Dean Curnutt: My guest today on the Alpha Exchange is Andrew Lapthorne. He is the global head of quantitative research at SocGen and a gentleman that was on this podcast about five years ago. Andrew, welcome back.

Andrew Lapthorne: Five years. Wow, that flew by. Yeah, thanks for having me back on. Yeah.

Excited to have the conversation. November 2021 and I just checked in, the market cap of Nvidia at that time was $657 billion. So a little bit has changed for Nvidia, but it’s not alone in just how much market cap these tech heavy, AI centric stocks have added. And I think that’s going to be really the basis of our conversation and some of your recent work. So let’s get the conversation started and let’s just, just start with this word bubble. It’s a kind of a loaded term and I feel like people talk past each other quite a bit. One of the early slides that you present in your deck is just this, the notion of financial euphoria, a Minsky type cycle. You cite Kindleberger and the sort of stages of euphoria. Why don’t you start there and just talk to us about what you see when you observe in S and P where the top 10 stocks are 40% of the index and they’ve just delivered such massive returns for investors.

Dean Curnutt: Yeah, I mean the word bubble, it’s difficult to define and obviously everyone kind of sees excesses and then basically normally then finds excuses for those excesses to continue. And the stages of Kindleberger where you kind of get euphoria and then basically all the bears give up and everyone has to participate. But the other point I make about bubbles is alongside bubbles you need kind of speculation, you need leverage, you need people participating because their neighbors participating. I think it was, was it JP Morgan who said it’s really painful to watch your neighbor making lots of money while you’re not. And then all the associated things with it, which is people, people wanting to participate in crypto, retail speculation, the explosion of options, et cetera. But ultimately I think for me it just comes down to the expense of things, the price that people are willing to pay for things relative to history. And, and that is very measurable and that tends to be very mean reverting. And obviously there’s a fallacy of composition there as well, where if you add up all the expectations embedded in valuations, then you can’t get the nominal GDP growth to drive those expectations.

Obviously the difficulty then becomes how do you navigate that bubble? And I think this is what’s unique about the current situation because the market cap of MSCI World S&P 500 is so tied in to the story that we’re all participating, whether you like it or not. So it’s not like 25 years ago where you could buy a bunch of value stocks in the S&P 500 and for a while ignore the Nasdaq implosion. At the moment, everybody, the market cap is all based around these ideas. Actually, November 2021’s kind of interesting as well because it was the start of an almighty value rally. And actually that value rally has probably made you more than the Nasdaq, but no one’s noticed because it’s such a small proportion of the US equity market. Yeah.

Andrew Lapthorne: And so this index, it ain’t your father’s index as they say. Right. It bears no resemblance to really much we’ve seen before. I mean, you go back, let’s say 20 years, we’re in the pre crisis leverage buildup, one that ended awfully but was really a period of time as the housing bubble inflated that really brought with it very low volatility. The VIX was low, credit spreads were ultra low, and the top stocks in the index were pretty diversified. It was JP Morgan and Citigroup and Exxon and Pfizer. And if you add up those top 10 stocks, I mean, you might have gotten to 20% or something like that. But those risks were very contingent on the amount of leverage in the system. And what people will argue now, and I’d love for you to take this up, is that while we do have potentially very extended valuations, the types of leverage dynamics that proved to be fatal for the financial system into 2008 are not as obvious or as present. And I’d just love for you to reflect on how you think about the overall risks in the context of the system now versus let’s say that pre crisis period there is not a lot.

Dean Curnutt: Of leverage in the corporate quoted sector for one. In fact, ironically, the amount of cash that a lot of these businesses own, 2 trillion of cash, when you then took interest rates from 0 to 5, they’re all of a sudden making 100 billion of interest on their cash pile, which is roughly the increase in capex that you saw. So bizarrely, higher interest rates causes a surge in cash flows for these companies, which allows them to build out their capex, which is something that I think traditional economics probably wouldn’t have modeled. There is a big story in terms of cash flows coming back to investors, which I guess is problematic. So I don’t think within the equity market there’s a kind of leverage build out. I don’t think the corporate sector’s particularly leveraged, particularly outside of the U.S.

Andrew Lapthorne: But.

Dean Curnutt: I think there’s other things in play. Such as, for example, a lot of the story is going on outside of the equity market. We talk about the AI bubble and we talk about excess valuations, but a lot of that is happening in the non quoted part of the market and that’s very difficult to get a handle on. Obviously we’re seeing an enormous amount of money being plowed into AI centers and data centers. We’re seeing a lot of pension and insurance company participation in providing that type of capital. So I think we’re at that kind of stage where you’re adding leverage to the story, which is something that we didn’t have at all connected to this sector, which is particularly cash flow rich, fairly, not particularly capital intensive and so on. I always kind of draw the analogy with Coca Cola and Coca Cola bottling. So Coca Cola makes syrup and it sells the syrup to a more capital intensive bottling company, which then makes far lower margins than obviously Coca Cola selling the syrup. The nature of these businesses is changing, which I think is fascinating. They’re having to raise an awful lot of capital.

