We explained our thinking in a recent episode of our Macro Bytes podcast. But for those of you who want things in a more succinct format, here are some of the key points from that recording: 

What is thematic investing?

It’s investing in long-term themes – such as energy evolution; health and the generational shift; and transformational technologies – that will drive economic growth over the next decade and beyond (see Chart 1).

The primary purpose of thematic investing is to invest in assets whose returns are linked to forces that are broadly independent of the economic cycle.

The investment universe is huge and often these forward-looking, specialist companies are rarely represented within mainstream indices. To make sense of this large selection, we’ve identified 13 sub-sets of the three main ‘mega themes’.

 

Source: abrdn, August 2024

How is it changing?

It has really taken off in the past few years. According to Morningstar, ‘thematic investment equities’ assets grew to more than US$800 billion by the end of 2021, a three-fold increase on 2018.

Until recently, this style of investing was seen as something for retail investors only. But in recent years, more and more institutional investors have been getting involved.

When the so-called ‘smart money’ turns up, it will help broaden the appeal of thematic investing and build momentum for further expansion. 

Not all themes are created equal

Investors should try to focus on more durable and reliable long-term themes – such as ageing populations, robotics and automation.

There’s more visibility on the structural growth associated with these themes. However, growth and value creation are not the same thing. We focus on businesses with robust ‘economic moats’, which are more likely to capture much of the value within our themes.

That means we avoid some areas and themes, such as food-delivery platforms, 3D-printing and space exploration, where too many questions linger around monetisation.  

Do we like AI?

The impact of artificial intelligence (AI) will be profound. AI has been around for some two decades so what we’re really talking about are ‘large language models’ – advanced text-based AI tools.

But we need to be aware of their limitations. There’s a risk we over-estimate the monetisation potential of AI in the short term, and under-estimate its monetisation potential over the long term.

Businesses are still figuring out what this latest form of AI can do, but we have yet to see a paradigm shift that will change existing business models. Most of the value creation so far has been confined to the semiconductor industry.

What are the opportunities then?

AI models are significantly more energy intensive. When you also consider the impact of electric vehicles (EVs), the electrification of buildings and air-sourced heat pumps, just to name a few, you have a lot of things driving future electricity demand.

Investors should keep a look out for promising electrical-equipment manufacturers, or those firms that play key roles in electricity grids, or those involved in their expansion to meet growing demand.

AI will also need a big increase in processing power. The obvious way to play this is via the chipmakers and their supply chains. Perhaps less obvious are the data centres and everyone in the supply chain involved in upgrading them so that they’re fit for purpose.

What about in healthcare?

There’s been a lot of interest around the potential of weight-loss drugs, but the opportunity within healthcare is much broader. We are living through one of the more intense periods for healthcare innovation. For example, gene therapy and cell-based therapies hold a lot of promise for the treatment of Alzheimer’s, Parkinson’s and rare muscular diseases.

We’ve identified a company at the forefront of so-called ‘gene silencing’ techniques – in which treatment ‘silences’ the part of a gene that’s causing problems. From a business perspective, these therapies are attractive because they’re ‘persistent’ – you need to administer multiple applications, sometimes over a patient’s lifetime.

AI, once again, shows great potential in helping with drug discovery. AI-powered predictive tools can be used to sift through mountains of data to help researchers focus on those options that are more likely to yield the best results.

Will geopolitics spoil everything?

US-China rivalries overshadow the evolution of globalisation, and it has led to an increase in ‘near-shoring’ of production closer to markets.

So far, we’ve only seen a few sectors – such as clean technology and semiconductors – that have been directly impacted by protectionist trade policies.

Investment and manufacturing have moved out of China, but this has also benefitted other emerging markets – India, Mexico and Vietnam are just three.

When investing we look at opportunities at a company level – assessing the impact of tariffs on a business, trying to understand the risk to company earnings. Decisions are made on a case-by-case basis to identify more resilient ‘quality’ companies.

Final thoughts

Markets are driven more by ‘mega themes’ than before. We see this not just in technology – AI is the obvious one – but really across all sectors from consumer, financial and industrial.

While we’ve identified many themes, there is a great degree of overlap. For example, you can’t look at ‘energy evolution’ without looking at ‘transformational tech’.

In a world in which economic growth is slowing, we think the value of these structural growth themes is probably going to go up, rather than down.

More and more investors are starting to see the benefits of this approach – one that transcends traditional asset allocation by geography or sector.

The best way to capture the value from these themes is via a quality-first approach.