Authors
Hi everyone and welcome to The Value Perspective podcast, where this week we are joined by Ben Inker, co-head of asset allocation at GMO. Ben joined the firm straight after graduating from college in 1992 and has gone on to work very closely with finance legend Jeremy Grantham, as well as being an active contributor to GMO’s extensive research library. For introducing us to Ben, we would like to thank Robert Hunter, organiser of the annual London Value Investor Conference, which we suspect would interest fans of this pod. This year’s conference, at which Ben will be speaking, takes place on 18 May. Juan Torres Rodriquez and Andy Williams sat down with Ben to discuss his experiences working with Jeremy Grantham and James Montier at GMO; whether mean reversion is really ‘dead’; how investors can look to break old habits; where he thinks value sits in the cycle today; and the difference between ‘value traps’ and ‘growth traps’. Enjoy!
Chapter headings for Ben Inker on The Value Perspective Podcast
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* Having investment legends as colleagues
* Data and the ‘journey to understanding’
* Is mean reversion really ‘broken’?
* When value investors have to look beyond value
* Where are we in the current value rally?
JTR: Ben Inker, welcome to The Value Perspective podcast. It is a pleasure to have you here. How are you?
BI: I am good. Thanks very much for having me.
JTR: Where do we find you today?
BI: Well, I am in our offices in Boston – and this will be one of the last few times I’m here. After 35 years in the same building, we are moving to a new one that is slightly higher above sea level – right now, we are exactly one foot above sea level, which is getting increasingly uncomfortable! So this will be one of my last hurrahs in the office I’ve worked in for 31 years.
JTR: That is very exciting. For those who might not know who you are – and there will not be many value investor listeners who do not – can you tell us a bit about yourself and about GMO?
BI: Sure. GMO is an institutional investment manager, which was founded in 1977. We manage stocks, bonds, multi-asset and alternatives. My job at GMO – I’ve been here a long time; for 31 years – is I co-head our asset allocation group. So my team is responsible for figuring out what kinds of stocks and bonds around the world we want to be investing in. Over my career, I have also been a direct equity analyst and a portfolio manager for stock portfolios, multi-asset portfolios and hedge funds.
As a firm, GMO tends to have a very strong valuation bias. That does not mean everything we do is traditional value stocks but we do have this very strong belief the return you are going to get from any asset is going to be driven by its valuation. That underlying philosophical premise certainly drives everything my team does and much of what happens across GMO.
JTR: Am I right in saying you started working at GMO straight out of college?
BI: Yes, I did. I started as a research analyst working for Jeremy Grantham. He had never had a dedicated research analyst before and wasn’t entirely sure what he was going to do with me – but I was foisted upon him and it wound up working out alright in the end.
Having investment legends as colleagues
JTR: Obviously Jeremy Grantham is a huge name in finance circles – and has been for a very long time. What is it like working with him?
BI: It has been extraordinary. Getting to learn from one of the real innovators and original thinkers in investing for 30 years has been great. It can be a little bit intimidating dealing with someone whose historical knowledge is as acute as his is – he will not only remember things I said to him, say, 15 or 25 years ago; he will also remember oh, you know, if I think back to what was happening in 1973, we bought this stock at this price and it moved to this price and here’s what we were thinking. So it can be a little bit terrifying thinking about how much he can recall of the last 50 years of investing – but he has been an astonishing person to be able to learn from.
JTR: One reason Jeremy is so well-known is because he has called some of the greatest bubbles in financial markets over the course of the last 30 years. One question I would ask then is why is he perceived to be trying to time the market?
BI: Well, it is an interesting thing. Actually, much of the time, I think he would say, You don’t want to bother trying to time the market – most of the time, show up, do your work, your diligence, your security analysis and stay out of trouble. But, over the course of his career, what he has noted is, periodically, something sufficiently extraordinary will go on in the markets as to have the potential to ‘wash away’ the benefits of coming in and doing your job day-by-day. And when markets get to crazy prices, that is predominantly where extraordinarily losses come from.
