Let's just return to what we've seen on Wall Street, particularly with the AI trade. Back in the driver's seat essentially after another strong round of hyperscale earnings. Let's get across what is ahead, though Sam Ruiz joining us from T Rowe Price. Sam, welcome back.

Hey, Andrew.

So we have seen those hyperscalers have been under pressure. This week, some real positivity to the point where it obviously pushed the the major indices higher. What have you made of those hyperscale earnings?

Yeah, well, we had a very volatile July. It isn't that long ago, but it was on the back of one of the best positive months of momentum in June and most of that sold off to be one of the worst momentum months in July. Why was that? Last time we spoke, we were flagging that we had this big moment coming for earnings where later in July, the hyperscalers would all be putting up their prints for CapEx and for monetization and margins within AI. So, with this enormous rally we've seen, it is really a big question mark in the market of can this momentum be sustained and also we're spending so much money on this AI cycle. Is it worth it? Are they going to actually make money from it? It was an unequivocal beat to expectation and really positively reaffirmed to the market. AI is making money. There are so many examples, from Open AI to Anthropic, even to SpaceX. SpaceX was down a lot last night. Let's put this into context. They have said that they think by the end of this year, their run rate revenue for AI compute is going to be $100 billion. You kind of have to just let that settle. These numbers are getting so large now the context of it is lost. So, all of this is reaffirmed for us that the AI cycle is alive and well. It's just this game of expectations now. Are the beats big enough? And then it could just be, let's roll through each quarter and make sure that we're continually reaffirming the positivity.

I mean, you mentioned what you see, particularly open AI, Anthropic, they've yet to come to the market. SpaceX obviously shares have come under pressure despite those are those beats that you've just mentioned of there. And on top of that, Sam, since we last spoke, of course you've had the emergence of another low cost model coming out of China raises that question of those those so-called open weight models and the challenge that lays down to the American business models.

Yeah. So those those American sort of frontier labs call them open AI and Anthropic still have the leadership. And it's not just this Kimi out of China that's doing open weight. Even NVIDIA already has an open weight model. There is a real tuggle sort of tug of war here happening. What it is, is we know that a lot of the the world would like lower cost models. That's open weight. We know a lot of enterprise, big large software companies want open weight. Why? Because they can put all their IP into ecosystem that they don't have to share it. If they give it to Anthropic or if they give it to Open AI, they're effectively sharing their IP and maybe allowing them to compete in the future. The problem is that Kimi is about 94%-95% as good, which was quite amazing actually for an open weight model with a six month lag. But that 94 percent is still not good enough for a lot of sort of the best cases to trust that the 94%.

It's going to get better though, isn't it?

It’s like I said, it's a three to six month lag right now. So as long as the frontier labs can continue to get better and better, it's called scaling laws, how much their models improve. That means that the open weights are going to be at this lag where they're potentially just not good enough or the value the better models are adding is better and worth paying for. Really important thing here, we're debating a lot right now is, what does that mean for how quickly this accelerates the need for those Frontier labs to accelerate to the next offering? We think that they're going to have the need to actually vertically integrate their products and maybe do this more quickly into an ecosystem. Let's call it the iPhone. They want to be the iPhone of AI where all the use cases have to sit on their system and they can effectively collect the rent and the tax. And if they don't do that, then potentially they get commoditized by open weight models, which is what you're inferring.

Where then does, where do those AI hardware stocks sit? You talk about potentially being in a sweet spot. How so?

So that is actually a great follow up question because there are hard problems in the market to solve and there are easy problems in the market to solve. The hard problem is what we just said Frontier Labs versus open weight timeline, how quick does that move? What we know though is that open weight models are still very, very hardware intensive. And if they start to gain traction, if they start to take market share, we know that the combination of open and close weight models together is just even further accelerating and further growing the demand for the AI compute capacity and infrastructure that sits behind that. So, coming out of earning season and even as a result of this Kimi release we saw in July, we're actually more bullish now on what that means for, call it, the next 12 months of demand for AI hardware.

