The overlooked defensive sectors to size up

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Markets are currently obsessed with the artificial intelligence (AI) story, meaning plenty of companies are getting left behind if they don’t fit the bill. This episode looks at the shares that have fallen out of favour, but could make your portfolio more defensive in a racy market.

00:00-01:00 Intro 
01:00-04:40 The defensive companies standing out 
04:40-09:27 The metrics used to spot them 
09:27-12:34 Where do “boring” companies fit in? 
12:34-17:47 What does AI disruption mean for defensive companies? 
17:47-19:58 Winning traits 
19:58-22:26 The regions most affected 
22:26-26:51 HALO stocks 
26:51-27:06 Outro

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Dave Baxter, senior fund content specialist at interactive investor: Whether you’re a bull or a bear, there’s one topic dominating the conversation right now. That of course is AI, whether you think it’s going to turbocharge market returns, or on the other end of the spectrum, whether you think it’s inflating a nasty market bubble.

What I want to do today is try and look past that and look at the sectors that are overlooked and potentially defensive against this market backdrop, and we’re going to do that from the perspective of an income investor.

So, welcome back to On The Money, I’m Dave Baxter here at ii and our guest today is Nick Clay, manager of the TM Redwheel Glbl Eq Inc R Acc (BMBQMY8) fund.

Nick Clay, manager of Redwheel Global Income Fund: Nick, thanks for joining.

Nick Clay: Thanks for having me.

Dave Baxter: So, let’s kick off discussing some of the sectors that are appealing on that front, and maybe some companies that also stand out.

Nick Clay: You’re right, the whole market is extremely focused on one particular theme, and there is utter confidence that the market has at the moment - or complete certainty, really - already made up our minds about who’s going to win and who’s going to lose. 

So much so that the JP Morgan data that just came out showed that the top 10 stocks in the S&P 500 are now 41% of the S&P 500. If you look back through history, that’s twice as heavy a concentration of the S&P 500 than it’s ever been for the top 10 stocks going back to 1985. So, we’re kind of twice as confident this time around that we know exactly who’s going to win.

The 10 stocks each year, each decade, change a lot because things get disrupted. So, every time we’re certain that we know which the 10 best stocks in the world are, 10 years later we realise that probably wasn’t the case. This time around though, we’re totally convinced we know what the answer is.

Also, what’s different this time is that it’s all based on one theme, not different themes across different companies. What that means is that certainty on the other side of that coin has meant that great swathes of the market are being discounted as boring, the losers of AI, just not interesting enough, not going to make you rich enough.

That’s where we find more interesting opportunities today, and that is based on the belief that AI is obviously genuine, that it’s going to go everywhere. We’re all going to have it, all our companies will adopt it. So, it’s not because of a view that AI is not going to happen.

We’re very comfortable that AI is going to happen. It’s then working out which companies we think are going to best be able to utilise AI, best able to transition through that revolution we’re going to go through, and remain very good-quality businesses on the other side of that, but today, are priced is if that’s never going to happen. 

This strategy has been going 20 years now, and today we are getting stocks dropping into our yield universe that we can now own, which we’ve never been able to touch before for the last 20 years because they’ve never been cheap enough.

Some of those stocks, for example, are Lvmh Moet Hennessy Louis Vuitton SE (EURONEXT:MC) in the luxury sector, as everybody believes that the Chinese consumer is never going to buy a handbag again, so, it’s boring and it’s not exciting. 

Equally, and AI-related, is Accenture  Class A (NYSE:ACN), the consulting company, which has fallen from its peak share price to today around 70% because the market is convinced that Accenture’s business is going to get replaced by AI and it’s just not fit for purpose anymore. Which is interesting because that was the same accusation [aimed] at it when the Cloud came along and the same thing was going to happen. Although the Cloud is now 55% of its business and growing at 10%, so it seems to have transitioned quite nicely into that.

AI is already about $3 billion of revenue and growing, obviously very fast from a low base within the company, and yet, it’s on a price/earnings (PE) of below 10. It’s on a free cash flow yield of 13%, and it’s on a dividend yield of around 5%. It’s been priced to effectively go out of business.