They’re having to borrow and they’re having to build out basically infrastructure which they haven’t had to do. You could probably actually draw the analogy. I know a lot of people draw the analogy to the telecom sector 25 years ago. But mobile companies effectively were given a free lunch by being given mobile licenses. They then had to respond to, to the massive demand as everybody started having mobile phones. They then had to build out their capacity. And as they were building out capacity, governments wanted to participate in it. So they started charging. You had 3G license bidding war, which was extremely expensive. And then obviously for the next few years you saw massive rolling out of infrastructure, telecom infrastructure to support both mobile and the Internet. But they weren’t the key beneficiaries of providing that infrastructure. It was companies which would follow on the Netflix of the world who would kind of benefit from that rollout. So maybe we’re at that stage of kind of, oh, we’ve discovered something new and there’s going to be a huge amount of build out of capacity. But actually the return on that investment is going to disappoint versus people expectations.

@ the end of the day, if you’re building a, an AI center, I guess it’s no different from building an office block. You borrow some money, you build it Then you populate it with clients and those type of investments tend to be kind of my cost of capital plus a margin, not massive ROE type.

Andrew Lapthorne: Returns. We’re going to talk about some of the work you’ve done on comparing the profits characteristics and valuation characteristics of today’s market specifically and some of the high flying components of it, and set that against the telecom investment boom and bust cycle. Before we do that, I can’t help but want to reflect on what you just offered on the interest rate hiking cycle almost being a benefit to these very, very cash rich companies. I mean, this won’t be our main topic of conversation, but it’s so interesting. When we started hiking in 2022 and took that policy rate up 4.5%, maybe even 5%, Warren Buffett got a lot richer, right? He’s holding $300 billion worth of t bills. And I just kept asking myself, are we tightening or not? It’s an interesting question. And if these companies like Google and Nvidia have so much free cash sitting around and suddenly it’s yielding 5%, you’re putting money in their pocket that they can then spend. It’s a really interesting differential of, let’s say the monetary policy cycle back in 2005 and 6, that tightening cycle, which really did have an impact on slowing the economy and borrowing.

I think it’s a fascinating kind of thing to think.

Dean Curnutt: About. Well, I think if you look at the 5 year or the 10 year average of the interest rate, yeah, it’s reasonably stable because you have up cycles and down cycles. So I think one of the things that a lot of people are missing, particularly when it comes to cross sectional stock returns, is that we are in a post bubble period already. But that bubble was zero interest rates and qe. If you set interest rates at zero and yields at very low for a long extended period, people forget that if you put money in the bank and stick up interest rates, you start making cash flows from it. And we were writing about it at the time because you can make estimates where the amounts of money flowing back to global investors, which ballpark was about 2 1/2 trillion dollars a year in terms of coupon, dividends, buybacks, et cetera, because you accelerated your interest rate, you were adding about an extra 2 trillion to cash flows coming back to investors. And obviously the flip side of governments having to spend an awful lot of money on their interest charges, those interest charges are somebody else’s returns.

And if you then spent 12 years or whatever anticipating your retirement, you’re over saving and there’s evidence that you’re over saving and all of a sudden you’re sitting on the beach and all of a sudden you notice that your bank account suddenly delivering you cash flows that you didn’t have before. And we’ve seen that. We’ve seen that in terms of wealthy people spending, we’ve seen that wealthy people now make up a huge amount of consumption where previously they didn’t. You’re seeing service inflation based around things like tourism, restaurants. Obviously Covid was related to that. But the rich have got a lot richer because they had lots of assets which are suddenly yielding an awful lot. And actually part of the credit story is some of the most popular ETF products or credit products are basically people thinking, well Look, I’ve got a 5, 6, 7% yield here. If they’re talking about interest rates going to zero again or just going down again, I want to lock in that yield because I’ve just lived through a decade of not having any yield. So you’re seeing an awful lot of asset managers selling credit related funds more than they’re actually selling equity related funds.

So I think it’s just having that period where you had no interest rate and then setting it to 5. People are still getting used to it. I would add that in terms of the behavior of markets, last year the bond market started to become a lot less volatile. It seems to be settling around a kind of four handle in terms of the 10 year. And the type of performance that you would see with higher interest rates and a steep yield curve is kind of what you saw. So you’ve been going through this kind of five year process of normalizing markets back to a higher interest rate regime or a more normal interest rate regime. But the big difference between say the US and everywhere else is obviously this AI story came along at the point where actually most growth stocks have been poorly.

Andrew Lapthorne: Performing. Let’s take up some of your charts because I think they do a great job of setting the stage and allowing us to, from a data driven standpoint, explore this concept of bubble. And let me give you my own version of it. I think we all are in markets. We care about the economy, we care about the Fed because we care about.

Dean Curnutt: Markets.

Andrew Lapthorne: Right? We’re interested in making profits on a strong risk adjusted return basis, avoiding big drawdowns. It’s asset prices that we care about. And so for me, the term bubble to me has got to invoke some concept of vulnerability. I think that’s really what we’re asking ourselves. Are prices well ahead of fundamentals or will there be a reckoning of some kind? You know, can we learn from the past based on other experiences where prices just rocketed higher? Did they ultimately sustain themselves or did they revert? You know, was there a vulnerability? I think that’s to me the operative question. So do you want to just load up one or two of the charts here? I mean, I thought a couple of the early ones on the distribution across different pension forward pes was a good.