So Jeremy’s focus on this certainly predates my coming to GMO. The first great bubble where we experienced a lot of pain – and then a lot of benefit from having avoided it – was the Japan bubble in the late 1980s. But what we realised from that – what he realised from that – is markets are capable of moving to prices that seem utterly impossible ahead of time. Who would have believed that a stockmarket that had never traded above 25x earnings would move to 65x earnings? And then, from those levels, the single important thing is to make sure to avoid that, right?
You could have been doing diligent security analysis within Japan from 1989 to 2009 and you might have outperformed Japan – but you wouldn’t have made anybody any money. So avoiding those oncoming ‘tidal waves’ is something Jeremy spends a lot of time thinking about. But those kinds of bubbles don’t occur that often – honestly, I would say in the last 20-odd years, they have come around more often than we would have guessed but, still, they are not very frequent. But, when they occur, it is important for people to be aware – and so he gets loud when he sees the evidence that a bubble has formed!
JTR: Here on The Value Perspective, we are big followers of the very generous research you guys make public – and my colleague Andy Evans asked me to ask what it is like working with James Montier?
BI: James is a very interesting character! It can be a lot of fun working with him because, over the years, he has looked at so many different problems – and so, no matter what is going on from a research standpoint, the nice thing is, you can call up James and ask, for example, Hey, we’re trying to figure out how to think about European insurers given what has gone on. And he’s like, Well, here’s how I think about insurers. I spent a lot of time on that when I was in Hong Kong in the late 1990s. We built this model. Here’s how I think about how that works ...
And that is really cool. On the other hand, it can be a bit frustrating dealing with James because he has some very strongly-held views about what does and doesn’t matter. And if you are interested in a topic, which he is adamant does not matter, he is just going to tell you, That doesn’t matter – that is a stupid question and you should not be asking me that! But, among other things, he is an incredibly engaging guy and an extraordinary speaker so I always love the chance to hear him present. And, frankly, I always enjoy the chance to just call him up and have a chat about whatever topic we are grappling with from an investment standpoint.
Data and the journey to understanding
AW: Ben, that is actually an amazing segue into a question I really wanted to ask you. The genesis of this podcast was decision-making in uncertain environments – and one area we and our listeners are really interested in is behavioural biases and how we account for those. Clearly they exist in markets but they also exist within investment teams and they influence decisions. Now, I understand GMO’s process is very data-driven so I would be very interested to hear how you account for those behavioural biases you see playing out – not just on a broad scale in the market, but also actually within your investment committee meetings.
BI: Well, some of what we do at GMO is strongly data-driven – we do run a number of quantitative strategies. Some of it is on the more fundamental side of things – but the data really matters. And the first thing I would say is the biggest problem with being data-driven in investing is the data itself – a lot of the data doesn’t necessarily make sense. And the first thing you need to do, as a data-driven investor, is to turn the data into something that makes sense, right? 35 years ago, when I was first studying finance, one of the things that was ‘widely known to be true’ is companies with negative book value were close to bankruptcy. Today, McDonalds has negative book value, Boeing has negative book value – big, strong companies have negative book value because book value does not mean what it was supposed to mean.
So the first thing you need to do, if you’re going to be data-driven, is get some economically useful data. Once you have done that – and, in our case, that was a product of probably tens of man-years of work – the question is, how do you build a portfolio? And how do you build a portfolio that is reasonable, given the uncertainties of the market? And then how do you build a business, given you know the market is capable of being inefficient for longer than the average client’s patience?
So there is a whole level of things I think you need to do. In fact, the very first one is making sure to be quite diligent about updating your beliefs and valuations. One problem for investors is falling in or out of love with securities or countries or styles. And, for us, the discipline of, say, building our asset class forecasts is sometimes those asset class forecasts are telling us, Value stocks look expensive and are expected to underperform. So having good discipline helps you avoid the problem of just assuming, Well, I loved these things a year ago, I loved them five years ago – I must still love them now.
As for the somewhat unrelated problem of how to run a business where you know you can be wrong for a long time – a lot of that is about communication. Getting the right clients in the door to begin with; and then making sure they know exactly what you are doing – and why. Frankly, for us, the reason we publish as much research as we do is it is an efficient way for our clients to understand why we’re doing what we’re doing.