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Dave Baxter: To pick up that point, are those the main metrics you’re using to judge this value? So, free cash flow yield is everything? Price earnings ratio?

Nick Clay: Correct. Free cash flow yield is everything, mainly because cash flow is the thing you can lie least about. Everything else in your profit and loss (P&L), you can kind of slightly make up a little bit depending on how you choose to account for certain things.

Dave Baxter: How would you define that for people who don’t know what it is, briefly?

Nick Clay: Basically, it’s how much cash the business generates, and then when you take off that, what they require to keep the business going. So, maintenance, capex, and anything that just keeps the business functioning and effectively keeps that cash flow able to be generated into the future. 

Then, whatever’s left at the end of that is the free cash flow that the company benefits [from]. That free cash flow that the company then generates, they have some decisions to make with that. They can either reinvest it back into the business to try and grow it even faster. Or they could return it to shareholders, and they can do that by [paying] a dividend, or they can do it by buying back their shares. 

It’s that capital allocation decision, what they choose to do with that cash flow, which is very important because it drives the future cash flow streams from that company going into the future.

Now, what we want to see is that companies pay us a dividend, as well as invest in themselves to maintain the durability of that cash flow. So, our perfect company doesn’t exist, but our perfect company would be a company that’s valued at an 8% free cash flow yield, and it takes 4% of that and invests it back into its business for growth, and it gives us 4% back as a dividend yield that it will grow over time as its cash flow grows.

It’s that durability of a business model that we’re trying to get to the heart of, and if you can get those cheap enough, if you think about what a free cash flow yield means, it’s how much cash it will yield back to you every year.

So, if you’re in double-digit territory like Accenture, it doesn’t take long for you to get your money back. So, the market’s basically trying to say to you that Accenture is a business that’s going to go bust over a period of time. If you do the maths, it’s about seven or eight years that Accenture could go bust. That comes back to this concept at the moment that when markets go up in a straight line and everyone’s getting rich very quickly, no one cares about valuation, no one cares about fundamentals, etc. It is literally, how rich can we be by Monday?

In that environment, you get to a situation where even the greatest companies in the world - and some of the really big technology companies are unbelievable businesses and probably are some of the greatest businesses in the world - at the wrong valuation become the riskiest businesses in the world.

Because all the valuation of a company is, is the expectations placed upon [it] of what [it has] to deliver. So, if your valuations are incredibly high, then what you have to deliver has to be exceptional all the time. That’s difficult to do for any company, however good you are. So, your risk is very high because you’ve only got to stumble a little bit and everybody panics.

Dave Baxter: It’s been interesting to see in emerging market... Now I can’t remember whether it was Samsung Electronics Co Ltd DR (LSE:SMSN) or others, but we’ve seen companies doing record high revenues and still the market is disappointed.

Nick Clay: Because it just wasn’t enough to satisfy the expectations and demand that the investors require. But of course, that works to the flip side as well, which is that if you’ve got a company like Accenture that is priced to go out of business after seven years, well then all it has to do is not go out of business in seven years to do better than what you thought it was going to do.

As an investor, you’re trying to work out which risk/reward you’re willing to take on board, going to Mars or not going bust? It’s not that’s clear, I know, because many businesses probably will go bust in an AI era. It’s not that disruption is not rife, it is rife, and AI is probably going to accelerate that.

So, it’s not an easy decision to make, but it’s which risk/reward are you most likely and most comfortable taking, and it has implications for how you generate your total return going forwards and the pathway of that.

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Dave Baxter: So, we’re talking about overlooked and potentially defensive companies and so on. Are all the names that spring to mind those cases where the market is pricing in an existential crisis and you disagree, or are there any more sedate ones where it’s just because sometimes in those markets what you’ve seen is companies just don’t seem to be sexy enough and therefore they fall between the cracks?