Dean Curnutt: One. Yeah. The simple thing is, as you say, we’re picking stocks and we want to work out whether we could find stocks which are cheaper than average, ideally. And one of the ways I do that and also one of the ways I get around the kind of concentration risk which creates a market cap weighted PE which is overly influenced by a few companies, is that you just simply count the percentage of stocks which are sitting in a particular PE bucket. And if you take the number of stocks on the left hand side and then you look at where, you know the average over the last 27 years and then you look at where we are compared to where we were in what was a recognized bubble period, 99 to 2000, the average stock is more expensive in the S and P. Well, in the, in msci. Now you could argue that most of the action was in the Nasdaq back in 1999 and less so in, in the main benchmarks. But you can see that there’s more black bars off to the right hand side today than there were in 99, 2000. The other thing, and I think this is a big difference between where we stand today and where we stood 25 years ago.

25 years ago, stock pickers, so asset managers buying and selling stocks were a massive influence on individual daily stock movements. That’s where you had the majority of decision making about what stocks are good and bad. You obviously had retail participation in buying those stocks as well. But because the passive battle has been won, essentially you’ve got wholesale buying and selling of the S&P 500. Because again, if you want to have exposure to these very big companies, they’re such a big part of the index, it’s the cheapest way to do it is just to buy the S&P 500. But. But that means that all stocks in the S&P 500 re rate as a consequence of that passive buying. So you could see, unlike 99 2000, there isn’t a cohort of cheap stocks on the left hand side. So there was somewhere to rotate to 25 years ago. And funnily enough, it was things like mining material stocks, stocks which are doing quite well recently, but there’s no cohort of cheapness. Now if you then look at the distribution of market cap, actually today is as extreme as it was in 1999. So this concentration of market cap in very expensive stocks, we’re in a similar position.

So I think it’s fair to say from these charts, are we in a valuation bubble? Well, if we expose, recognize the TMT bubble was a bubble, then the answer to that question is yes. The other pushback that I’ll then have is yeah, businesses are far more profitable than they were US businesses. Take that up. So again, you could do this simple analysis of saying, okay, let’s look at the distribution. I’m using MSCI World here as a comparison, but I’ll come back to US Stocks specifically. Again, I’m just showing MSCI World’s distribution of valuations and then I’m just looking at the distribution of return of invested capital. So, and again, I can’t see on the right hand side chart any material difference in the historical profitability of MSCI World constituents to where we are today. Now, this is all at the stock level. Now when we start getting into aggregates and adding in these exceptional businesses with their high profitability, that is going to then impact the aggregate. But that does not mean that the average stock is doing well. It just means that there’s some isolated companies which are doing particularly.

Andrew Lapthorne: Well. If we go back, and I’m just using my own recollection here of the original Internet boom, 99, 2000, you had Cisco, you had Qualcomm, a bunch of other high flyers, but those were massive PE ratios, certainly profitable, but the amount that the market was assigning to the growth prospect aspect of it was enormous. And so these charts I think are less consistent with at least how people remember it. And certainly what you’re saying here, the statement you’re making, are stocks more expensive because they’re more profitable? No, that’s a narrative that is not consistent with what we hear. Right. And I’m curious, I’m sure you’re hearing people say, well, these companies are printing money and the valuations for these high flyers are not as extreme as they were for again, Cisco and Qualcomm and so forth. What do you hear most? And what are you. You’re refuting it here, but I’d love for you just to explore it more in terms of the common narratives that we’re exposed to in the financial.

Dean Curnutt: Media. Yeah, I’m going to go ahead to another chart which I think is useful in this context, which is this one. So these companies are very, very big. They’re also making a lot of money and as such a thing, which is I get pushed back on all the time, is look, the market cap’s gone up versus everybody else but so has their profits. That’s absolutely fair. But that does not mean that you don’t have to be concerned about it because essentially 30%, 1/3 of your profits is coming from 10 stocks in the S&P 500. That means if any of them suddenly have a change of direction, you know, suddenly they have a competitor they didn’t see or suddenly someone produces a chip which is far cheaper than the current chip provider, then all of a sudden not only do you have your market cap at risk, your price of the index at risk, but the profits are at risk as well. So you could take it both ways. You could say this is absolutely fantastic. They’re big companies, they’re generating pretty much most of the profit growth in the S&P 500. They’re also now impacting GDP, US GDP because of their build out data centers and also they’re dominating the capex story.

So that’s all great but for me it lacks diversification. I would like to have, you know, other things I could be invested in, other ideas I could be invested in and this is just like it looks increasingly like a one way street on one particular topic and that, that’s where I get the concern. So, so a huge topic is the story of, you know, diversification. I have a chart on tracking.

Andrew Lapthorne: Error. Yeah, I love that one. Which I’ll show.

Dean Curnutt: You. Active risk. Active risk is tracking error versus the benchmark. Now what we do on the left hand side here is we just calculate a market cap weighted version of the S&P 500 which systematically excludes the top 10 stocks. And we do the same for MSCI World and then we’re just measuring the tracking error of that kind of MSCI World x those top 10 stocks versus the original benchmark. Now you’ll meet a lot of people, a lot of institutions who have active risk budgets of somewhere around 2%. But that was perfectly fine in the era before 2019. But now your active risk budget is entirely consumed by these stocks. And if these stocks are particularly big and then volatile like we saw last year, then that’s going to increase your need to hold that particular company simply for tracking error purposes. So it’s one of the kind of most disappointing things I hear which is, look, I think That’s a really great idea. And I hear that you’re worried about the valuations on these stocks, but I really need to own these stocks because that’s in my mandate and to state the obvious that these stocks at some point then get into trouble.

