James Montier is a member of Grantham Mayo van Otterloo’s (GMO’s) Asset Allocation team. Prior to joining GMO in 2009, he was co-head of Global Strategy at Société Générale. Mr. Montier is the author of several books including Behavioral Investing: A Practitioner’s Guide to Applying Behavioral Finance ; Value Investing: Tools and Techniques for Intelligent Investment ; and The Little Book of Behavioral Investing . Mr. Montier is a visiting fellow at the University of Durham and a fellow of the Royal Society of Arts. He holds a B.A. in Economics from Portsmouth University and an M.Sc. in Economics from Warwick University.
Advisors and retail investors can access GMO’s asset allocation by buying the Wells Fargo Advantage Absolute Return instead of the GMO Benchmark-Free Allocation Fund and the Wells Fargo Advantage Asset Allocation Fund instead of the GMO Global Asset Allocation Fund. The minimum investment for the GMO Funds is $10 million, while the minimum investment for the Wells Fargo Funds is $1,000.
I spoke with James on Jan. 28.
How do you select the subjects on which you do research? Are there particular publications or information sources that offer good insight or inspirations for the topics you choose?
It’s really tough. The inspiration comes from a wide variety of places, many of which are client-related. Often it comes from conversations with clients around their interests – smart beta and risk parity would be good examples. More often, though, I ask myself, “What do I actually think about that issue?”
A lot of the time, I respond to the issues and the topics the markets throw up. Other times, it’s more direct. Once or twice I’ll come across something and think, “No, I really don’t agree with that.” Looking for the evidence that I disagree with is always useful, so I spend a reasonable amount of time reading people with whom I definitely do not agree.
Jeremy Siegel is a pretty good example of somebody in that camp at the moment, with his views on the inadequacies of the Shiller cyclically adjusted price-earnings ratio (CAPE). Then I think about how I might battle with the potential logical flaws are in those arguments.
Siegel’s argument, if I understand it correctly, is not with the CAPE methodology. It’s with the underlying data that’s being used. He’s argued that the national income and products account (NIPA) data should be used rather than the S&P data that Shiller has been using, and that if you use the NIPA data you come to different conclusions. What are your thoughts on that?
The attacks on the CAPE are kind of odd, right? It hasn’t done a bad job. It works. A large part of me says, “Well, if it’s not broken, why the hell are you trying to fix it?” People say, “Well, valuations haven’t mean-reverted for the last 20 years.” My response is, “No, but returns, frankly, have been very poor for the last 20 years.” So there is no inconsistency between a high valuation and low returns.
I think Siegel’s main point is that goodwill accounting misses half of the data. Yes, goodwill accounting has certainly increased the volatility of earnings. But also we had a situation during the crisis, somewhere around March 2009, almost exactly at the bottom, when the accounting authorities suspended FASB rule 157, which was the mark-to-market rule.
All of a sudden, financial institutions could lie with impunity. They no longer had to recognize any of the impact of asset deterioration on their earnings. One can make an equal case on the other side that earnings probably recovered too fast because of that suspension of the rule. That may have created a rather weird pattern. Maybe those two patterns offset, and therefore that is one of the reasons you should take a 10-year average, as the CAPE methodology employs.
The idea of replacing S&P earnings with NIPA earnings is slightly surreal. The S&P is a relatively small number of stocks, whereas NIPA effectively represents very much the entire economy. So the two constituents are very different.
NIPA profits are at extreme highs right now, as are listed-market profits. Basing an evaluation on something that is at an all-time high is almost certainly going to make things look cheaper. To me, this is a strange way of honestly adjusting a valuation measure. I have not yet seen any evidence that the NIPA-adjusted series gives a better return forecast over time than the straight Shiller. That would have to be the hurdle. The burden of proof is on those who think the Shiller model is somehow not useful.
How does your research impact the investment process at GMO?
It very much depends on the topics. Something like smart beta or risk parity doesn’t have any huge impact on our portfolios, because they’re not things we particularly believe in any way.
But I started doing some work on forecasting market returns. This is part of a project I’ve been involved with on profit margins, a topic about which I’ve written extensively. Margins have direct impacts on the forecasts, and ultimately those forecasts are what drive our portfolios.
In early 2010 you published a white paper titled What Goes up Must Come Down, and in it you observed that the U.S. profit margins were at record highs and you are on the lookout for sound arguments as to why GMO might be wrong in its assumption of margin reversion. Do you have any additional thoughts at this point on why profit margins have remained so high?