It has the side-effect of allowing other investment managers to know why we’re doing what we’re doing, which is of mixed benefit! But it is really important because it is not enough for an investment manager to outperform over time. Investment managers can outperform over time and still see their underlying investors in them underperform – because of poor timing as to when those investors hire and when they fire. So one of the things we spend a lot of time upon is trying to make sure we are as clear with our clients on what we’re doing and why – to help buy us enough time for the markets to eventually become ‘sane’.
AW: Is the narrative around the data is also really important then? As you say, one aim of GMO making so much research public is to improve actual client outcomes so they match actual fund manager performance profiles. So is that something you have thought about very actively throughout your careers – how do we tell the story with this data? It certainly feels like GMO is doing that in a very well developed way versus some others.
BI: I think you’re right that we do. And I think a lot of that comes from the legacy of having Jeremy Grantham as a founder because – of people who think about the world in a very disciplined data-driven way – he is an absolutely extraordinary storyteller. I can remember the first client conference we had after I joined – this was the fall of 1992 – and it was the first time I had ever really gotten to see Jeremy present. I had been back in the corner, doing research on currencies or what have you and they didn’t let me speak to clients or anything, right? I was a 21 year old who knew nothing – but I got to sit there in the client conference.
He gave this presentation and, somewhere in the middle of it, he just stopped speaking. And he looked around and said, I have completely forgotten what I was talking about. Can somebody remind me? A client piped up and said, You were talking about, let’s say, the return to high-quality stocks in the US. And he was like, Oh yes – and then he continued and kind of explained it all. And I found it utterly eye-opening. First, it was the best speech I had ever seen a human being give – despite the fact that, in the middle of it, the worst thing that could happen to a speaker happened! And what Jeremy was able to do – and I in turn have tried; I don’t claim to be the speaker Jeremy is, but I’ve tried to learn – is take people through the journey that you took to get the understanding. Human beings learn through stories – so you’re not going to convince anybody by throwing up a linear regression and saying, See! Look at that beta or r-squared. Isn’t that cool? And they shouldn’t be convinced – because a regression on its face is as likely to be a statistical artefact as anything else.
What you need to do – both to have confidence in yourself and to allow your client to have confidence – is to take them through: here is the underlying economic logic that caused us to do this; here is the result that caused us to believe, Yes, we are right, we understand something about the world; and here are the reasonable conclusions you can derive from that. It may not always be the most polished presentation but it really resonates with people because it helps them take the journey you took to reach the conclusions you reached.
Is mean reversion really ‘broken’?
JTR: That is very interesting. Mean reversion is such a powerful concept in finance – and so important for GMO’s process too. What do you say to those who argue mean reversion is now ‘broken’.
BI: Mean reversion is powerful – but it is also a shorthand. Asset prices, or valuations, have no obligation to revert to some particular level – whether that is an average over some period of time or what have you. But what really does have to happen is, if you were going to get a certain return from assets in the long run, those assets need to be priced at a level that is consistent with earning that return. And if it is going to earn that return, that asset has to be going through that level of valuation periodically or it is just not going to happen.
If equities are going to give you 5% real, they need to be priced to deliver 5% real. So what needs to revert is valuations to a level where earning that 5% real from sustainable sources is doable. Now, it could be the case that – I don’t know – 60 years ago, equities needed to deliver 6% real or 7% real and now they only need to deliver 4.5% real so they are not going to trade at the same valuations. But I don’t think it is possible for mean reversion to be ‘broken’ in the sense of ‘returns from assets are not going to be driven, in the end, by the valuations those assets are trading at’.
But to really understand what needs to revert – and what doesn’t – you can’t just look at prices. You can’t even just look at naive valuation measures. You need to dig into the underlying drivers of return for this asset, for this activity, and ask, Which of those drivers are going to be impacted and be different because of the valuations you are at today? You can choose to say, I think that is going to revert. You can choose to say, I think that is going to stay where it is. But what you need to do is make sure your expected returns are consistent with where valuations are now – and also have a reasonable philosophical belief about where they could be sustained in the long run.