So I’m just recording on the right hand side the performance of the top 10 stocks relative to the rest of the stocks. And yes, you could have an extended period where they’re doing very well, but mean reversion does tend to happen eventually. And then you sit there and go okay, why? What’s the problem with owning the top 10 stocks? And they’re really expensive. So we talk about the fact that 25 years ago these businesses didn’t have the profits. Well now they do have the profits and they’re still trading at 25 to 30 times. So that leaves them susceptible to profit disappointment or indeed positive profit surprise. But you’re also carrying valuation risk long term. And the longer you carry valuation risk long term, the more you’re at risk of basically generating a poor return at some.

Andrew Lapthorne: Point. So the profit margins question, we’ll explore that. I also want to talk again about your chart on tracking error the MSCI one. I mean as I ballparked it, you’re basically 5x from the post GFC period 2011, 1213. That’s an incredible increase in tracking error. We talk about FOMO in the market. Fear of missing out. One of my little sayings is it’s more for fund managers is Romo risk of missing out. The risk of underperformance is a death knell for a fund manager who is paid on assets under management. You’re long the call option on your asset base. That’s really the incentive structure. And so to deviate from the benchmark and the S and P is a formidable benchmark. It’s realizing a sharpe ratio of kind of one and a half the last three years. It’s a crazy result. And it’s so concentrated with these high flying highly valued stocks, all of which are pursuing the same AI riches. And yet and this is wanted you to sort of take this up. It’s incredible how uncorrelated they are. They’re in the same space. But if you run the realized correlation of stocks in the S and P, we’re at levels we’ve never seen before.

So you have an index that’s undiversified in how concentrated it is, but somehow some way it’s achieving diversification because you look at the correlation matrix of the high flyers, it’s remarkable how idiosyncratic these moves are. And that to me is another kind of risk hiding in plain sight, not realized yet. But that to me is almost part of the problem. It’s dampening realized volume at the S and P level because the stocks are behaving in such an idiosyncratic fashion. I’m curious if you’ve any thoughts on that or if you’ve looked at.

Dean Curnutt: That. Actually funny enough, my son, I think he did his dissertation on idiosyncratic risk in the S and P and actually the maths showed actually there wasn’t a lot of idiosyncratic risk. Bizarrely because if you from a mathematical standpoint but forward looking, you’d imagine that’s what you’ve really got. Because these big companies need to participate in AI because if they don’t, they don’t have a business thereafter. So there will be winners and losers amongst them and maybe it’ll be a function of who’s got the most money to spend and who’s got the most cash flows to allow them to spend it. But yeah, there is going to be differentiation in what they achieve. And actually it’s really interesting, we talk about AI bubbles, et cetera, but when you then look at the performance of those stocks last year, well a lot of them didn’t even go up. So it’s very hard to argue that you’ve got a stock bubble in these names when their prices aren’t going up. And instead you’ve got a rally in value stocks and so forth. You mentioned it. The mighty s and P500. If you think about it, if you were to create a long short portfolio, that is relative performance, why would you put the very best stocks in the world in your short leg?

I mean that’s what relative performance is. And actually I have a chart later in the pack which shows that out of the 9,000 stocks that we track globally 25 years ago, about 50 to 60, 60% of them used to outperform the MSCI World or Benchmark or the S&P 500. Today that’s 30%. You’re picking the wrong fight by trying to outperform the benchmark. And the demand for benchmark product far exceeds the demand for stock picking product. We use the S and P in terms of an asset allocation tool. In terms of vix, a hedging tool, the demand for S and P index product far exceeds. So therefore to then expect that the stocks in your portfolio are going to outperform something which has got way more demand then I think is Foolhardy. So obviously that leans into kind of systematic quants. And systematic quants have been doing very well. Longshore equity has been doing very well. And we note that even in a year when MSCI world goes up, 40% of our universe of stocks goes down. But it’s very, very hard for people to do. Their mandate is a relative benchmark.

Andrew Lapthorne: Performance. So a couple areas of follow up. One is we’re exploring this concept of vulnerability. You’re pointing to some, I think, compelling charts that illustrate that these stocks that are such a big weight in global indices in the S and P are so richly valued that they’re. History tells us that there could be a reckoning. There’s a chart in your deck as well that looks at. And I’ve seen this from others, it’s a scatter of the forward PE as an entry point and then the kind of realized 10 year ex post return. Right. Which to me is. It’s a pleasing thing to look at. Right. Because it tells us that the starting point matters. So I guess my first question is just how do you see this playing out? So the S and p is realizing 22% a year the last couple years. So it’s hard to get away from. Where do you see this.

Dean Curnutt: Going? I sit next to Albert Edwards, who’s quite a renowned bear. And we had a kind of bear conference in London yesterday together with Grant Williams. And you know, when you think about what normally causes bubbles to pop is putting up interest rates or fiscal retrenchment and the opposite’s happening. You’ve got expectations of interest rate cuts. You’ve got kind of fiscal imprudence from governments all over the place. You then have to think about where there might be a liquidity shock or a liquidity problem somewhere down the line. And then you kind of, it’s like all eyes on Japan because Japan has been feeding the world money because it hasn’t been able to generate interest rates at home. So if you’ve got interest rates going up and if you’ve got long bond yields going up in Japan, then that kind of argues that you might get less money flowing out of Japan and maybe flowing back into Japan got major concerns around deficits and the cost of debt. So maybe it comes from volatility reemerging in the long end of the interest rate curve where effectively, and it’s something that Albert was pointing out yesterday, where effectively the yield curves just start steepening too rapidly.

