Why a fund approach to investing in tech stocks can be better than individual stock picking

By Janus Henderson´s Global Technology Leaders Team

In this article Janus Henderson’s Global Technology Leaders Team discuss why technology investing benefits from active management.

Key takeaways:

• The generative AI wave will last for multiple years because of the level of investment required, with multiple up and down periods, and hype cycles.
• The characteristics of the tech sector lend to the merits of actively managed investing versus selecting individual stocks.
• Active management, guided by managers with extensive experience of navigating previous technology waves, enables better identification of potential winners, particularly with the return of cost of capital in this ‘winner takes most’ industry.

Technology stocks’ outsized returns over the past ten years,¹ coupled with generative AI promising a myriad of investment opportunities, has led investors to pile into tech stocks, often using leverage. But it also means concentration risk has significantly risen in a few names (Magnificent 7). This heightened market volatility is causing more dislocation of share prices from company fundamentals and highlights the need to be selective.

Why active matters

1) High growth – the assessment and valuation of tech companies is challenging due to their high growth potential and often intangible assets. Experience and expertise is needed.

2) Highly disruptive – an active risk aware, stock-picking approach enables the identification of companies that are likely to be disruptors rather than those being disrupted.

3) High volatility – active managers can identify valuation versus fundamentals disconnects, typical in a fast-moving, innovative sector.

4) High risk – active managers can employ portfolio diversification to reduce downside and concentration risk. ESG integration and company engagement can also enhance valuations, reduce risk and help future proof a company.

Gen AI: not just a theme

Our experience of successfully navigating through previous tech waves like the PC and mobile internet tells us generative AI is a true technology wave, because the cost curve of adoption is being structurally flattened. A huge amount of infrastructure has to be built out because gen AI isn’t a single product. We see gen AI as having multiple investment layers; this is important because we need to think about where we are in the tech adoption hype cycle, how long it will last and how you invest in it.

Figure 1: Compute waves have lasting effects; what we can learn from past waves….

In the third wave – the mobile internet wave, there were over six years of strong double-digit returns (Figure 1). But significant volatility accompanied these strong returns. Looking at the third wave, even when returns were up more than 60%, there were double-digit drawdowns. The key is knowing when you have a drawdown, and identifying when there’s a significant price dislocation.

The fourth wave, the gen AI wave is only moving into its third year (since ChatGPT’s launch in November 2022), and we’ve already seen a significant drawdown. This is when you find the leaders and losers. This wave is set to last for multiple years due to the level of investment required, and will see multiple up and down periods. Looking back at the second wave, the initial area of investment was in silicon (semis), with companies like Intel and AMD driving that first cost down in Silicon Valley.

Similarly, in this fourth wave, NVIDIA as well as companies like Broadcom are the bedrock of the AI ecosystem. The first layer is the building of the physical infrastructure (GPUs, data centres, etc) and the foundational models (ChatGPT, large language models etc). Next comes the platforms – the GPUs need to connect with the data centre via networking, and then much higher speed connectivity is needed to connect them to the last mile user.

The second layer, AI platforms, are starting to emerge now. Typically these look to be the cloud platforms/hyperscalers that have the balance sheet strength to invest, but also because they’re involved in every single layer, hence can offer a full stack solution. We’re starting to look to transition from semiconductors to networking and other areas that will benefit in this second phase. The last phase will be the most exciting, the application and software layers, which is likely to be a good few years out from now. Our team is deliberating on what the time scale for this to start playing out might look like. To what degree can it be very easily upgraded on to an existing offering? To what extent does there have to be training to the end user to be able to do this? Remember that Uber launched in 2009 but didn’t have its IPO until 2019 to become a viable investment.

What’s the benefit of actively investing in tech?

1) Navigating the hype cycle and ESG considerations

Identifying companies with a sustainable competitive moat and strong growth potential with rational valuations is essential to benefit from the generative AI wave. Maintaining a strong valuation discipline is key as investors often get overexcited about the pace of new technology adoption. Lots of capital comes in and then it unwinds. We’ve seen this through 3D printing, the internet bubble, and ultimately we will see this through AI. The magnitude of capital spending for gen AI looks to surpass previous waves given its potentially wider ability to disrupt the economy and impact supply chains, costs, competition and sustainability.

Figure 2 illustrates the stages of the hype cycle of new technology and how it aligns with tech adoption. We use the hype cycle adoption curve to guide us in our thinking and decisions; history has shown us adoption is always much broader than initially thought. You have to identify those strong long-term themes, understand the path of the waves, and then integrate sustainability factors using a financial materiality lens, which supports a company’s success in the long term. Gen AI, with its multiple investment layers, will see each layer having its own hype cycle, with each generating risks and opportunities to navigate.

Figure 2: Navigating the hype cycle

2) Size is not a stock picking strategy in technology

Selecting stocks by size is not a strategy for stock picking. Technology is a scale market. So while you can simply buy the top ten largest stocks in an index, it would be a huge mistake to not invest in some of those winners absent in that top ten. Looking back ten years ago, the top ten holdings in 2014 and the following ten years, only three of those stocks relatively outperformed, but they did so spectacularly (Figure 3).

Looking back between 1990 and now (Figure 3, table on the right), for companies that had hit market cap of US$1 trillion, 100 billion, 10 billion, 1 billion, buying each company that hit US$1 trillion, you would have doubled your money the fastest, with an 80% probability of achieving that. Whereas if you bought small caps at US$1 billion, you only had a 47% chance of capturing a stock that would double. So active management means not just owning all of the top ten, and it doesn’t mean abandoning all of the leaders that will be crucial to the success of the gen AI wave, because you could miss out on some of the strongest returns.

Figure 3: Technology sector: size is not a stock picking strategy

Also, branding the large caps as one homogenous group, isn’t accurate. The Mag 7 isn’t a monolith (see Figure 4). On a valuation basis, Walmart trades on four multiple points (P/E ratio) more expensive on 2026 earnings than Amazon, but it has slower growth and much lower margins.

Comparing Colgate vs Apple, McDonald’s vs NVIDIA, these companies trade at a similar level, but the contrast in earnings growth (EPS) is stark, with almost double the growth from the consumer tech companies. They also have a lower PEG (price/earnings to growth) ratio, which shows higher underappreciated earnings, which we believe is the best guide to future performance. We are constantly trying to add value for our clients through the active management of identifying smaller companies but also adding value in larger companies.

Figure 4: Magnificent 7 is not a monolith; growth, valuation, momentum, capital intensity and allocation vary significantly

A strong case for active management

Ultimately, the best way to gain exposure to tech is dependent on investment goals, risk tolerance, and time and effort to manage the investments. We would argue that compared to individual stock picking, investing in a fund with an active manager may be a more prudent approach when it comes to technology investing. With the return of the cost of capital, selecting the winners in a ‘winner takes most’ industry such as technology is key. As a team, we believe that providing exposure to multiple themes across the underlying AI compute wave, and identifying areas of unexpected earnings growth, is most likely to drive stock market returns over the coming years.

Footnotes:

¹ MSCI.com; MSCI World Information Technology Index in USD vs MSCI World, 10-year returns to 10 March 2025.

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