That was a little bit theoretical but, when we looked at where growth stocks were priced as of late 2020 or early 2021, we thought they were priced to deliver – in the long run – a negative return above cash. Well, that’s stupid – they can’t possibly stay at those levels forever. So something had to change. But whether the market needs to trade at a level that is going to give you ‘cash plus three’ or ‘cash plus four’ – I don’t know with certainty which those are going to be. But I can say ‘cash plus minus one’ is not plausible – and so that thing has to revert.
JTR: Why do you run your asset allocation portfolio forecast over seven years in particular?
BI: Well, we started doing it over 10 years. And we did that simply because 10 seemed like a nice round number. Jeremy then asked me to dig a little deeper – around 22 years ago or so – and just look to answer the question, How long does it take assets, on average, to get back to fair value? And the answer was around seven years. So seven seemed a reasonable result. Then, another 10 years later, when we dug in a little bit more deeply when revising our forecast methodology, we found a little bit more nuance.
If you are modelling assets as an AR(1) [autoregressive] process, you do indeed find that, for equities, you tend to move one-seventh of the way back to fair value in a given year – so seven years is a nice shorthand for that. But that isn’t necessarily true if you’re looking at small caps versus the market, say, or value versus the market. And so, even though it’s under the seven-year ‘brand’ – because for groups like stocks or bonds – seven years is about right, there is a little bit more nuance when we are looking at groups of stocks relative to the market because where we see evidence that mean reversion tends to happen faster, we will incorporate it. So the seven years is actually, at this point, a little bit of an oversimplification but it is still true that the best data we have is the market tends to move one-seventh of the way back to normal in an average year.
When value investors have to look beyond value
JTR: You have observed in the past that habits, once formed, are very difficult to break. After a very tough decade or more for value, how do you communicate to people that heuristics are very powerful and sometimes the data is showing you that you need to move from one asset class to another, or abandon a style that has worked for you in the past, for one that feels more unfamiliar?
BI: So there are several questions in there – and I’m probably not going to be able to do justice to all of them! The first thing is to recognise that, as a valuation-driven investor, it cannot possibly be the case that you will always want to buy traditional value stocks. I actually wrote a paper in 2005, called The Trouble with Value. And the point I was making, after this extraordinary run value had been on since 2000, was that value stocks were trading at a much smaller discount than normal to the market – and that this was a problem in that value deserved to underperform.
So the first thing you need to do in order to be intellectually honest is to make sure the conditions that caused you to like this thing, whatever it is, still persist. In 2000, value stocks were trading an extraordinary discount to the market – it was the opportunity of a lifetime – but, by 2005, they were a lousy investment. So that is not directly about heuristics – that is about having the discipline to make sure you understand where the returns have come from, for the asset you own; where to expect those returns to be coming from going forward; and whether that asset – be it value stocks or the S&P or anything else – is priced to deliver what you need from it.
The issue with heuristics is ... heuristics are relatively simple algorithms for determining your behaviour. And the thing I tend to like about heuristics – under certain circumstances – is the more complicated algorithms sometimes just give stupid answers! And so trying to build a multi-asset portfolio from an absolute kind of mean-variance process does weird things. You know, if you tailor it so that, if everything is priced normally, you are going to own 70% stocks and 30% bonds, if stocks are 5% more expensive than that, the model is going to say, Well, I should own less than 70% in stocks and I should own more bonds – despite the fact that stocks still have a higher expected return than bonds. So you are voluntarily saying, I want to run a portfolio that is going to underperform my benchmark – and it is like, Well, why would I want to do that?
Now, if you instead ran it for tracking error, what you would find is that mean-variance optimisation would say, Oh, as long as the expected return to stocks is greater than bonds, I am going to be overweight stocks. But that is stupid too because then the 70/30 wasn’t a reasonable benchmark to measure yourself against. So the nice thing about a heuristic is, if a broader quantitative process is going to be giving you stupid answers, there is still a huge benefit to the discipline of having a standard ‘thing to be doing’ – so, ‘When X happens, I expect to do Y’.