So you’re cutting interest rates, but as you’re cutting interest rates, the long end is going up because it’s worried about your deficits, it’s worried about inflation. So if we get a Fed which is highly pressurized to cut rates irrespective of what’s going on with inflation, then that could cause volatility in bond markets. And we saw what happened in 2022. When that happens, you start to get the 6040 portfolio coming under pressure, but that remains to be seen. Short term, it’s going to take some time for that to appear. I think the other side is, as you mentioned, you’ve made 20% per annum for the last three years, so you might want to bank those returns. You become incredibly wealthy and you might suddenly think, look, I’m going to get out because I want to lock in these returns. A lot of investors are sitting on an awful lot of house money, so maybe their tolerance for downside is quite strong. But I think that’s what I’d be worried about. I’d be worried about inflation not allowing the Fed to, to do what it wants to do. The other point is I think the general economy could just become weaker.

For all the talk about bubbles and valuations, one of the most compelling charts is simply the year on year change in MSCI World and the year and year change in MSCI World. Profits. If profits growth is accelerating, MSCI World tends to trend up. And if profits growth is decelerating, it tends to trend down. Obviously it could go in excess of that, but it’s almost on a one for one basis. There’s a chart in the pack which shows.

Andrew Lapthorne: That. See if we can find that.

Dean Curnutt: One. Forecast profits and you’re most of the way there. So the profit story really matters. Now, Europe had no profit growth last year. It was one of the best performing stock markets. So it was all based on valuation change. So you went from really cheap markets to, to expensive markets. The US entirely went up based on its profit projection. PE multiples stayed roughly where they were and then Japan was somewhere in the middle. Half of it was valuation change and half of it was profit growth. You could see that during 23, 24, actually MSCI World was moving ahead of profit growth, but the direction ultimately moves in tandem. So if we start to see a disappointing profit story, then that will impact the direction of markets. And then I kind of wanted to make a point about, I suppose, what looks like the most bullish chart in the world, which is this idea that you get double digit profit growth, which is again the forecast for this year from bottom up consensus. At the same time getting interest rate cuts but it’s really important to think about the relationship between, you know, how come we only get interest rate cuts when you get profit growth decline, you’ve not seen the type of interest rate cuts that we’ve been getting and are expected without seeing a double digit profit decline.

And the relationship is between interest rates, inflation and sales growth. So what happens is inflation accelerates. So inflation accelerated up to 8%. Your sales growth is now running about 16%. Inflation is companies putting up the prices of things. Your margins then expand rapidly because your cost base is not going up quite as quickly. So your cost of your building wages haven’t started to go up. Now what the Fed then does is it pushes up interest rates to slow down inflation. So as you decelerate inflation back down to target of 2%, sales growth collapses to around 0 to 4%. But then you get the lagged impact of your cost base going up. So your cost of, you know, your SSDA costs, etc. Start going, going up and then you get a margin collapse because you’ve essentially decelerated sales growth while you’re getting lagged inflation coming through on your cost base. And then they cut interest rates because one, they defeated inflation and two, the profit growth story is weak. So therefore you’re kind of left thinking, well, that’s not happening until you suddenly see charts like the one here, which I think is absolutely fascinating. So what I’m doing here is I’m trying to get away from the concentration of profits in certain companies and I’m just counting the number of companies which are increasing sales year on year, increasing their profits year on year, and increasing their margins year on year and throughout history.

I could take this chart even further back. It’s always pretty much been the case that as more and more companies increase their sales, they also increase their margins and they also increase their profits. But at the moment you’ve got more and more companies increasing sales and then you’ve got the majority of S&P 500 companies actually not seeing margins go up. And you’ll hear things like, oh, we’ve got peak profit margins, all this kind of stuff. For me, that’s fundamentally a question of why is that happening. And on the one hand you’ve got phenomenally strong nominal gdp, so sales is pretty robust. And at the same time you’ve got people worrying about the jobs market, which is possibly the red line on this chart. So it’s another K in the long list of.

Andrew Lapthorne: K’s. Yeah, I mean, this is quite a disconnect just looking at the Chart historically you just don’t see anything like it. And it is a perfect K. What would you say that is allowing companies to increase sales to this extent? I mean you’re at 80% are increasing sales and yet income and margins especially are.

Dean Curnutt: Falling. So it could be the fact that people have just accepted inflation. So if you’ve got inflation, if you’ve gone through an inflation period and you’ve got volatility of prices, all of a sudden companies are able to increase the prices and things. So it kind of lends itself to the idea that you’ve got something which is pushing up inflation. Tariffs could be part of this as well. This could be some impact of tariffs and it could be demand, it could be improving demand. So the sales growth story could be wrapped in all kinds of things. But say for example, your costs are going and you think okay, I could pass that along in sales growth but I can’t pass it along fully because I’m going to, I’m going to lose clients. Then you start absorbing some of your price increases in your kind of margin. The cost of things, rent, all these types of things, the cost of your building, a lot of it is coming through SGA costs which are running around 5 to 6% increasing whilst at the same time you’re not quite seeing companies deliver 5 to 6% sales growth. I don’t think you could put one thing on the reason.

