Thematic investing can broadly be broken into two sequential ideas:
Whether or not the investor is successful afterwards (from a performance perspective) is based on many factors, the primary ones of which include:
To what extent do these identified disruptions actually materialize and create profits to the disrupting companies; and
To what extent is the success of the disruption already priced into the current shares when the investor purchased them.
For example, one popular theme is that the populace is becoming more concerned with carbon emissions and governments have incentivized the increased use of “green” or “clean” energy. One could deduce then that companies providing solar, wind and hydro power may be best suited to capitalize on the disruption in the oil and gas space. Without having to build a portfolio of individual companies, an investor can simply purchase a green energy ETF. However, there is still an additional level of due diligence necessary which we will discuss below.
While these questions might provide an interesting ideological exercise, they are also material in that the performance of these 31 ETFs can differ drastically. For instance, year-to-date performance (as of 8/10/2021) for the worst performer was -17% (a clean energy ETF) whereas the best performer was at +24% (an ETF focused on water infrastructure) 3. That is an over 40% spread for two seemingly similar investments. The below chart further illustrates the performance dispersion between these sustainability ETFs 4:
To take this notion further, lets step outside of the sustainability category and examine two ETFs in the robotics space (another disrupting theme). Both of the ETFs contain “Artificial Intelligence” in the name, both are global portfolios, and they have the same expense ratios. Differences start to emerge when examining holdings in that one portfolio is more concentrated (36 holdings to the other’s 74 holdings).
Astoundingly, there are only three companies that appear in both ETFs. As you can imagine, country weightings (e.g., US weighting of 71% vs 42%) and sector weightings (e.g., Tech weighting of 69% vs 36%) are also drastically different 5. It is not to say that one is better than the other, it is just that their holdings (and thus performance) are drastically different even when trying to achieve the same goal of isolating companies that can capitalize on “Artificial Intelligence”.
Moreover, active management coupled with a disciplined risk approach could also be appropriate for thematic investors.