Because, without that, what we find behaviourally is there is a tendency to say, Well, whatever I have been doing has been working – let’s keep doing that. Or, Whatever I have been doing hasn’t been working – please, God, let me come up with an excuse not to. And the heuristic that helps you say, You know what – if this thing has not been doing too well, my bias should be sell it and do something else, you don’t necessarily have to follow that. And one of the nice things about heuristics is, you know they are an oversimplification so you don’t have to – but it pushes you in that direction. And it pushes you against doing what emotionally will feel easiest, which is keeping going with anything that’s been working and abandoning anything that hasn’t.
Where are we in the current value rally?
AW: You mentioned the value rally that ran from the dotcom crash in 2000 through to the mid-2000s and, arguably, the rotation from growth to value we think we are in at the moment started around the vaccine announcement in November 2020. As ever with value, it has gone in fits and starts but, in terms of what the data is telling us today, and how far in we are in and how much further there might be to go, would you say we are closer to 2000 or to 2005?
BI: I don’t think we are particularly close to 2005. In a very simple way of measuring things, in 2005, value stocks were trading at a 20% premium to their long-run average relationship to growth stocks. Today, value stocks are trading at about 75% of their long-run valuation relative to growth stocks. So, if things were going to mean revert, in 2005 we had a problem because value stocks were overpriced to the tune of 20%. Today, they are underpriced to the tune of 33%. So on a pure valuation perspective, we don’t look anything like 2005.
Now, under the surface, things are a little bit more complicated because one of the things we find – and this is more true in the US than it is elsewhere – is that simplistic analysis just breaks the market into two halves. And, if you look under the surface, there is more going on in the US than just those halves – and, in particular, within value, of that cheap half of the market, the cheapest 20% of the market is really trading at a huge discount to its normal valuation. And that next 30% – the rest of value – is actually trading expensive versus its history. So, in the US, overall value looks pretty good – but, in fact, it is only this tail that is worth investing in. The rest of value just doesn’t look very attractive.
Overall, though, value is trading at something like, as we speak, maybe the 10th percentile versus its history –again, at that 25% discount to its normal discount. So it is trading a lot wider. And one of the things people do not seem to understand about value and value investing is it’s not just about mean reversion. The charm of value trading at a bigger discount than normal is not simply, Well, it’s going to come back up and trade at a smaller discount – it is that rebalancing within value is going to be so much more powerful when value is trading at a big discount.
That rebalancing effect is something people just do not understand and, as a result, they just don’t actually quite get what value investors are doing. If you think about value investing, what people will say is, Well, value stocks under-grow the market so you get less growth and you get more income. And that is absolutely true. The problem is, value stocks under-grow the market by, like, five and they out-income the market by, like, one and a half – and minus five plus one and a half gives you a negative number.
So that would suggest value should underperform forever – and it hasn’t. And the reason why it hasn’t is because value is not a static strategy. Every year, you come back and you look at the stocks you bought at the beginning of the year – and some of them no longer look like value stocks. On occasion, that may be because they have gone bankrupt! But bankruptcy is actually a pretty small issue. What is a much bigger thing is some of them now look like growth stocks. And the bigger the discount value stocks are trading, relative to growth stocks, the more pleasure there is in having one of your value stocks turn into a growth stock.
So the size of that rebalancing effect is very sensitive to the size of that discount. Right now, we have a big discount – and, on the flipside, this is the big problem for growth stocks still today. The problem with growth stocks is a disappointing growth stock is going to be really painful when those growth stocks are trading at a big premium. Because, man, if they disappoint and people say, Oh, this isn’t a growth stock anymore, that is a huge fall. If we were instead trading at 2005 or even 2014 levels of spread and the growth stocks weren’t trading that expensive, relative to the market, it doesn’t hurt that much. So a wide spread is really important – and it is really important, even if you didn’t believe in mean reversion.
AW: Is there anything particularly interesting about that cheapest quintile today, in terms of its composition, versus its history?