The macroeconomic framework that we used in that document, the Kalecki equation, still holds true. As I wrote in that paper, I wasn’t talking about the next 12 or even 24 months, but rather that margins would eventually come under pressure principally because governments were likely to end up tightening their fiscal belt, rightly or wrongly. They tend to do that over time. That was likely to drag down profits, and that remains the major source of concern. It probably won’t be this year in the U.S., because the budget deal that has been proposed has removed some of the sequestration pressure, though not all of it. But the pressure picks up again in 2016 and 2017. So, certainly within the time horizon of our forecast we would expect to have mean reversion of profit margins as our base case.
You hear a lot of stories about low tax rates, low interest rates, globalization and sector differences. All of these are taken into account by the Kalecki equation.
Low tax rates are a good example. People point out that corporate tax rates have never been lower, and that accounts for high profit margins. There’s an element of truth to that, but it’s actually exactly what the Kalecki equation says, because those low tax rates in the corporate sector imply that the government needs to run a greater deficit to maintain the same level of government spending.
Sector differences are another one we come across. In the 1970s, we had a very different industrial composition in the market than the one we find today. But the reality is, that doesn’t account for anywhere near as much as the margin expansion as one imagines. If you applied the 1970s sector weightings to today, you would still get very, very high profit margins. Only about a percent of the profit margins can be explained by sector shifts over the intervening time period.
None of those stories hold water. The most likely path is towards mean reversion over the next seven years.
What about low interest rates? Have you looked at that in the context of the Kalecki equation?
Low interest rates are another pretty good example of the framework, because ultimately those interest rates would have to be paid to somebody. It’s generally the household sector that benefits from higher interest rates. What that really means is that household savings have to be altered, because household income is less than it would be if you had high interest rates. The household-savings element of the Kalecki equation is where low interest-rate effect shows up.
I haven’t been able to find an explanation that isn’t assumed within the Kalecki equation. I describe it as one of Tolkien’s rings. In the beginning of The Lord of the Rings, there’s a poem about having one ring that in the darkness finds them all, and to me, that is the real essence of the Kalecki equation.
In your most recent commentary, No Silver Bullets in Investing, you chronicled a risk-parity portfolio, and you stated that proponents of risk parity often say that one of the benefits of their approach is to be indifferent to expected returns. You cited arguments by others that risk parity is what investors should do if they know nothing about expected returns. But GMO has a demonstrated history of insights about prospective returns for various asset classes and publishes its forecast monthly. Your latest seven-year forecast indicates poor real returns for bonds and negative real returns to cash. If one is negative on equities, what is the best asset to pair with stocks to mitigate risk?
That is the $64 million question right now. The issue is, as you quite rightly point out, everything is expensive right now. How do you build a portfolio that recognizes the fact that cash is generating negative returns, and bonds are now more attractive than they were, but still not enticing in any great sense?
The answer is, you have to recognize that this is the purgatory of low returns. This is the environment within which we operate. As much as wish it could be different, the reality is it isn’t, so you have to build a portfolio up that tries to make sense. That means owning some equities where you think you’re getting at least some degree of reasonable compensation for owning them, and then basically trying to create a perfect dry-powder asset.
The perfect dry-powder asset would have three characteristics: it would give you liquidity, protect you against inflation and it might generate a little bit of return.
Right now, of course, there is nothing that generates all three of those characteristics. So you have to try and build one in a in a synthetic fashion, which means holding some cash for its liquidity benefits. It means owning something like TIPS, which are priced considerably more attractively than cash, to generate inflation protection. Then, you must think about the areas to add a little bit of value to generate an above-cash return: selected forms of credit or possibly equity-spread trades, but nothing too risky.
You don’t want to be caught reaching for yield.
In 2011, you wrote a paper titled, The Seven Immutable Laws of Investing. Which of those laws are you particularly concerned about in the current environment? Those laws were: Always insist on a margin of safety; this time is never different; be patient and wait for the fat pitch; be contrarian; risk is the permanent loss of capital, never a number; be leery of leverage; and never invest in something you don’t understand.
The one that scares me most is the first one, because I just can’t find any assets that have a particularly high margin of safety. There is nothing that reaches out and screams, “Hey, I’m really undervalued.” Therefore, you are in this situation where you’re stuck in this kind of foie gras market where you’re being force-fed risk assets. That is a very uncomfortable position to be in.
But, you have to balance that against the second rule – this time is never different – with, “Well, maybe this time is different.” This is a period of enormous financial repression in which central banks around the world are committed to keeping their short rates low for an extended period. That genuinely is different compared to most of history, or at least most of history that we have experienced. How should that affect your desire to allocate assets?
It’s not obvious to me that anyone has the perfect answer when you build a portfolio like the one I described, trying to balance risk assets and safe-haven assets and maintain some vague degree of normality..
