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Addressing the Scalability Challenge in Thematic Investing and Custom Indexing

Companies and Markets

By Russell Smith  |  May 4, 2022

Thematic investing is poised to be one of the major trends for the year ahead. As noted in one of FactSet's recent Insight posts, a rising interest in thematic investing presents a compelling opportunity. Investor appetite to explore a wide range of specific themes—from environmental, social, and governance (ESG) to disruptive technology, demographics, and smart beta—is high. Combined with a willingness to partner with fund issuers to develop customized funds, thematic investing will become an area of focus for investors in 2022.

The Art of Customization: An Opportunity and a Challenge

The opportunity that thematic investing presents also comes with a challenge—one of scalability. While the benefit of this investment style is the number of themes and sub-themes available, carrying out research and development into each can quickly become overwhelming. Coupled with the marketability of a given theme—is there enough interest to launch as an exchange-traded fund (ETF) or index, or is this a client-specific mandate—the ability to rapidly test, develop and iterate through new product ideas will become more important than ever before, to capitalize on the success that this opportunity presents.

The challenge of scalability is not unique to thematic investing. In fact, this has been cited as a barrier to entry in the self/custom-indexing space for several years, with both workflows requiring the ability to rapidly iterate, validate, and progress/discard multiple ideas in a short amount of time. In 2022, however, the theme of disruptive technology itself, can help address this challenge. We’ve already seen a growing number of large asset managers beginning to adopt technological innovation to enter the custom-indexing space.

Here we consider the creation of several custom baskets designed to address one of the top investment themes for 2022, as noted in Forbes' The Top 10 Investment Themes for 2022: sustainable investing. We used FactSet’s Quantitative Research Environment (QRE) to explore various ESG-focused strategies. QRE is an open, programmatic environment where users can analyze data and explore ideas by leveraging open-source Python packages alongside FactSet content and APIs.

Defining the Investment Universe

To develop a sustainably focused product, we sought to create an ESG-aware carve-out of a broad global market index, the STOXX Global 1800.

To evaluate trends in the index, we captured five years of monthly observations of the constituents. We adjusted for survivorship bias as well as historic M&A activity and corporate actions to accurately recreate the index membership through time. As companies moved in and out of the index, we captured their membership status. For example, GlaxoSmithKline has remained in the index throughout the five-year range, while FMC Technologies was a constituent member on the first observation date only.

Incorporating Additional Data Points

Having generated our investible universe, we then enhanced the index data with several additional data points.

First, we screened our companies based on their Company Insight Scores from FactSet’s Truvalue Labs (TVL) data set. The TVL Insight Score provides a measure of a company’s longer-term ESG track record. The Insight Score includes a time decay using an exponentially weighted moving average (EWMA), meaning that scores are less sensitive to daily events and reflect the enduring performance record of a company over time. Using a scale of 0 to 100, TVL generates a score where 50 represents a neutral assessment; the closer the score is to 100, the more positive the sentiment, and the closer the score is to zero, the more negative the sentiment.

Using these scores, we defined two company groupings. Stocks with an Insight Score of 50 and above were marked as "ESG Inclusions” and would form our investible universe. Any stock with a value below 50 was flagged under "ESG Exclusions." As these companies fall outside of our investible universe, we analyzed the impact of removing them from the index.

Finally, we included starting index weights, FactSet RBICS Economy classifications, and monthly returns for each of our STOXX 1800 constituents, captured at every observation date through time.

Characteristics of Our Data Sets

Before analyzing the performance of our stock groupings, we sought to better understand the composition of each basket and its evolution over time.

More Companies Are Focusing on ESG

As shown in the chart below, there has been a clear increase in the number of companies flagged as ESG Inclusions under our Insight Score grouping taxonomy. The number of companies in this group increased from a little over 1,000 at the end of December 2016 to just over 1,400 at the end of December 2021.


Increased Overall Weighting for ESG-Focused Companies

As shown below, there has been a clear shift in the overall market value of the STOXX Global 1800 that falls into our "ESG Inclusion" group. In aggregate, this group has moved from approximately 52% of the index at the start of the analysis timeframe to 67% at the end.


Sector Trends

Next, we wanted to analyze any changes or patterns at the sector level. Would our ESG Inclusions approach lead to a concentration in a small number of sectors? Are we able to determine any trends over time, i.e., sectors that have become more (or less) ESG focused? Are there any sectors that appear to be clear leaders in ESG adoption?

Drilling into the stocks classified as ESG Inclusions, we examined the overall index weight associated with each sector, as defined by the RBICs Economy classification. The graphs below show an increase in weighting across every sector, excluding Utilities. The largest observable changes occur in the Consumer Cyclicals, Healthcare, Finance, and Technology sectors, with each sector seeing a 2-5 percentage point increase in the overall index weight associated with our ESG Inclusions strategy. The change in Technology stocks is most notable from the start of 2020, with the weight rising from 5.9% in January 2020 to 11.2% as of December 2021.