BI: We have been agonising over that, right? We have a group of stocks that looks optically really quite cheap – the question is, well, is it really cheap for a reason? On an individual stock basis, it is – and it always is, right? In order for a stock to get to look really cheap something bad has happened. So you look across the names in the portfolio and it is, like, Oh yeah, I understand why the market doesn’t like Meta, I understand why the market doesn’t like Intel, I understand why the market doesn’t like JP Morgan ... all of these stocks – yeah, they’re cheap because somebody hates them. And they have a reason for doing that.
But if we look across them, questions we would ask would be, Well, is this a particularly low-quality group? No, it is not. Is it low-quality relative to its history? No, it is not. Is it excessively cyclical? Is there a lot of industry concentration? And, if we adjust for that industry concentration, does that cheapness disappear? No –we don’t see anything. Now, the thing that is a little bit tricky – and this is somewhat trickier in thinking about deep value than it is for value, but it is a problem when thinking about value as well – is that people want to say, Hey, value stocks have this characteristic; value stocks are cyclical; value stocks are low-quality; value stocks are this; value stocks are that – and at times they are, right?
If you look at value stocks in the winter of 2009, that was a low-quality group of companies. Now, if you look at the performance of value stocks during the course of 2008, one of the tricky questions was, What are you going to do with the financials because the financials look pretty cheap and they did very badly. But, for the moment, I am going to pull out the financials and look at the rest of value and say, Well, value underperformed a little bit, but not that much. But the stocks that are in value as of February 2009, those stocks had been destroyed. So the basic issue is value as of February 2008 was quite a different group of stocks, with quite different characteristics, than it was in February of 2009.
And in February 2008, when we were about to enter – or had just entered – the worst economic and financial crisis since the Great Depression, the value stocks weren’t particularly cyclical, they weren’t particularly low quality and they performed as they should have. By 2009, that portfolio had turned over and the stuff you had added looked quite different. So one important thing to recognise about value is it doesn’t tend to have permanent characteristics. It has some semi-permanent biases but the intensity of those biases really changes.
You know, one of the questions a lot of clients ask us today is, Well, how vulnerable is value in a recession? And what I can say is, if I look at the group of stocks that are value now, they don’t look particularly cyclically vulnerable. If I look at the long-run performance of value in recessions, sometimes it wins, sometimes it loses. But if I look at value at the end of recessions, it is always a group of stocks that did poorly in the recession – and that has normally worked out pretty well because those are the stocks that get the best bounce as the economy returns.
JTR: Have the issues with Silicon Valley Bank and Credit Suisse given a black eye to the value camp?
BI: Lord knows, it didn’t do anything for value, as of now! How long this lasts, though, I don’t know. Silicon Valley Bank – although somewhere on its way to zero, it must have flashed as looking ‘cheap’ – it is not like it looked cheap most of the time. It is amazing, right – it suffered from an absolutely classic bank run of the kind that we had lots of before the existence of the Federal Reserve, and we haven’t seen in a long time. But, hey, banking is banking.
I think there has been a certain amount of throwing out babies with bathwater with value here. If you look at the value stocks – and, in particular, the deep-value stocks – they are not hugely vulnerable in the event of a credit crunch because they don’t need a ton of financing. Now, you do tend to be overweight financials in value. You don’t have to allow yourself to be but, when we look at financials today, we see a bunch of financials that really do look pretty cheap – and we think it makes sense to own some. We also think it makes sense to recognise financials are a slightly tricky group because they are one kind of stock where looking rally cheap can be a problem, right?
Forget about Silicon Valley Bank – the reason why Credit Suisse had to die is because it was trading at a valuation level such that it could not raise the capital it needed, right? If a bank is trading at a big discount to book value, it just can’t survive if it has a capital hole – and that is very different from an industrial. So financials are a little bit tricky – and they are subject to periodic crises. Personally, I don’t think it looks like we deserve to have a financial crisis of the 2008 variety – but I wouldn’t want to have a portfolio that was entirely financials today. I don’t think I would ever want to have a portfolio that was entirely financials!
