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The Magnificent Seven: tech stocks, AI and US markets

In this week's episode, Susannah and Sarah look at the biggest names in tech, the Magnificent Seven: Microsoft, Amazon, Google (Alphabet), Tesla, Facebook (Meta), Nvidia and Apple. We also delve into the latest edition of the HL Savings and Resilience Barometer for an inside look into the nation’s savings and investments.
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This podcast isn’t personal advice. If you’re not sure what’s right for you, seek advice. Tax rules can change and benefits depend on personal circumstances.

This podcast isn’t personal advice. If you’re not sure what’s right for you, please ask for advice. Investments can rise and fall in value so you could get back less than you invest.

Susannah Streeter: Hello and welcome to Switch Your Money On from Hargreaves Lansdown. I’m Susannah Streeter – Head of Money and Markets.

Sarah Coles: And I’m Sarah Coles – Head of Personal Finance.

Susannah Streeter: And again we’re back in the studio together, and we’ve been talking about how much time we actually spend getting here. Today was a bit of a struggle! – especially for you, because you live by the sea – a fair way away.

Sarah Coles: Yes – and I always seem to get stuck behind a tractor on the way in. It was something that sprung to mind with the release of the latest government insights into how we spend our time – ‘cause it emerged that we spend about 1 hour 40 travelling each day – including the commute – which does feel about right on our studio-days.

Susannah Streeter: Yeah – it was a really interesting read all round, because we spend a similar amount of time – about an hour-and-a-half a day – using a computer outside of work – although I think, in my house, it’s way more – even 90 minutes a day is more than we spend on exercise and other wellbeing.

Sarah Coles: It’s part of the furniture of our lives now – including investment. So, we thought we should turn our attention to technology companies in this episode of the podcast we’re calling, ‘The Magnificent Seven.’

Susannah Streeter: Yes – there’s been a lot of excitement surrounding these tech giants – partly because of the potential which the acceleration of artificial intelligence capabilities, in the world around us, presents for them.

Sarah Coles: We’ll be talking to Sophie Lund-Yates – our Lead Equity Researcher – about a few of the ‘Big Seven’ and their prospects at the moment. We’ll also be speaking to Emma Wall – our Head of Investment Research and Analysis, who’ll be exploring this from a fund management perspective.

To get a greater insight into the sheer demand for all things AI – and how it’s breaking new ground around the world, we’re going to take a trip to the Arctic and speak to the founder of a company which is using AI to map ice patterns – to help the shipping industry.

Susannah Streeter: I am delighted to say Leslie Canavera – CEO of Pol Arctic – is on the podcast with us today. It’s really great to have you on. Leslie and I met in Arctic back in January – so it’s really great to hear your insights on Switch Your Money On.

Leslie – you must be super-busy right now, given how companies – large and small – seem desperate to benefit from AI advances.

Leslie Canavera: It has been really busy these past couple of months – as a lot more are looking to embrace the new technology.

Susannah Streeter: Really looking forward to having your insights a little bit later. But first, let’s delve into these tech giants.

The original ‘Magnificent Seven’ were a group of hired gunslingers on a mission to save Mexican villagers from marauding bandits. Nowadays, it’s more often the term referred to giant tech companies than Yul Brynner and the rest of the 1960’s movie cast.

Microsoft, Amazon, Google Parent – Alphabet – Tesla, Facebook (aka Meta), Nividia, and Apple have been dubbed the ‘Magnificent Seven’ – in part due to their scale and in part due to how their valuations have risen.

Sarah Coles: Six of the Magnificent Seven companies are valued at over $1tn – with Tesla being the exception at $550bn. Together, they’re valued at an eye-watering total of around $14tn.

Susannah Streeter: Between them, they make up nearly a third of the S&P 500’s total value (an index tracking 500 of the largest US companies). So, the US stock market’s performance is very heavily weighted to the performance of these seven companies.

That means that, even if you don’t hold them individually, you might do – if you invest in a fund which tracks the US stock market – or hold a pension which is invested in slices of the US market.

It’s also the case if you hold a fund that tracks a range of indices, worldwide.

Sarah Coles: Not only that, but their rise or fall holds huge sway in US indices, and then can influence sentiment across wider financial markets.

