Since the onset of the pandemic, there has been an evolution of behavioral changes that are not one-offs to our society, but transcendent trends that may impact future generations across a variety of different parts of our economy. While some of these trends existed prior to COVID-19, the pandemic has pushed the timing of the adoption of certain behaviors up by a few years – creating new future growth opportunities.
Naturally, this has spurred investor interest toward thematic ETFs that seek to provide exposure to some of these firms at the forefront of innovation in our new economy. This year, more than $30 billion has flowed into thematic ETFs – strategies focused on such areas of innovation as: Future Communication, Clean Energy, Smart Transportation, and Cloud Computing.
With all this interest, due diligence on the underlying exposures is necessary – as many of these strategies deviate from owning just large, mega-cap tech stocks and venture into smaller firms that are not as well known. One of the areas of analysis that has routinely come up is valuation, and in this blog, I will walk through which valuation metric is most appropriate to use when trying to formulate a fundamental view on areas of innovation.
Fundamentally thematic Before we delve into the intricacies of valuation multiples, there is one caveat to mention: many of these strategies are within the “growth” category. In fact, out of the 145 funds we have identified as thematic, 124 have more than 50% allocated to “growth” stocks.1 Given that traditional growth stocks are trading above the 90th percentile across price-to-book, price-to-earnings, price-to-next-12-months-earnings, price-to-sales, enterprise value-to-sales, and enterprise value-to-EBIDTA,2 it would follow that these nontraditional growth stocks are also likely to end up in a similar “high-valuation-multiple” place.
But what metric to use? To answer this, we need to understand the type of firms typically found within these strategies. When performing a security look-through analysis, we find that many are concentrated in Consumer Discretionary, Health Care, and Information Technology sectors, as shown below. This is important, as the firms within those three sectors typically have a large amount of intangible assets on their balance sheets. And price-to-book is not the best metric to use when a firm has a high amount of intangible assets, as those assets are usually understated in a firm’s book value, and, as a result, that could inflate a firm’s price-to-book measure. However, one advantage of price-to-book is that it can be used with firms that have negative earnings – a trait that may be valuable in this exercise. Despite the latter feature, the high presence of intangibles leads to price-to-book not being a suitable metric for thematic strategies.
Source: Bloomberg Finance L.P. as of December 15, 2020 based on SPDR Americas Research calculations of 145 thematic ETF underlying sector exposures. Characteristics are as of the date indicated.
Earnings-related issues for thematics While expected three-to-five-year earnings-per-share growth for the firms found within our thematic classification of “Broad Innovation” funds4 is expected to be 19.50% — versus 12.50% for the S&P 500 — some of this growth is coming off from a very low — and in some cases, negative — base. In fact, out of the 1,410 unique securities held across the 18 funds classified as “Broad Innovation,” 30% of the firms have a negative trailing 12-month earnings per share.5 Now, the reason why some of these firms may not yet be profitable is that they are still in the early/entrepreneurial stage of their firm’s maturity cycle. The median market capitalization of the firms within this small subset of thematic exposures (Broad Innovation represents just 13% of the 145 funds we classify) is only $8 billion – compared with the $34 billion median market capitalization of firms in the S&P 500.6
There are two issues, however, stemming from the dynamics discussed above if we use earnings-related metrics (e.g. price-to-earnings (P/E), price-to-next-12-month-earnings, and enterprise value-to-EBITDA). First, negative earnings firms must be removed, and that provides an incomplete view of the exposure, as not all firms are being analyzed. And those firms must be removed in order to not skew the result (i.e., negative P/E values would tamp down the high P/E values when performing an average calculation for a portfolio). Second, it requires the use of a weighted harmonic average7 to account for outliers, given that small earnings-per-share figures (e.g., $0.10) can result in P/Es well north of 100 – in fact, out the 1,410 securities mentioned earlier, 15% have a P/E over 100.
Using a different approach is not the problem, and in fact, when analyzing ratios, the weighted harmonic calculation is the preferred method. However, the problem does lie in that many just apply a straight-line average, and this is incorrect – and it is even more incorrect when there are outlier figures. Consider the example below of a three-stock portfolio and the different results when a straight-line or normal-weighted average is used instead of a weighted harmonic average. The firm with a P/E of 80 has a larger impact in the straight-line and weighted-average figure. Meanwhile, in a harmonic approach, equal weight is given to each data point and outlier impact is reduced.
Weighted Harmonic Average
Source: SPDR Americas Research for illustrative purposes only.
Given the presence of negative earnings firms, any multiple that has earnings-related information in the denominator should, therefore, likely not be utilized. This holds true for the price-to-earnings-growth ratio (PEG) as well, given that it still relies on earnings in the denominator – even though it does normalize the ratio by expected growth. Yet, if someone does steadfastly want to use P/E or another earnings-based figure, ensuring that it is a weighted harmonic calculation is extremely important.