People just assume, Oh well, banks are in value, banks are doing badly, therefore I need to sell all of value. And that is kind of weird but, you know, you talked about behavioural problems in the market – the flip side is, the only way the market gets inappropriately priced, which is the only thing that creates opportunities to add value, is somebody doing something irrational. So yes, it’s a pain for near-term performance to have value stocks you don’t think deserve to go down, go down. On the other hand, they are cheaper than they were – and that is pretty cool!
AW: It is reassuring to hear there is some decent quality in that cheapest quintile – and that it is not as cyclical as some may assume. A lot of people might find that surprising because of the narrative and ‘muscle memory’ going back to 2009 – though, personally, I find it amazing how long that has lingered in investors’ minds.
BI: Yes. And it’s not even fair, if you look back to 2009 – because, yes, value was really junky in 2009 but it wasn’t in 2008. And being junky in 2009 was a good thing – junk had a hell of a run! Unfortunately, the banks had a really nasty dilution event but there are times when it makes sense to own junky stuff. Now, I would say the models I am using to pick that cheapest 20% are willing to pay up for quality – so one thing we are always interested in looking at is, What are the stability of the cashflows from this company? The more stable they are, the higher the valuation we are prepared to pay. So in order for a junky company to look really cheap to us, it needs to be trading at a substantially lower valuation than one that is high-quality.
The lesser-spotted ‘growth trap’
AW: Most investors will have heard of ‘value traps’ – not so many will have heard of ‘growth traps’. And while value managers are always asked about value traps, I would bet growth managers almost never get asked about growth traps! You have written a brilliant paper on why both kinds can be so dangerous for investors so, for those who are not familiar with it, could you outline your arguments?
BI: Sure. The first thing we needed to do was come up with a reasonable, simple definition of a ‘value trap’. What we said was a value trap is a company that looked cheap at the start of the year yet proved to be substantially less cheap than it looked because the underlying fundamentals wound up being substantially worse than anybody expected. So, basically, a value trap is a value stock that disappointed. And I think part of the problem for value managers is that value stock that looked cheap and then underperformed along the way may still look cheap. So it is still in your portfolio having disappointed – and I think the basic reason why value managers get criticism here is because they’re still there in the portfolio.
So we did a couple of things. One is we looked at value traps; we defined them as those value stocks that disappointed in the given year; and then we asked the question, Well, what percentage of value stocks disappoint in a given year? And how likely are they to disappoint in the next year? And what we found was –round numbers – 30% of all value stocks disappoint in a given year and are therefore value traps. And the next year, they have a 30% chance of disappointing again. What that says is there is zero serial correlation in ‘value trapness’ – at any given point in time, 9% of the value universe will have disappointed two years in a row. But it is not the case that having been a value trap, this is now a toxic company.
But the other cool thing we were able to do, having come up with that definition, is to say, All right, we can now look at the growth universe for companies that have that same characteristic. So we just defined a ‘growth trap’ as a growth company that disappointed investors over the course of 12 months. And because of the gains over earnings, the way we chose to do that – which isn’t the only way you could do it – is we wanted to see a company, either in value or growth, that underperformed on revenues – because companies tend to cheat less on the revenue side of things, and saw expectations for future revenues come down. So this wasn’t just some one-time thing but an expectation for the future.
And what we found is, on average, if 30% of value stocks disappointed and were value traps in a given year, maybe 33% of growth stocks were – so growth traps were a little bit more prevalent than value traps. But the bigger issue was value traps underperformed the value universe. It is painful and it is reasonable that investors ask about those value traps because, if you could avoid them, that would be awesome. They underperformed the value universe on average by about nine points a year. So if you could avoid that 30% of your universe that underperforms by nine – man, that’s 300 basis points of outperformance. That would be great.
Yet the growth traps underperformed the growth universe by about 13.5%. They underperform by more and they are more prevalent – so why don’t growth managers always get hit with the question of what do you do about growth traps? I think it’s because, if you’re truly a growth manager and your growth stock disappointed, it no longer feels like a growth stock and it is not going to be in your portfolio anymore, right? The growth manager who owned Meta in 2020 because they thought it was a big grower? Well, by 2022, when the company had just disappointed two years in a row, they don’t own it anymore.