It means that, even if you don’t really care about technology companies – and how they’re doing – they could still have an influence on your investments.

Susannah Streeter: Within the group are some extraordinary commercial propositions:

The three leading cloud computing providers are in there – so is the world’s dominant office software suite – and the operating system running in the large majority of PCs. The world’s leading electric vehicle manufacturer is also on the list – Tesla, of course – and so too is the dominant producer of artificial intelligence (AI) computing capacity – Nividia – along with the major e-commerce player, Amazon – and the western hemisphere’s top search engine, Google owner – Alphabet.

All claim to have their eye on the current prize of being a big player in artificial intelligence – and it’s the possibilities that AI will present in the future for these companies that are the big drivers in their valuations.

Sarah Coles: Few investors will have held all of these companies from their early days. Their commercial success is something that’s compounded over time and hasn’t always been as it might appear today.

Nvidia were seen as a niche producer of graphics chips – which was good at what it did, but constrained by its niche. Not anymore. The applicability of Nvidia’s intellectual property to AI computing has dramatically increased the commercial opportunities the company faces. It’s had a storming ride – repeatedly sailing past investors’ expectations in terms of its results – to reach new heights. But it’s unclear if that will continue – and how much demand for AI chips may fluctuate in the future.

Susannah Streeter: Tesla has been plagued by production challenges that would have seen off many other manufacturers. Its share price has been on a volatile ride recently – as we’ll discuss later with Sophie – partly given just how competitive it’s been in the EV space – but also because investors have raised questions about its AI credentials – especially given that the future of autonomous driving is still uncertain.

Apple has been seen as lagging behind the AI revolution compared to some of its peers – and it’s been tight-lipped about its plans, despite speculation that it’s working on its own chips for data centres.

Some of the frustration has been reversed recently following a record stock buyback plan – but still, questions have been raised about whether Tesla and Apple deserve a place among the Magnificent Seven after all – and whether the giants should be limited to the ‘Famous Five’ – of Nvidia, Microsoft, Meta, Alphabet, and Amazon.

Sarah Coles: Certainly, if you take their latest rounds of results and expectations for Nvidia – which is yet to report – they show another round of strength – and big step-up in profits growth. The big question is, ‘Will this continue?’

Susannah Streeter: Forecasts are creeping in, showing a slowdown in earnings ahead – while the results of the other 493 companies listed on the S&P 500 – those not tagged as the ‘Magnificent Seven heavyweights’ – are expected to show an acceleration of profits.

Sarah Coles: With hopes rising again for US interest rate cuts this year, it’s also set to buoy the wider index, rather than the slim, but mighty group of seven being responsible for gains. But, of course, much will depend on other data popping up with regard to the strength of the US economy, as the exact trajectory of rates remains highly uncertain, and could still cause volatility ahead on US markets.

Susannah Coles: Then, there’s regulation.

Being big has its downsides. Regulators get nervous when businesses become too influential – or even dominant. Investors have to try and juggle the success of these companies with the risk that regulation eventually clips their wings.

Sarah Coles: There’s also concern about big bottlenecks on the road to AI adoption.

Demand for generative AI solutions – harnessing the power of large language models – requires a huge well of data – and that’s got to be stored somewhere. Tech companies and cloud solutions providers are racing to provide that storage to satisfy all the demand.

Susannah Streeter: This presents a huge opportunity for the big tech giants providing the infrastructure, but there are warnings that these power-hungry data centres – essentially, warehouses full of computer systems – could put a big strain on electricity grids, globally – and may struggle to cope with demand.

Sarah Coles: With all that in mind, let’s bring in Sophie Lund-Yates, who’s been exploring some of these behemoths.

So, Sophie – we don’t have time to talk about all the Magnificent Seven stocks, but who’s up first?

Sophie Lund-Yates: Hi, Sarah – I think it makes sense to have a bit of a deeper look into Tesla.

Tesla has lagged some of the other big names. This is partly because the wider excitement is largely linked to AI, and – as Susannah has mentioned – Tesla’s exposure to this tech is less cut and dry than it is for others. It’s also a lot more exposed to the consumer mood than others. Selling cars at a time of economic uncertainty is a tough ask, regardless of how nice the cars are.