Are you then bullish overall for market growth, particularly what you're seeing on Wall Street at the moment, given these results, given your forecast there, do you think that momentum can continue?

More optimistic. So, July was quite bad, particularly. Let's put this into context. AI has been one of the single things driving the market. It's responsible for almost all of the earnings upgrades and the majority of earnings growth that we're seeing. Are we thinking that we're still going to see that going forward? Yes, earnings are an upgrade cycle. We're also seeing in the US something that could derail this inflation, is actually relatively contained. And we're not seeing the yield curve, the long end move away war, Iran sort of energies is a bit of a hotspot when we're not seeing really closely. For now, we're actually seeing economic growth, corporate earnings growth and that volatility we saw in July was not on the back of earnings compressing. Earnings are actually still accelerating, which means it was a narrative LED sentiment LED sell off. And that for us feels more like a mid cycle correction, which is really healthy in the market as opposed to warning signs that we're starting to see a deceleration of growth. And that's something where we think multiples deserve to move lower and investors should be more cautious, but we're not there yet.

What are the other risks you're looking at the moment? Not the least, of course, being a massive amount of debt been taken on to fund this AI growth and whether there's the capacity to absorb that?

Yeah, that is a key question right now. There is more than likely going to be more debt and equity issuance, particularly by the big hyperscalers. They have a really big role to prove that they can actually monetize that. And it's worth investors allocating that debt to them. Why? Because otherwise their valuations will compress. If investors don't believe the story, their cost of funding in debt markets will increase. And that makes it incrementally harder for them to actually fund their ambitions. Put it in in the context of equity markets. If they want to raise, you know, Alphabet raised $85 billion of equity, I think last quarter. If their valuation falls 20%-30%, they have to dilute more to do that. So for now, these companies can actually take on a lot more leverage than what they already have and it would still be quite responsible so long as the returns are there. So for now, I think leverage is growing and will become a problem. For now, I'd say the bigger question mark is keep track of whether they are showing proof and evidence of monetization and the payoff which they have shown last week in earnings. They are. And that means that investors for now will say we back the extra leverage because we know it's got payoff for now.

We are somewhere in a bubble

We really believe that we are somewhere in a bubble and we would definitively call it that. And of course with bubbles you can have mid cycle pull backs.

If we look at an analogy here and I like this chart because it's actually pretty simplistic.

What we're doing here is we're just plotting the S&P cumulative return, the tech bubble versus now.

So in the Navy blue line, you see the launch of Netscape actually in August 1995.

And similarly we have the pink line, which is the launch of ChatGPT in November 2022.

And you can see quite a similar trend here, strong upward cycle.

In both instances we've had mid cycle pullbacks, so back in ‘98 and of course last year with tariffs and now this year and in the first quarter as well with concerns around the Middle East.

That said, we fundamentally believe that there is further for this market to run and why is that?

Multiple reasons we can talk through, but one is actually the monetary stimulus is still feeding through with a transmission mechanism.

We have the rate cuts coming through from last year.

Secondly, as the fiscal spend coming through and the one big beautiful bill so-called, this has been genuinely quite supportive and the US is running a deficit of 6%, which we can discuss the sustainability of that, but is giving a genuine fiscal impulse to the economy on the demand side.

In addition, we are seeing elements of speculation and frenetic moves.

We do think we're seeing indications of retail hype, meme stocks for example doing pretty well again, profitless tech performing very well last year as well.

And the top 5% of beta, the really sort of more speculative growth, these stocks doing relatively better.

Fascinating example is Allbirds, the sneaker company that you know was very trendy back in 2021 in Silicon Valley and then had its time and kind of went out of fashion and was almost written off in investors minds.

And they then said a couple of weeks ago, look, we're pivoting. We are now going to be a compute company and we're going to buy GPU's. And the share price of that company was up 600% in one day. So clearly elements of speculation here and signs of a bubble.