But as this year develops, I think looking at profit margins and how they of individual companies will be really interesting. And again to go back a couple of charts, if we look at the evolution of the consensus last year, it looks really robust. You see big improvement in forward expectations of the NASDAQ, a sensible improvement in S&P 500 expectations. Remember ring that people always forecast kind of profit growth but then when you remove NASDAQ from that, basically you see a kind of big impact of what happened in April and profits were downgraded by 5 or 6%. So we’re keeping an eye on the average company and how it’s doing as a measure of what the Fed might do and the broader kind of economic strength in the.

Andrew Lapthorne: Us. So you’re pointing to some version of the S&P493. I think you might even have some charts on the relatively lackluster profit growth that is experienced outside of the high flyers. I’m wondering if you or colleagues have have looked as well at the capex centric nature of the economy itself. Jason Furman, very well respected guy, has done some work pointing to can’t Remember his exact timeframe, but it was some part of 2025. You exclude all of the AI CapEx and boy, you get something very different at the investment side of the GDP account that the investment is just all AI centric capex. And so one of the, I think things of the way to look at this perhaps is that the market.

Dean Curnutt: The.

Andrew Lapthorne: Economy is too beholden to all of this AI CapEx, that if you get some pullback, economic growth suddenly looks a lot worse. And that again, that’s a vulnerability that perhaps we’re just not necessarily seeing.

Dean Curnutt: Properly. I mean, capex is normally a function of the operating profitability of a firm. So if your profit growth is around 3 to 4%, your capex tends to be around 3 to 4% and they kind of ebb and flow together. So you’re exactly right. The CapEx growth outside of just six or seven companies is around 3 to 4% and that’s actually what their prevailing profit growth was. The other thing is if you look at free cash flow, so if you take the big, big few companies who are doing all the spending and if you look at the free cash flow, so how much after paying out dividends, capex buybacks do the rest of the world have? So this is MSCI World, excluding just six or seven companies, it’s $50 billion. That’s it, that’s the spare capacity. So inevitably, if people want to spend more, they’re going to have to borrow more to do that. What you’re also seeing is actually a deterioration in distributions to shareholders because actually a lot of these big companies, they don’t pay dividends and actually one in particular just issues about 2% of its capital per annum, that is share counts going up in a straight line.

So the more that you’re taking cash flow and having to deploy it to build out AI, then that’s less cash flow available to shareholders at a point where you’ve got record low dividend yields. And it’s a big topic of conversation for asset owners who have liabilities, pensioners to pay, where am I going to get the cash flow to pay them? And that concerns me because there’s no big pot of money sitting around doing nothing, waiting to spend money on AI. There is with these big tech companies, but they weren’t paying much in terms of dividends anyway. The shareholder return is going to therefore be fully encapsulated in price. So much for.

Andrew Lapthorne: Compounding. So big picture, the S and P is an incredible benchmark. It’s market cap weighted, so it’s become Very top heavy as these things have just outperformed by so much. But there are vulnerabilities. We’ve probably pulled forward a lot of the good stuff. That’s just how markets operate. So how does an investor think about staying engaged in markets but being risk aware? You mentioned it before. Diversification. What are the sources of diversification that you see that really should be incorporated into the portfolio construction process right.

Dean Curnutt: Now? And we’ve actually done a lot of work last year in terms of measuring diversification. I’ve got a colleague called Brian Fleming who joined us last year who’s actually put a number on diversification. So for example, we can now measure if you were to add a strategy or an asset, how it improves diversification. But actually the kind of traditional 6040 portfolio only has about 2.6, 2.7 ideas in it. So your degrees of diversification are very, very limited. So we’re forever trying to think about how we could add ideas to the 6040 mix and it really then becomes on the capacity of the investor to be able to participate in those. So I don’t really want to have a situation where I’m betting against the S&P 500, but I do want to have the ability to buy and sell stocks and generate alpha from selling stocks. So Quant, systematic Quant had a brilliant year last year. Global long short models in the classic value momentum, quality mold all did very, very well. In fact, they did particularly well during the kind of difficult April because of their focus on individual stock factors and individual stock returns.

And that’s actually as well. That’s been going on for some time now. It’s just that people have only really started noticing in the last couple of years. Kind of annoying that if you went and just selected the cheapest companies in the world based on their PE, there was four or five companies, countries like Korea where the forward PE was less than 8. And all of those countries kind of did 60, 70, 80% returns in US dollars last year. So I’m a bit kicking myself at why I had a kind of nice value strategy running along in Europe which did very well at the stock level. I forgot to notice there are some countries out there on very, very low single digit P es. Take a look at the Spanish stock market. It’s been quite incredible for the last few years simply because it’s full of kind of cheap financials which have been busy re rating. So I think one of the kind of sad tales about concentration risk is the fact that people are missing really interesting opportunities elsewhere. There is A chart in the pack, which I think kind of sets the scene right at the beginning.