Nick Clay: Correct. I mean, 10% growth used to be pretty good and now people don’t even get out of bed unless it’s 50% growth-type thing. So, you’re right, there are many companies, particularly staples companies like Nestle SA (SIX:NESN), like Nestle SA (SIX:NESN) - which is fizzy drinks and coffee in America - they’re just boring.

They just don’t grow fast enough, they grow GDP in a little bit. And that, quite frankly, is just not exciting enough when you’ve got other companies, which every month can double the size of their revenues. So, in that environment, they just get forgotten about. And again, these are great durable companies, they’ve been around a very long time. 

PepsiCo Inc (NASDAQ:PEP), for example, there’s a great stat that if you bought Pepsi in 1987, today Pepsi returns to you as a dividend every year the share price you paid for Pepsi in 1987. So, if you put a 100 in, in 1987, you’re getting a 100 back every year in dividends from Pepsi, what you paid in the first place for it because it’s grown its dividend throughout that period. 

They are incredible companies, but no one’s interested in them because they’re not exciting. That’s an opportunity because you’re able to invest in these companies on attractive valuations. 

Right now, the market would argue against that and go if it’s not growing fast enough and it’s not transformational in an AI sense, then they’re not as attractively valued as you think they are. And you really want to buy the really hyper-growth companies, and they might look expensive today, but they’re growing so fast that, really, they’re very cheap.

But then again, that just comes back to the point we’re making earlier, which is about expectations and what risk/reward you want to take on board. That might be true, but they better deliver on it, and nothing better go wrong. Otherwise, you’re going to hit a brick wall. Whereas we would rather take the risk in good, durable companies where they don’t have to do much to make us money.

And in an environment which is dominated by greed, we feel having a little bit of fear in our way of thinking about things is appropriate, as would be the case if the market was abundantly fearful, we would then want to start getting greedy.

But right now, it’s the staples, it’s some healthcare companies, it’s some of these areas in software, luxury, where people are just giving up on those businesses, that we think the opportunities lie today.

Dave Baxter: You mentioned software, obviously that’s been a big victim of those existential fears related to AI disruption. How wary and agile do you need to be with this idea of a defensive company? Because what AI is perceived to be doing is suddenly tearing down or destroying those defensive moats almost overnight.

Nick Clay: Correct. Disruption is on the rise. If you went back to the 1960s, the average tenure of a company in the S&P was 60 years. They didn’t really disappear. Today, it’s 18 years.

Disruption is huge, and it’s probably only going to accelerate with the adoption of AI. So, you’re right, the challenge today is to not rely on a business which historically has been durable and good quality and just naturally assume that’s going to be the case going forwards. Because AI is breaking down what was called moats or protection that companies had previously. It’s breaking those down and then they’re not moats anymore. They don’t defend the company anymore.

Companies we’ve owned in the past, like a RELX (LSE:REL), for example, has been under a lot of pressure, and historically, its database of legal and science and tax, etc, has been the massive moat for that business because the cost and the time required to replicate that was basically impossible and so they were well protected. And so could easily transition from paper, where they used to do it before the internet, to online. 

Today, with AI, you can create that database quite quickly, and quite cheaply. So, suddenly, you have to question whether that company has the barriers and the protection it’s historically had. 

You have to start to ask yourself slightly different questions about your companies. The way we phrase it is if they can suffer the transition of AI. We do not assume that all our companies are going to adopt AI and become suddenly super-profitable. No technology in the past has really demonstrated that, only for very specific individual companies.

In the main, technology gets adopted and all it does is just protect the margin that you were running previously, but you had to do it. The internet is a good example of that, and we don’t see AI as being any different. So, companies need to be able to adopt it, so what they require is the time and the opportunity to transition AI into their business for their clients. That’s the key, we believe, of whether a company is going to be able to suffer.

A good example, we think, of that would be Amadeus IT Group SA (XMAD:AMS). Amadeus does software effectively for airline companies. From the moment you book your ticket to the moment you get off the plane at the other airport, it all happens on the Amadeus system and it enables the likes of British Airways, etc, to get a passenger, put them on a plane, take the plane off and land it and get the passenger off at the other end. It’s pretty mission critical, what BA have to do, and because it’s so mission critical, they use one person to do it for them, which is Amadeus.