Don’t leave the party early

Leaving the party can be just as bad as not going. And actually, if you look back to the tech bubble and the NASDAQ performance, over 50% of the four year total NASDAQ return occurred in the final year.

So what are we doing here?

We're very fortunate to have such a broad platform of analysts who have the time and the capacity to be on the ground meeting management teams, building bottom up models and forecasts.

And what we're doing is we're focusing on participating where the fundamentals really justify that is companies where we're seeing real earnings upgrades coming through, real pricing power management teams that we trust to allocate capital effectively throughout the cycle and market share gains in this competitive environment.

So we have to navigate this responsibly. And we're very fortunate to have the the platform to be looking at all these companies in this excitement.

Our bubble-watch framework in action

What we've done is we've said, look, we need a framework to make this systematic and not emotional.

So we've studied a lot of prior bubbles to look at the conditions for bubbles and also conditions around which bubbles do end.

And there are five key points that we would draw upon here.

And as you can see on the right hand side, we have sort of we're taking the temperature on each of these.

We've got a bit of a traffic light system; green looking more promising, red high risk, a little bit more flag for concern. On interest rates, bubbles do not pop with interest rates flat or going down.

Historically, they only tend to pop when rates go up.

Now of course, US, Iran does add a little bit of nuance here.

But that said, when we look at everything coming out of the Fed and we speak to our macro analysts, they will tell you that this is a supply side shock and hiking rates is not going to change the price of oil unfortunately. That is not how the transmission mechanism works.

In addition, the Fed does have a dual mandate and it has to focus on both employment and output as well as inflation.

And so we need to be cognizant that whilst unemployment is in a very good place right now, we may ultimately see some pressures from some of the cuts being put through thanks to the productivity gains.

So right now, we're feeling neutralist on rates, a little bit worse versus the start of the year.

But on our side, we're not expecting an aggressive hiking cycle right now in the US in particular.

What about the broader economy and employment?

Of course, bubbles do tend to pop when we see recessions and that is something to watch.

But as I mentioned, actually the global economy was in an encouraging position before this kicked off.

And we don't invest in economies, we invest in companies, in bottom up stocks.

And if you look at the earnings of these companies, they're still accelerating.

We're seeing the all country world index, we're seeing high teens expectations for the next year as in EM, we're seeing higher 28% growth expected on a one year view.

So we're still seeing encouraging signs coming out of companies as they report and no imminent signs of a recession.

What about the AI super cycle?

When we look at historical bubbles, of course, when the tech price does not come through in reality, that can cause disappointment.

Scott and I have spent a fair amount of time meeting the companies this year, but also on the ground in Silicon Valley.

And what is fascinating is actually this is a piece where we feel even more constructive than at the beginning of the year.

One example is if you look at the scaling laws, the models that are coming out are only getting better and better and more powerful.

And you can see that in Mythos, for example, the release from Anthropic, where it was deemed so powerful that actually they did not want it to be yet released to the general public.

And it's being used to shore up cybersecurity for some dominant companies.

So of course, we need to watch for risk of CapEx cuts.

But actually, this week, even with the MAG 7 results, we've seen further CapEx increases.

So one to watch, but an area we still feel very good on.

What about leverage? Leverage is #1, where again, if you see excess leverage and of course, a hiking rate cycle. #2, that tends to be bad for bubbles.

Net, we want to run a lot of data on this front. And sovereign debt is a place to monitor with higher fiscal debt to GDP. But private debt is still in a very good pace.

Households have deleveraged substantially. Post to GFC.

And whilst we're seeing pockets of stress in private credit, when we really dig into it, there's nothing we see that is genuinely systemic on that front.

And then very lastly, geopolitics. As I mentioned, we are running a lot of scenario analysis here, but ultimately this is a place where we feel worse unequivocally versus the start of the year.

So that is one reason why we have pared back the beta of the portfolio at the margin from 1.13 coming into the year versus our core benchmark to 1.08 at the end of the first quarter.