Tesla’s results, a few weeks ago, did disappoint the market. That was more to do with the outlook statement, which included the fact that volume growth will be notably lower this year – as new vehicle launches take priority. The group is speeding up planned product launches, which may affect cost savings too, but boost long-term efficiency. Essentially, Tesla is trying very hard to combat climbing competition, especially in Asia. This also means average selling prices are now under pressure.

The group does have some angles pointing towards AI. Software is a potential outlet for extra growth – the group’s self-driving technology has already delivered to existing vehicles through wireless updates. This lends itself well to software subscription programmes, which would help pad profits and squeeze more out of cars already sold.

Another potential avenue is insurance. It’s still early days, but Tesla is already seeing green shoots. Driver data is used to set premiums. This creates an instant feedback loop, ultimately encouraging safer driving. Tesla is responsible for fewer accident costs and customers save money.

Tesla has an amazing position in the market – and there’s a lot to be said for that. The shorter-term, potentially, looks a bit tricky in my opinion though.

Susannah Streeter: So, that’s Tesla – who else have you been looking at?

Sophie Lund-Yates: Next up is Meta – which, of course, owns Instagram, Facebook WhatsApp, and Messenger. Its latest set of results – which were in April – saw a reversal in its spending plans. The groups has said it’s going to reinflate its budget so it can really go for it with AI products.

The reason this initially spooked the market is because Meta had recently reined in its spending to refocus on the core advertising business. Not because there’s anything wrong with spending on AI, but because there wasn’t an iron-clad plan. Spending needs to be targeted and in-line with a clear strategic view. The ‘See what sticks’ method of years gone by won’t be tolerated ty the investor base.

Meta’s resources are vast – but they’re not infinite – and its digital advertising market share needs to be defended at all costs – and that means being disciplined, first, but in tandem with some moonshots in the background.

Obviously, I’m not saying [laughs] this is the end of Meta – it’s simply that uncertainty about exactly what the strategic targets look like has increased. This is still a company that made $12.5bn in free cashflow in the last quarter – so the apple cart is still very much upright. What I would say though is that we could see some ups and downs if Zuckerberg’s plans are deemed too woolly.

Sarah Coles: ‘Woolly’ is not a word we hear too often in equity analysis. Who’s the final name?

Sophie Lund-yates: That would be the very non-woolly Microsoft. So, reaction to its latest results were relatively muted, but that’s partly because the bar’s been set so high.

Investors are aware that Microsoft is in one of the strongest positions to benefit – so make money from the adoption of AI. AI products and services can be integrated into the majority of the group’s existing products – and things like its huge cloud business are also primed to benefit.

With that said, technology budgets could still face some pressure. End customers are likely going to trim spending while they ride out the economic storm. The potential for Microsoft to do exceptionally well from generative AI remains, but the exact moment in time that this tech will be adopted at large will depend on if and when corporate spending picks up the pace – and there are no guarantees.

There are more strings to Microsoft’s bow too. The acquisition of ‘Call of Duty’ maker – Activision Blizzard, for example – is offsetting declines in physical hardware sales, reflective of the challenging consumer environment. While this trend plays out, it’s important to consider the growth levers available to Microsoft.

In terms of things to watch out for, I’d say it’s really important to keep an eye on competition dynamics. In the grand scheme of things, we’re still in the early days of the AI race – and regulatory and political pressure are also things that can move the dial.

Susannah Streeter: Thank you, Sophie – it seems as though we’re on the cusp of some fairly dramatic technological changes, so there will be plenty to watch.

And, of course, as AI bleeds into the world around us, it’s changing the picture dramatically – right across the globe. It is a good idea to explore the impact in an area at the cutting edge of technology. Let me bring back in Leslie Canavera – CEO of Pol Arctic, which uses AI modelling to forecast ice patterns in the Arctic.

Leslie – tell me a bit more about what AI is making possible in terms of navigation in the Arctic.

Leslie Canavera: We see so much happening with climate change now – and change in how patterns are behaving – and things are impacting and reacting to that.

You can think of climate change as a non-linear process – where, if you push it so much, then it changes more than that or less than that.

Artificial intelligence has a unique way of capturing that – that other modelling techniques don’t. Artificial intelligence is able to learn the behaviour and really model it and forecast the future more accurately than these other techniques.

Sarah Coles: So, what semi-conductor chips and infrastructure do you rely on for your operations? How easy are they to acquire?