Drivers of Weight Changes

The above observation in Technology seems intuitive; we know that many tech companies rallied during 2020. For example, the price of Zoom Video Communications, Inc. surged by over 700% between January 1, 2020 and its peak on October 19, 2020.

But does this imply that the increase in weight is solely driven by price performance, or has there been an increase in the number of companies that have moved into the ESG-aware grouping over time? Re-running our RBICS Economy analysis of the ESG Inclusions provides some insight.


The graphs above show increases in the number of companies that have moved into our ESG Inclusions grouping in Finance, Industrials, and Technology, indicating a broader adoption of ESG principles in these sectors.

Performance Comparison

With an understanding of the composition of our ESG-aware group, we examined the performance of our three different stock baskets: the broader index, the ESG Inclusions group, and the ESG Exclusions group. We looked at each basket in a backtest context, calculating forward returns for each stock on every observation date, to understand how each group of stocks performed following their classification on a given date. Returns were calculated on an equal-weighted basis to remove market cap bias.


As shown in the chart above, the performance of the stocks in the ESG Inclusions group was in line with the benchmark over the last five years. While the ESG Exclusions stocks outperform, they demonstrate a higher level of return volatility, as denoted by the orange area band.

Building Our Indices

We now turn our attention to the construction of our customized basket. Asset selection will continue to be driven by our ESG Inclusions/Exclusions flag, but further consideration needs to be given to selecting a weighting scheme. Given that our investment approach is to be built around ESG stocks, does it make sense to continue with a market-cap-weighted index, where more weight could be assigned to stocks with lower ESG profiles based solely on their market capitalization?

Our analysis found that the stocks with the highest ESG scores have a very small market cap weight in the index, with the top five ESG-ranked stocks totaling around 0.05% of the overall index weight. At the same time, the two highest market-cap-weighted stocks would fall outside of our investible universe on an ESG basis, with Insight Scores falling beneath our threshold of 50. If we want to allocate more weight to the stocks that have the best ESG profiles, a conventional market-cap weighting might not be the best approach.

Equal-Weighted Portfolio

The equal-weighted portfolio carries an overweight towards Industrials and Non-Energy Materials at the RBICs Economy level. Underweights relative to the STOXX Global 1800 show a sizeable tilt away from Technology stocks. At the country level, the equal-weighted basket shows a large tilt away from the U.S., favoring countries across Europe along with Australia. Japan represents the largest overweight on the country level.


Measured at the end of last year, the basket holds slightly lower volatility relative to the STOXX Global 1800, with moderate active risk of almost 4.4%. This itself is predominantly (85%) driven by systematic, or factor-based, risk. Looking at a selection of customizable portfolio characteristics, we see that the basket shows a significant tilt towards small-cap value with both higher volatility and lower quality, relative to the benchmark.

Market-Cap-Weighted Portfolio

Like our equal-weighted approach, the market capitalization-weighted portfolio carries an underweight in both Technology and Healthcare relative to the STOXX Global 1800. However, using this weighting methodology, the extent of the underweight is less pronounced. In contrast, the largest Economy level overweights come from Consumer Non-Cyclicals and Consumer Cyclicals.


At the country level, the U.S. remains underweight relative to the Index, with Australia moving to the second largest underweight position. France and Japan represent the two largest overweight countries. Overall, the country-level weighting decisions in the market capitalization portfolio are much closer to the benchmark.

This custom basket carries slightly higher standalone volatility than the benchmark, but a much closer level of active risk/tracking error at 1.93%. Decomposing the underlying drivers, we see that idiosyncratic risk is slightly higher (54%), with country factors representing the largest factor group. Looking at the portfolio characteristics, we see a similar small-cap, low-quality profile coming through, with a value tilt appearing more muted.

By building the baskets through time, we can further analyze their historical performance. Below we see the cumulative return of both the equal- and market-cap-weighted baskets, with the latter clearly outperforming.



It's clear that thematic investing will be a hot topic in 2022. Whether through customized ETFs and indices or via custom indexing for client-specific mandates, the ability to rapidly research, develop, and deploy multiple iterations of customized stock baskets will be key to realizing the opportunity that this space presents.

Daniel Vetter and Sean Carr contributed to this article.

Disclaimer: This blog post is for informational purposes only. The information contained in this blog post is not legal, tax, or investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.


Russell Smith

Vice President, Senior Sales Specialist, Portfolio Risk and Quantitative Analytics

Mr. Russell Smith is Vice President, Senior Sales Specialist in Risk and Quantitative Analytics at FactSet. In this role, he is one of FactSet's experts for Portfolio Risk and Quantitative Analytics and has spent the last eight years specializing in workflows and solutions for quantitative analytics including but not limited to factor research, portfolio construction, optimization, and risk and factor attribution. Starting as a Consultant in 2008, he has spent two years working with some of FactSet’s largest buy-side clients across the UK and Ireland before joining the Analytics team in 2010. Mr. Russell earned an LLB from Nottingham Trent University.


The information contained in this article is not investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.