They don’t use a multitude of providers of systems. So, then the question becomes, can AI replicate what Amadeus do? Most likely it will be able to do that at some point. Is British Airways going to take the risk with its business and say, ‘There’s someone over there with headphones on and a beanie who’s vibe coding something that you can do, Amadeus, and he’ll do it at a fraction of the price. We’re going to risk the whole of our business on him and kick you out’?

We think that’s an unlikely scenario that someone will make that decision. So, we think that the mission-critical nature of something like Amadeus buys them the time to integrate AI into what they do in their software for their clients, and then to deliver it to clients and deliver the efficiencies it will bring to their clients, not charge them more for it. And maybe it will allow them to do more stuff for their clients, and therefore that’s the growth in their business going forwards. 

Whereas other companies, it might well be that they’re not the only provider. And if you’re not the only provider and there’s a whole multitude of people, well that company’s risk of taking on yet one more provider and giving it a go, the vibe-coding AI, why not? It’s not mission critical. And if you can let them in, then suddenly you realize, wow, and, more importantly, at the price it could do it at. So, even if we don’t take you, we’re going back to the other provider and telling them they need to halve the price.

So, the dynamics, that’s what we’re trying to look for in terms of what we say is an ability to suffer.

Dave Baxter: So, I guess it’s less about metrics, because maybe I imagine fund managers are often tempted to look at whatever it is, like market share or something, and it’s more about traits and assessing what a real moat is. I guess there’s a mission-critical point, there’s also been the argument that if you’re a heavily regulated business, again, that might be another kind of protection.

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Nick Clay: Correct. Or if the data with which AI is going to work is yours, rather than publicly available. For example, a lot of data in the insurance industry belongs to the insurance companies, and so they have a competitive advantage with regards to if they’ve got the most data, maybe they can get the better answers from applying AI to that data, to therefore be able to price.

If you think about motor insurance, the insurance companies will tell you that it’s quite technical and they’re very good at subdividing the risk categories, etc. But, in reality, it’s teenagers, people who are not teenagers, and old people. It’s pretty basic the way it’s split up.

Well, technically, it could get down to the individual with AI down the road, which would mean their ability to price the risk properly in regards to claims, etc, goes through the roof and it should be able to make their profitability more sustainable, less cyclical, etc. And if the data is all theirs, because they dominate the industry and therefore they’ve collected the most amount of data over the years, then they might be able to do that even better than their competitor. 

It’s those kind of things that we think are going to be key when we go through, which is starting now, the adoption phase of AI as it comes into businesses, and understanding who can do it, who would therefore retain their business at the end of it, dealing with their same clients, and therefore they would be the ones who can suffer this. A lot of those companies today are priced as if they can’t do it, they’re not going to suffer and they’re going to get disrupted by it.

Dave Baxter: Yeah. It’s a basic question, but is there any regional element, like, are there geographies where you’re finding more of this opportunity than elsewhere?

Nick Clay: No, it’s not as clear-cut as that. Concentration in the market of AI has kind of infiltrated everywhere. It’s even worse in emerging markets than it is in the US, for example. 

I saw some [stats recently showing that] if you took the performance of Samsung, SK hynix Inc ADR (NASDAQ:SKHY) and Taiwan Semiconductor Manufacturing Co Ltd ADR (NYSE:TSM) out of the emerging market benchmarks, they’re basically flat this year rather than not. So, it’s more about what’s been left behind in various markets for whatever reason it might be.

And it’s not always AI-related, so the Chinese consumer has been very lacking in confidence since Covid, quite frankly. So, anything exposed to that is seen as that’s gone, they’re never coming back, the Chinese will never spend any money again because they’re in financial ruin.

But all the data will show you that they’re not in financial ruin, it is just a confidence thing, and there is evidence to show you that when they get the opportunity to spend, invariably when the yen is weak, everybody travels to Japan, buys stuff in Japan, and sales of certain things in Japan go through the roof.