Leslie Canavera: We use Nvidia GPUs. They have been easy enough for us to acquire here in the United States. The reason we use them is because of the compute that they’re able to do – and the parallel processing. This is a traditional way to do a lot of artificial intelligence modelling.

Susannah Streeter: When did you realise that the Arctic was potentially a good business opportunity for you – and who did you launch your venture with?

Leslie Canavera: I’m from Alaska – I’m Yupik-Alaska-native – and my cofounder is my sister. She is also Yupik-Alaska-native – but we had really different paths. I went into the United States Air Force – got a background with satellites and remote sensing – and, from there, I went to the National Geospatial-Intelligence Agency – did some more with that. She became a Physical Oceanographer – did all the modelling for how currents and different ocean phenomenon behave – did a lot with oil spills and the Deepwater Horizon oil spill in the Gulf – and, when that was wrapping up, I called her up and noticed there was a big gap for the Arctic – for coverage and things that are gonna be changing with climate change – and you can see that.

So, we started the company – and it was a risky proposition – going into it – because the Arctic is an emerging place – but, recently – with everything going on in the world – people are starting to really look at, ‘What would Arctic shipping look like?’ – and then, ‘How would we understand and price that risk?’

Susannah Streeter: What kind of clients have you attracted?

Leslie Canavera: It’s been a lot of different types of clients. We’ve had a lot of shipping companies – that’s the most tangible to be able to understand when and where you can travel. We’ve worked with fishing companies, who wanna know where that ice edge is – so they don’t lose the gear – essentially having ghost gear in the Arctic. We’ve had some contracts with the US Government as well – for the Department of Defense – for understanding, ‘What does that operational picture look like?’ We’ve also been working with insurance – and Lloyds of London – for being able to them price that risk accurately.

Sarah Coles: You talk about the Arctic being fairly unpredictable in the past – so what’s the drawback in terms of the data that you can draw from when you’re trying to predict the future?

Leslie Canavera: The Artic can be a data-desert – it’s hard to study. We don’t have a lot of in-situ measurements – or booeys in the Artic gathering data – so there’s a lot of challenges with actually getting that on-the-ground data. But what we’ve done is combine two different systems of knowledge: one is Western Science and one is traditional, indigenous knowledge. We are Yupik-Alaska-native – and that really helped for us to really value that kind of knowledge system – but that opens up a lot of data and possibilities for being able to model the Arctic – and understand and forecast it more accurately.

Susannah Streeter: Given the fact that you’re using all types of knowledge, what would you say your experience tells us about the problems in accessing good quality data to run bigger models – and just what should be done to ensure that there isn’t bias or gaps in those models?

Leslie Canavera: All the models rely on data – and, if your data is bad, your model will be bad. When you have inherent bias in a system, you encounter all sorts of things that you might not even realise in your data.

There’s a great example of a group that went and collected a bunch of medical information from an area – but, because they used primary care physicians in the United States – which a lot of people of colour do not use – they excluded a whole racial group. And so, your data – inherently – is biased from the beginning – and so the information and the models it’s providing to you are not going to be accurate. When you’re able to include multiple knowledge systems, you’re able to include larger datasets. It really impacts the quality, going forward – and I think that’s gonna be a big challenge for the ‘Big Seven’ – because, when you get so big, you don’t even see your blind spots.

Sarah Coles: it definitely seems like there’s a lot to be learned along the way for AI. What sort of phase d’you think the world is in right now when it comes to AI development?

Leslie Canavera: I think we’re in early-adoption. We’ve seen a lot for Silicon Valley and been able to have the $billion, $trillion dollar industries addressed – but there’s a long tail in Ai, and that can address lots of different areas – lots of different regions – and I think we’re really early in that.

If you look at the diffusion of innovation – and how ideas spread through society – artificial intelligence is at that beginning critical 10% of adopters – and looking at it. I think we’re at the cusp.

Susannah Streeter: So, if we’re in early-adoption, d’you think AI capabilities and benefits will accelerate, but then plateau in years to come?

Leslie Canavera: For different types of AI, I think it could – and I think you see that with large language models – and ChatGPTs – and all of those groups that are coming out. I think there will be plateaus for different technologies in AI at different times. What we’re looking at – form climate technology – I don’t think we’re there yet.

