be slowly drifting back down for the moment.
• The rally in Growth slowed as it remained largely flat on the week.
• Earnings Yield continued to revert from a peak of 1.53 SD above the mean on 10/8 and is on the cusp of dropping out of Oversold territory.
• Size was again the biggest losing factor as it crossed into negative normalized space.
• US Total Risk (using the Russell 3000 as proxy) declined by 36bps.

Normalized Factor Returns: Axioma Worldwide Equity Risk Model (AXWW4-MH)

• Exchange Rate Sensitivity saw the biggest normalized move (up +0.28 standard deviations) in a relatively muted week for global factors.
• Value and Size crossed into positive normalized territory, with both now sitting slightly above the mean.
• Growth saw slight strength and now sits at +0.5 SD above the mean.
• Earnings Yield saw continued weakness, albeit at a slower pace, as it ticked down slightly after being +1.53 SD above the mean on 10/7.
• Global Risk (using the ACWI as proxy) declined by 31bps this week.

Regards,
Alyx