So I’ll just move to it. You’ll hear a lot of people talking about lots of four complicated charts here. But the difficulty quality stocks are having or low volatility stocks, and most of people are forgetting, the reason why these things are are struggling is because they had a fantastic decade where they re rated on the back of low bond yields. So what these two charts at the top are showing is just if you were to just build two portfolios of quintiles, one where the red line are stocks that like falling bond yields, so are positively correlated to bonds. And then you’ve got the black line which prefers rising bond yields. So they’re typically things like cyclical assets and financials, while the red line is typically things like consumer staples, more defensive assets plus growth stocks. You could see that from before QE came along, the bond yield had no impact on the cross sectional valuations of stocks. But during QE Qez because you had cyclical problems, people were just forced out of the bond market into the equity market and they favored buying high quality growth stocks almost at any price. So then you walked into 2021, 2022 with these stocks trading way beyond their normal levels and the cohort of cyclicals trading on single digit P es.

And actually if you look at the performance of those two portfolios almost from November 2021, you could see that actually it’s been a straight line upwards. So actually one of the best ways to make money and continues to be a good way to make money is basically do exactly the opposite of what happened during the zero interest rate QE induced bubble. I think a lot of that is happening in markets outside of the US and that’s where you saw a lot of the performance last year. The type of markets did really well last year. I know they’re more smaller periphery markets where these kind of markets which were put on very low PE multiples as a function of long term neglect from investors. And if you’ve got a market or part of a market which is on a cheap PE multiple, that’s indicative of it being neglected by investors. And it then doesn’t take much in the way of a kind of change in attitude or a change in investment flows for that P multiple to move very, very rapidly indeed. So despite South Korea going up 80% plus, it’s still only on a P of 14 times, I think, which is not exactly challenging.

And then you get, I think we talked about this chart on the right Hand side between. It’s just relationship between the starting forward PE and the returns last year. So I’m still looking for pockets of value. I’m still looking for bits of the market which has been left behind by this entire focus on one particular.

Andrew Lapthorne: Story. Yeah, I mean you make this great point that there is such a fear of getting away from the behemoths. They’ve delivered the goods time and time again. It’s just extraordinary. The risk of underperformance is a real thing for a fund manager and I like the way you frame it. It’s kind of distracting in almost preventing you from looking at again sort of just stocks or indices that present themselves on a valuation basis that are compelling and where that right hand chart, the good part of the right hand chart, the upper left part of your of your right hand chart the starting point being a very low PE and over a longer period of time that being informative about the ultimate results. Well, I want to finish this with some of your work in my own sandbox. I’m a very proud card carrying vol nerd. So I look a lot at options and you’ve done some interesting work on just retail participation in the options market. I think Citadel had a recent stat that talked. They’re estimating something like 60 odd percent of the flows are retail driven. And what we know about retail I think based on the GME incident is they’re actually in the option space probably smarter than folks realized.

They understand a little bit about gamma and understand time decay and convexity and they’re big. It just adds up. I like to say you tell 500,000 people to buy one contract all at once. That’s a big trade if you can get everybody to do the same thing. So walk us through some of your work. Maybe there’s some charts to display but I found some of your work.

Dean Curnutt: Interesting. Yeah, I mean there’s this kind of whole story about kind of the gamification of finance. A lot of my son’s friends walk around just making daily kind of punts on the direction of stocks with no intention of holding it for more than a day. It’s a bit like sports betting really the. And because you’re not going to make much money if you decide to go long or short a low volume stock you’re going to want to punt around in the most volatile assets that you’ve got. So it’s been the high volume small cap space which has really participated in this. And actually if you look at the trading behavior in those type of stocks and the volumes in the option markets, it’s very much tied into what you see in terms of the performance of Bitcoin, another very volatile asset that people like to play around with. And it was a really difficult period for quants in the US we have lots of strategies based around. The idea is that I don’t want to own unprofitable businesses. Businesses with bad balance sheets, businesses with simply a low share price are often bid up because there’s a perception that if you’re buying a stock at $2, it’s a lot, lot ch than if you’re buying it at $200, you know, so, but all of that is wrapped into volatile stocks being very well bid because of all this option activity.

And a lot of that option activity is coming from Asian based investors as well as US based investors. You’re seeing a lot of articles which have been talking about the massive volumes coming out of Asian markets. And you know, the difficulty for a lot of the quants is that we’re on the wrong side of this. There’s lots of money typically to be made from avoiding the trash in small cap indices. So alongside all this retail activity and retail frenzy, there’s often articles about quants struggling to cope. And it’s very clear that the trends in the US small cap index factor wise last year were completely different to what you saw in most other markets. So we’ve spent a lot of time looking at these things. I’ll flip you through to some relevant charts. This is the point I was making in terms of we kind of measure speculative factors, stocks which are really, really volatile, stocks with a low absolute share price and stocks with bad balance sheets. And this is a relative performance of those type of assets. You could see the frenzy that was really starting to go on during the summer. And then if you just tie in the performance of that kind of small cap speculation with Bitcoin, then there seems to be some kind of relationship.

And then when you start to think, okay, can I somehow measure retail activity? So we started looking at option market option volumes. And it’s incredible really, because you could see that it’s pretty much entirely concentrated in the most volatile quintiles of the market. And the size is huge. You’ve gone from 2 million contracts traded to 7 million contracts traded. And that’s again, you’re seeing that reflected in some of the data which is put out there by Citadel, et cetera. Now this stuff is quite near the money option. And as a consequence, all that option activity is directly being translated into hedging in the underlying and therefore you’ve got a very close relationship between the single stock volumes and all this option related volatility. So I’m left then having to think about how I measure us retail speculative behavior to see how I could either avoid it or take advantage of it. And for the large part at the moment it’s been one of avoidance. We’ve worked out if we could run our quant strategies away from this cohort of stocks. They tend to have a better out of sample experience than if we’re facing off basically retail speculation.