Susannah Streeter: So, which other sectors d’you think could really benefit from your technology?

You’re focusing right on the Artic – and ice patterns, in particular – where else d’you have your sights?

Leslie Canavera: Like I mentioned – insurance. One of the interesting things is that, where the ice breaks up in the Arctic – and when it breaks up – actually impacts wildfire in the United States – continuous United States. And so, when you’re looking at property insurance, that’s a really big factor. You can also look at electrical grids – and how the electricity is used and flows through those. The same type of modelling techniques that we’re using could be used for electric grids. It could also be used for economic forecasting – hedge funds, stock markets – things like those.

Sarah Coles: Do you think greater regulation could help, or d’you think it might actually hinder the process?

Leslie Canavera: I am very ‘For’ regulation. I think why I’m for it is because it needs to build trust for the AI systems – and, if you don’t have regulation – and you don’t have that trust – then you’re not gonna get as fast of adoption – or you’re gonna get that bias we talked about earlier. The way people are building them – and the decisions people are making with them – are not gonna be accurate or reliable. And so, I think regulation will only help the AI industry.

Sarah Coles: Thank you, Leslie – it’s been absolutely fascinating – and I wish you the best of luck for the future!

Leslie Canavera: Thank you for having me.

Sarah Coles: So, with another eye on the future, this feels like a good time to bring in Emma Wall, who’s been speaking to Lauren Romeo – from Franklin Templeton – about the technology sector.

Emma Wall: Hi, Lauren.

Lauren Romeo: Hi, Emma.

Emma Wall: We’re here today to talk about AI – the AI revolution – the ‘Mag Seven.’ It’s completely transformed the US stock market – in fact, the global stock market – over the last year. As a US equity investor, what impact has the ‘Mag Seven’ had on the broader US stock market?

Lauren Romeo: First of all, it’s fuelled exceptionally strong performance in US large caps. If you look at the S&P over the past five years, it’s generated a 16% compound annual return – and that compares to its per-year average annual return of 10%. But that significant outperformance has been driven by the top-ten stocks led by the ‘Mag Seven.’ They’ve produced one-third of the gain that you’ve seen over that five years. And the result of that is 1) narrow performance – and 2) much greater concentration in the index as those stocks have appreciated – and investors have piled into those ‘Mag Seven.’

So, if you look at the top-ten stocks in the S&P – are 33% of the S&P 500 – and that’s a new peak level that surpasses the level of concentration that we saw at the height of the tech bubble in 2000.

Emma Wall: Given how significant that rally has been, are you finding any opportunities to put into your portfolio? Your portfolio is obviously smaller companies’ fund rather than the ‘Mag Seven’ mega-stocks – but is there still value to be had in AI?

Lauren Romeo: Absolutely – particularly in the quality area – where there are a lot of companies that provide essential products or services that are key enablers of the AI revolution – or they’re poised to benefit from the second-order effects of its proliferation.

There’s an old saying of, ‘In the California goldrush, the prospectors didn’t make the money – it was the providers of the picks and shovels that made all the money.’ And so, that’s where our companies are – they’re the picks and shovels’ providers that enable AI expansion.

Emma Wall: Can you give me a couple of examples? Who are the picks and shovels?

Lauren Romeo: Fabrinet is one example of a company we own. They provide outsourced manufacturing of complex optical components that are used in data communications and telecom – and the AI relevance is that data centres – where all the processing of data and training of models for AI-driven applications is occurring – and are being done on Nvidia chips – which it has a monopoly there.

All of these AI servers are networked together – and, in order to take advantage of the speed that Nvidia’s chips brings, you also need to have faster communication between all the AI servers in the data centre. For that, you need an optical transceiver – and Nvidia, drawing on Fabrinet’s optical manufacturing expertise, has developed an optical transceiver that can transfer data at double the speed of the current standard transceiver – and that’s enabling these workloads to be done more quickly.

Fabrinet is the sole-source manufacturer for Nvidia for these products. They’re already working on the next generation, and it’s just gonna continue to ramp up in terms of the data rates at which these transceivers can send data.

Emma Wall: And any other companies?