You can see that the appetite to spend is still there, it’s just a confidence thing. Well, are the Chinese consumers going to remain lacking in confidence forever? Unlikely. But that’s what some of the luxury good stocks, for example, are pricing.

Kering SA (EURONEXT:KER) and Gucci has been priced as if Gucci will never turn around again. We still think we can find evidence to say Gucci is still a relevant brand in the luxuries market. And things like luxury, it is not something that can be disrupted by AI in the sense that I don’t think AI is going to create a new luxury brand which is going to overtake LVMH or Hermes International SA (EURONEXT:RMS) or whoever it might be.

Tangentially, it’s almost a play on the positivity of it because it’s creating wealth for the upper part of society. They’re just getting wealthier and wealthier and wealthier, and the thing they buy is luxury, and luxury’s priced as if it won’t grow again. Things like that we find quite interesting at the moment.

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Dave Baxter: How do you feel then about the so-called HALO concept? High asset, low obsolescence.

Nick Clay: When you’re trying to think about investing, you shouldn’t invest for certainty because invariably the future isn’t certain. So, you’ve got to think of the range of outcomes that you face, and HALO is about one outcome. 

But there are other outcomes that we could easily face, which are separated from AI. The view of AI utopia is that it conquers all and it can save us from everything. But just say, maybe it can’t. What if we had an inflationary backdrop? Or what if we had a recessionary backdrop? These are things that used to happen in our past. And thinking about the range of outcomes we face and about what company characteristics serve us best in that range of outcomes.

We’ve talked about suffering in an AI world, but do they have pricing power to be able to suffer in an inflationary world? Or do they have more stable defensive business characteristics to suffer in a recessionary world? Then, if you can get into those kinds of businesses that are priced better for the range of outcomes we might face, rather than ‘we’re just convinced that one outcome is going to happen and we’re just going to invest for that’, we think that is a more prudent way to try and manage our clients’ money. 

Now, it means that we will deliver our total return in a different fashion to someone who’s all about ‘I’m going to make more money on the way up in one trade’. That’s all about upside capture. Whereas we want to make our money from the other part of your total return, so your capital goes up, you have the compounding of your dividends, and those two things make up your total return.

The heart of what we’re doing is trying to compound that dividend and so it makes up roughly about 50% of the total return over the long term, did for the first 15 years, for example. That gives you a certain characteristic which we think better suits that range of outcomes because my companies only ever pay me dividends, unless I’m an idiot and I keep investing in companies that will cut their dividends to zero, and then I will get fired. So, my companies are going to keep giving me a dividend, and every year I receive a dividend, so it just goes up every year because I keep receiving more and more and more and more. And then I can compound it.

That is very un-volatile, especially compared to share prices that go up and down like a yo-yo. So, if you can get 50% or so of your total return driven by the compounding of the income, well your overall total return is going to be less volatile than that of just capital alone. 

Now when things go up in a straight line to Mars, no one cares about that. It’s all about greed and it’s nothing about volatility. But if things become more volatile because whatever happens, AI disappoints, inflation, recession, whatever it might be, then suddenly you have to think differently and downside capture becomes ‘I don’t lose as much money when things go down’. Mathematically, that’s what matters. And focusing on companies which are durable in their cash flows and therefore can continue providing you with a dividend stream, then that gives you some downside protection. And that’s what gets your downside capture number low enough, and that’s what can help you in more volatile times. 

We think, given where we are today in markets, which are close to all-time highs, record valuations, and complete certainty, having something within your portfolio of funds that you might invest in that thinks differently and does things differently and generates a return in different functions, is quite appropriate for this kind of environment we’re in today and where we are today.

Dave Baxter: Well, thank you for your time.

Nick Clay: Thank you very much. Thanks for having me.

Dave Baxter: And thank you for watching and listening. Do let us know what you think in the comments and you can, of course, contact us directly at otm@ii.co.uk. Thanks again, and take care.