You can imagine two polar extreme outcomes: Central banks could end financial repression tomorrow. You would get real-rate normalization and the only asset that survives unscathed is cash. Bonds suffer, equities suffer and pretty much everything else suffers. Or, the central banks keep their rates incredibly low for a very, very long period.
The portfolios you want to hold under those two different outcomes are extremely different. I have never yet met anyone with a crystal ball who can tell me which of these two outcomes is most likely – or even which one could actually happen. You’re left trying to build a portfolio that will survive both outcomes. It won’t do best under either one of the two outcomes or the most probable outcome, but it will survive. That really is the preeminent occupation of my mind at the moment.
GMO became an expert on bubbles before “black swans” and “tail events” entered the lexicon of investors. What do you make of the increased talk of bubbles, and is bubble-hunting a useful investment activity?
Ah, that’s a great question. I’m going to annoy some of my colleagues by saying this, which is always good. Bubble hunting-can be overrated, and the reason is, ultimately, I’m not sure it’s particularly helpful, in many regards. Now sometimes that is not true. I’ll try to elucidate on the specifics.
Let’s take an equity-market bubble, like the technology-media-telecom (TMT) bubble. Everyone now agrees I think, except maybe two academics, that TMT was actually a bubble. To some extent it didn’t really matter, because you had a valuation that was so extraordinarily high. You didn’t actually have to believe it was a bubble. You just knew you were going to get incredibly low returns from the fact that you were just massively over-paying for those assets.
Knowing it was a bubble as such helped reassure those of us who were arguing that it was a bubble, though we could see the more common signs of mania like massive issuance, IPOs and shifting valuation metrics that eventually were off the income statement altogether.
All of those things are good confirming evidence, but ultimately it didn’t matter because the valuation alone was enough to persuade you to think, “Hey, I’m just not going to get any returns in these assets even if it isn’t a bubble.”
Bubble-hunting is much more useful when it is with respect to things like credit conditions and the kind of environments we saw in 2007, when it was far less obvious from valuation alone. Valuation was extended, but wasn’t anywhere near the kinds of levels that we saw in 2000. It was extended, but not cripplingly so by 2000 standards. But the ability to actually think about the credit bubble or the potential for a bubble in fundamentals or financial earnings is very useful.
The use of bubble methodology is certainly not to be underestimated, but people can get a little too hung up on it and start to see bubbles everywhere. You hear things about bond bubbles. Do I really care? All I need to know is bonds are going to give me a low return from here. Ultimately, for a buy-and-hold investor, the redemption yield minus expected inflation gives me my total return for bonds. There can’t be anything else in there.
You get that conclusion that, “Hey, I don’t really care if it’s a bubble or not.” I suspect bubble-hunting can be useful in some regards. But people use the term too loosely and it can lead to unhelpful assessments.
Tail events of a good-natured basis do not seem to get labeled. The development of technology that has made available massive amounts of shale energy might qualify as such an event. Have you given any thought to its impact on the economy and the markets?
You make a great observation that on the upside it is just called a good outcome. We take them as the new baseline, and it’s only on the downside that people get upset, which is fairly amusing.
In terms of shale, it’s not something that I’ve spent any time thinking about. Not that it isn’t important; it’s just not within my wheelhouse of particular skills. I can’t do a better job than many who have examined it. I know there is potential for a fairly large shift in the energy position. How those will play out through both the economy and market is sadly beyond my limited knowledge.
Your firm’s presidential cycle work would have predicted that 2013, the first year of a term, would be a relatively poor one for the stock market. But as we know it was one of the best in the last couple of decades. Do you have any thoughts on why that might be, and has your opinion of the importance of the presidential cycle changed?
It’s quite important to note that we have never used the presidential cycle in any formal way. We view it as an interesting after-the-fact run of history that we’ve had. It doesn’t influence the way that we build portfolios.
We are in a world in which we have extreme monetary stimulus, which is characteristic of a year three and a year four of a presidential cycle, where they’re trying to boost the market. One wouldn’t have been surprised to see the behavior from the market we saw last year. It comes down to this almost psychological belief in the Fed’s ability to keep on priming the stock market. To some extent that explains the oddity of last year from a presidential-cycle standpoint.
Is the experience of being bearish too early in previous cycles having an impact on the investment process at GMO?
It probably is. One of curses of value managers is we’re always too early both to buy and to sell. One of the ways that were trying to deal with that is to deliberately slow our behavior down, so we try to react at least to a moving average of the forecast rather than the spot forecasts. We know our forecasts are generally built to be conservative. Therefore, as they become more and more extreme, we will react to them. But we do think we should react to them as a general rule – not in all circumstances – with a degree of slowing down of our behavior. That is certainly in the interest of our clients, given our history.
Read more articles by Robert Huebscher