So because they’re not in the portfolio, there isn’t that much of a tendency to ask, So tell me about this thing in your portfolio – in that the things in a growth portfolio will tend to have done well, right, because they are still there and they still look like growth stocks. Now, I am not a growth manager but I do think people, first, underestimate the pain of having been wrong with growth stocks; and that rebalancing effect is really negative for growth. People don’t get it and, as a result, they really get wrong what growth investing is.
But they are also too obsessed with value traps for value managers – and I think the reason why is because the stocks tend to stay in the portfolio. And there is nothing more frustrating than, You were wrong in this stock last year – what makes you think you’re going to be right this year? And if they come back and say, Oh, but look how cheap it looks now and I don’t think it’s going to disappoint – and then it disappoints again – you know, you just want to strangle them! And that will be true, on average, of 9% of their portfolio. It will be true, on average, of 0% of the true growth stock manager’s portfolio – but only because they already sold them, not because they didn’t cause damage in the portfolio along the way.
JTR: Cycles can last a very long time and, earlier on, you mentioned the importance of research in helping GMO’s clients understand the way you are investing and the importance of looking at the world from a certain perspective. Given that, what tools – behavioural or otherwise – do you use to encourage both the team internally and your clients to focus on the long term and tune out the noise of short-term underperformance?
BI: Oh man – if I knew how to do that really well, life would be a lot easier! What we try to do with any client who is hiring us is, we’ll talk to them and say, Hey, look at our history – we are capable of looking stupid for extended periods of time because, you know, in order to get a great opportunity, what you need is a good opportunity that moves against you to become a better opportunity that moves against you to become a great opportunity. You have invested with us because we have done a good job handling those great opportunities – but there is pain getting there and that pain can go for a long time. So one thing is – make sure the clients getting in know what they’re getting in for.
But the reason why even that isn’t enough is, while you may have that understanding with the client CIO who hired you, that CIO has a limited expected span in their seat. That CIO is going to be replaced. That CIO has an investment committee that is going to be replaced over time. And, even if you have done a great job with that investment committee and with that CIO, you have to continue to do that again and again, because their memories are fallible – you are not the only thing they have to worry about.
But there is turnover in their investment staff, there is turnover on their investment committee and I don’t know, honestly, how to be true to a style, which is subject to periodically having the cycle move against you for a long time, without running a very substantial risk of getting fired at a bad time by investors – even if you have done a wonderful job of communicating with them. But what I will say is, if you have not done a good job of communicating with them, and the only reason why they hired you was they liked that past track record, as soon as your track record doesn’t look like that, you are at risk. So you have to communicate, you have to be clear, you have to be convincing – but, even then, it isn’t easy.
JTR: Ben, we are coming to the end of our session and we want to ask you for some book recommendations - either something you have you been reading lately or some all-time favourites?
BI: I guess this is shilling for former colleagues and friends but here are a couple of what I think are the best books that have been written in the last few years about investing and how to think about investing. One of them is by a former colleague of mine [and recent TVP podcast guest], Edward Chancellor, called The Price of Time. Among other things, it is this extraordinary history of credit and what credit has meant and the various ways it has created problems over time and, given I worked with the guy for close to a decade and had read everything he had written, it was amazing how much I still learned in reading this book.
Another book I thought was incredibly valuable to read was The Delusion of Crowds, by Bill Bernstein. It is kind of an updating of Charles Mackay’s original work, The Madness of Crowds. Its subtitle is ‘Why people go mad in groups’ and it just points out – not just on a financial basis, but in religion and politics – the ways groups of people can do utterly insane things. It is, on the one hand, kind of horrifying as one thinks about the risks we run as humanity – but when you are facing the problem of, Oh my god, the market seems to be doing something crazy right now, how do I come to grips with that? It is very helpful to understand well, that is all part of the nature of human experience – and here is 500 pages of the last 150 times the world has done that.
JTR: That is fantastic. Ben Inker, thank you very much for coming onto The Value Perspective podcast. Best of luck with moving to the new office and have a nice trip to the London Value Conference in May.
BI: All right. Thanks very much for having me
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