No earnings, but revenue, hopefully While some of these innovative firms do not have earnings, hopefully they have sales/revenue. As a result, using a sales-based metric may be more optimal. One issue with revenue, however, is that sometimes, it can be hard to make comparisons between firms as a result of different margins. High-revenue, high-margin businesses may have higher stock prices than high-revenue, low-margin businesses as result of the former’s ability to turn sales into earnings.
There are two potential sales-based metrics available to investors: price-to-sales and enterprise value-to-sales. The latter, in my opinion, is the most appropriate and comprehensive view of a firm’s operations, as enterprise value (EV) accounts for both the firm’s equity value and amount of debt.8 As a result, it will account for the level of leverage/debt being utilized by the firm to generate revenue, and be more comparable across industries, given it is capital structure agnostic (i.e., high-debt industries typically look cheaper on a price-to-xyz basis given their debt isn’t captured in the metric, but under EV, the debt is taken into account).
A list of the metrics — and the strengths and drawbacks of thematic valuations — are shown below:
Strengths for thematics
Drawback for thematics
Can be used on companies with negative earnings
Not appropriate for firms with a high level of intangibles
Accounts for cash flow after expenses and what a firm earns that can be paid out to shareholders or retained for growth
Impacted by capital structure, not applicable for firms with negative earnings
Accounts for metrics like P/E, as well as growth expectations
Impacted by capital structure, not applicable for firms with negative earnings
Capital structure agnostic and accounts for cash flow
Not applicable for firms with negative earnings
Controls for negative earnings firms
Impacted by capital structure, not applicable for comparison across industries with different margins
Capital structure agnostic and controls for negative earnings firms
Sales not applicable for comparison across industries with different margins
Source: SPDR Americas Research
To put this into practice, the different metrics for an aggregated portfolio containing all 18 Broad Innovation funds compared with the broad S&P 500 Index are illustrated below. As shown, the average figure for the Broad Innovation category is higher than the broad market – as would be expected. However, when it comes to enterprise value-to-sales, the skew is much tighter, given the dynamics discussed above. Yet, some of these multiples are trading below the levels we see in traditional S&P 500 Growth stocks, while broad-based innovation funds are expected to grow earnings at a greater rate over the next three to five years (19.50% vs. 15.24%).9
P/E using FY1 Est
S&P 500 Growth
Average Broad Innovation
Difference to S&P 500
Difference to S&P 500 Growth
Source: FactSet as of November 30, 2020
Ultimately, these exposures are indeed trading rich. But the multiples are elevated to the broader market as a result of the high expected growth estimated and the potential for future growth opportunities as a result of the behavioral changes.
Thematic exposure analysis key in 2021 and beyond The inflection point from COVID-19 in our global society is likely to lead to an increasing need for innovative technologies that allow for more contactless interactions, advanced medicine, digital connectivity, and intelligent infrastructure.
The increasing number of options available to investors to participate in these next-generation trends is one of the reasons that we developed a framework for classification as the first step in due diligence. Once you define the universe, it’s important to understand the construction approaches within a certain exposure. And for investors trying to ascertain valuations, amongst the sea of multiples available, enterprise value-to-sales may be the most appropriate.
For more insights, continue following the SPDR Blog.
1 Bloomberg Finance L.P. as of December 15, 2020 based on SPDR Americas Research calculations. 2 Bloomberg Finance L.P. as of December 15, 2020 based on the S&P 500 Growth Index based on data from March 1994. 3 An intangible asset is an asset that is not physical in nature. Goodwill, brand recognition and intellectual property, such as patents, trademarks, and copyrights, are all intangible assets. Intangible assets exist in opposition to tangible assets, which include land, vehicles, equipment, and inventory. 4 Eighteen funds, as classified by SPDR Americas Research as of December 15, 2020. 5 Bloomberg Finance L.P. as of December 15, 2020 based on SPDR Americas Research calculations. 6 Bloomberg Finance L.P. as of December 15, 2020 based on SPDR Americas Research calculations. 7 The harmonic mean is a type of numerical average. It is calculated by dividing the number of observations by the reciprocal of each number in the series. The weighted harmonic mean is used in finance to average multiples like the price-earnings ratio because it gives equal weight to each data point. Using a weighted arithmetic mean to average these ratios would give greater weight to high data points than low data points because price-earnings ratios aren't price-normalized, while the earnings are equalized. 8 EV is the market capitalization of a company as well as short-term and long-term debt less any cash on the company's balance sheet. 9 Bloomberg Finance L.P. as of December 15, 2020
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