I imagine this stuff will start dying if you were to see unemployment go up and recession, et cetera. But at the moment it still seems pretty.

Andrew Lapthorne: Intense. I mean you look at both charts, but just taking the left one, the total volumes, you clearly see the COVID everybody’s at home, there’s been stimmy checks issued and Robinhood is flourishing. You see the GME pop there in 2021, early 2021, and that looks modest by virtue of what we just got to. It’s quite extraordinary. And I can certainly say just watching option volumes all day long, you see some of these hundred volume names and the option volume is enormous. You know, volume, volume are very correlated assets, correlated time series. So you said avoiding them, meaning that just trying to make sure you’re not long some of this cohort of names. Is that the.

Dean Curnutt: Idea? I mean they tend to appear in your short. It’s not quite 2021 where they were specifically picking on the most shorted stocks. I think it’s just as a function of people playing around in the high volume. They’ve ended up participating in buying the most shorted stocks. Normally stocks are shorted for a very good reason. Normally people use most shorted as a momentum indicator, I. E. You go towards them, you tend to agree with them and short them yourself. So actually when we have strategies which tend to be long, say good stuff and X for junk, you’re getting hurt by your short leg not behaving as your traditional factor model would expect. So actually what we try to then do is just say, okay, let’s just take them out of our universe altogether and then just run our strategies without them. And luckily there’s enough stocks left in the universe who are not participating here. But certainly there’s some very painful periods just like There was in 2021 for certain strategies performance as a consequence of this. And then it’s like, is this a permanent feature of markets now? Is this something that we have to contend with all the time?

There’s slightly kind of nihilistic in a way that rather than investing their money long term in shares, people are now just betting short term. And that’s always going to be to the advantage of a casino, not necessarily the gambler. So I’m hoping this is something which isn’t permanent. But the ramp up in activity this year has been, as you say, as you noticed, pretty.

Andrew Lapthorne: Exceptional. I mean, you’ve got the prediction markets, which folks are making calls on Fed policy on, and the gambling kind of concepts are moving closer together. Even some of these exchanges are having prediction markets on them and they’re putting them side by side. Here’s where I wanted to finish, Andrew. We’ve talked a lot about AI and we’ve talked about valuations of AI. And as a quant you are trying to discern whether there’s vulnerability here or whether we’re onto something brand new. And the old paradigms are maybe not as relevant, but you’re also using new tools as a quant that are a function of AI. So you’re evaluating the AI trade, but you’re also using new advanced quantitative tools. And that’s the part I just wanted you to share some thoughts on. As a quant, running a team, this new branch of just extraordinary data availability and ability to harness data in a way that even a couple years ago, I think things are accelerating. What has that meant to your ability to analyze data and model things? What’s new and what are you excited about on that.

Dean Curnutt: Front? My degree is in computer science from the 1980s. So we’re quant, we like data, we like effective ways of analyzing data. And I did a panel with you where I talked about our ML models many years ago and we’ve been using ML models to pick stocks for almost 10 years now. Successfully differentiate between AI and machine learning. Machine learning is a toolkit that we’re very familiar with. It’s very robust in terms of analyzing data and we’ve been using it and applying it to stock selection in all kinds of manners of ways for the last 10 years. Last year, for example, one of the most obvious things in equity markets is weekly mean reversion, that is selling last week’s winners and buying the losers. But it’s very, very difficult to get away after trading costs. We just asked our machine learning model to predict weekly returns and it came up with a mean reversion model which we can then trade after costs. That toolkit is super, super useful and that allows us to then take new data sets and give it to the machine. And say, look, you’ve got all these existing data sets which you then decide what to use.

If I give you this new data set, do you find any use in it? Do you find any features? So you get feature recognition from ML type systems. So without having ML to help us analyze all this data then we would be somewhat overwhelmed by all this data. So I think people are embracing it. I certainly think that prior to ChatGPT coming along there was a certain amount of cynicism towards our ML model. It’s a black box, we don’t understand it, et cetera, et cetera. So kind of one of acceptance and wow, we need to onboard this technology, we need to start using this technology and start working out how to incorporate it into our business. Now that’s ML LLMs completely different. I think the application of LLMs to the investment process so far is difficult because ML allows us to backtest with precision. LLMs does not. In fact, it’s almost, you know, generalized models. I don’t really want, I don’t really want a generalized model picking, picking my stocks. But in terms of things like productivity, you know, the usual things of helping us program quicker, build things quicker, that’s all super useful and we’re all learning every week about the capabilities of it.

I’m a big fan of using ML in terms of helping with the investment process because our out of sample experience is very, very.

Andrew Lapthorne: Good. Excellent. Well Andrew, it’s been a pleasure to reconnect have you back on the alpha exchange and it’ll be less than five years before you come back next time, so thanks for taking the.

Dean Curnutt: Time. I’ll also get some earphones which actually fit properly and stop dropping out next time. Lovely to see you. Thanks for having me.