Lauren Romeo: There’s several companies within technology – semiconductor capital equipment companies, such as FormFactor – which does wafter probe cards that are used in testing chips – and MKS Instruments that does critical components that go into this equipment. They’re growing because you need new equipment and tools to develop these leading-edge chips – and you need more of them.

Emma Wall: Let’s just briefly talk about the risks of any market bubble. You’ve been investing in the US stock market for a while. This isn’t the first time you’ve seen a trend and then lead the market. I just wanna put in a word of caution for investors – because this has been a very hot topic.

What risks d’you think there are associated with this – other than the fact that this bubble, potentially, bursts?

Lauren Romeo: That’s the biggest risk right now – and it really rests in large cap because that’s

where everyone has flocked to. I think investors were so early in this AI evolution that they’re going with the obvious winners. I think there is risk that the concentration is that high again. There’s been four times, historically, when the concentration was that high in the S&P – and, in each case, it really represented the peak of large caps outperformance over small caps. So, we actually like where we’re positioned – there’s a lot of things to like about small caps, generally – and this is just another datapoint where there’s a lot of overlooked names – where you don’t have the same valuation and inflation that you’ve seen – and there’s a lot more diversification of opportunities that aren’t reflecting the same sort of levels of valuation and expectations that the ‘Fab Four’ – that ‘Mag Seven’ – are!

Emma Wall: Lauren – thank you very much.

Susannah Streeter: That was Emma Wall with Lauren Romeo from Franklin Templeton – and please bear in mind that these are the views of the Fund Manager and are not individual stock recommendations.

You’re listening to Switch Your Money On from Hargreaves Lansdown. Before we go, there’s time for a quick stat of the week – and, for this, we’re taking a step away from technology and towards a new Saving and Resilience Barometer report HL has published.

Sarah Coles: Yes – it’s a special edition we’ve been working on, covering the efficient use of money. While that sounds a bit soulless, the idea behind it is incredibly useful.

So much of our financial lives seems about having to do more to be financially resilient, but millions of people don’t actually need to find a penny more to improve their resilience – they can just move existing money around very slightly and it’ll make a major difference.

Susannah Streeter: Yes – for example, 6.4 million households have no arrears and more than enough savings, but no investments. They can move the extra savings they don’t need for 5-10 years or more into stocks and shares ISAs. This could boost their overall resilience dramatically.

Similarly, 12.2 million households don’t have the pension savings required to retire with a moderate living standard. However, within this group, almost 7 million are not in arears and have excess cash or investments that could be used to boost their pensions or SIPPs.

Now, it is tricky to test this on you, Sarah, because I know you’ve been looking at this data, but can you remember – if they made this relatively simple behavioural shift – just how many more people would be on track for a moderate retirement?

Sarah Coles: It’s actually a really huge number – it’s 1.8 million households. So, that means sorting your retirement income without having to find any more cash – which has got to be an attractive idea.

Susannah Streeter: Yes – just think, if we can get those pension savings up, you won’t need to spend such a big chunk of the day schlepping into the studio late into your 70s!

Sarah Coles: [Laughs] Yes – by that stage, I do plan to take much more time capitalising by the fact I live by the sea.

Susannah Streeter: That is all from us for this time. Before we go, we do need to remind you that this was recorded on 13th May 2024 – and all information was correct at the time of recording.

Sarah Coles: Nothing in this podcast is personal advice – you should seek advice if you’re not sure what’s right for you. Investments rise and fall in value, so you could get back less than you invest. – and past performance is not a guide to the future.

Susannah Streeter: Yes – this is not advice or a recommendation to buy, sell, or hold any investment. No view is given on the present or future value or price of any investment, and investors should form their own view on any proposed investment.

Sarah Coles: And this hasn’t been prepared in accordance with legal requirements designed to promote the independence of investment research and is considered a marketing communication.

Susannah Streeter: Non-independent research is not subject to FCA rules prohibiting dealing ahead of research. However, HL has put controls in place (including dealing restrictions, physical and information barriers) to manage potential conflicts of interest presented by such dealings.

Sarah Coles: You can see our full non-independent research disclosure on our website for more information.

So, all that’s left is for me to thank our guests: Leslie, Lauren, Sophie, Emma, and our Producer, Elizabeth Hotson.

Susannah Streeter: Thank you so much for listening. We’ll be back again soon – goodbye!