Archive

Archive for the ‘Investing’ Category

Targeting Tuition as a Long Run Goal

September 21, 2017 2 comments

A few months ago, in a couple of articles entitled “The Bias in Investor Perceptions” and “What’s Wrong With the Long Run?”, I started to lay out the case for individuals and family offices to approach the investment challenge like a well-run pension fund or endowment would. Most well-run pensions and endowments these days are run in a “liability-driven” manner, which means that instead of maximizing the performance of the fund’s assets, subject to the risk of those assets – classic “mean variance optimization” based on “Modern Portfolio Theory” – the manager aims to maximize the funded status of the plan subject to the variance in the funded status. That is, the manager recognizes that having assets which mimic the behavior of the liabilities is valuable and worth at least some sacrifice in expected return. Many such portfolios, especially when they are fully funded, have two “buckets” for assets, one that is designated as the “liability immunizing” portfolio and one that is designated the “return-seeking” portfolio.

The reason this is a valuable mode of thought for an individual or family office is that it tends to force a focus on the long run, since the “liabilities” in question (such as retirement, college education, bequests, etc) tend to be long-term in nature. But there are a couple of challenges.

One such challenge is to get the client to focus on that long run, rather than on the brokerage statement that shows up in the mail every month and is always one mouse-click away. And that’s what I discussed/lamented on in those prior two articles.

The other challenge is that, unlike a pension fund or endowment, an individual has a kaleidoscope of different liabilities that behave differently from each other. Some of these, like saving for retirement, can be approximated by general consumer price inflation (CPI). But some, like saving for college or saving for future health care costs, behave in their own unique ways. And so the conundrum for many years has been “sure, personal Liability-Driven-Investing makes sense, but what assets do I hold against those liabilities?”

This has driven calls for “goal-appropriate financial instruments,” led by people like Arun Muralidhar (who specifically used that term in “Goals Based Investing, the KISS Principle, and the Case for New Financial Instruments”) and Robert Shiller, who muses on making “previously untradable risks tradable” in Finance and the Good Society, and has a history of innovative enterprises to attempt the same.

What I am excited about is a step forward in creating these instruments…one that my company Enduring Intellectual Properties has had a key role in. Last week, S&P Dow Jones Indices announced the launch of the “S&P Target Tuition Inflation Index,” which is designed to reflect inflation of college tuition and fees over long-term periods. The index was designed by S&P on the basis of a method that we developed a very long time ago but could never figure out how to commercialize. It involves liquid securities, and so can easily be made into investible products such as mutual funds, ETFs, UITs, and other structured products that individual investors can buy. The chart below shows the index, alongside CPI for College Tuition and Fees (NSA).

As with any liquid markets-based index compared to a periodic economic indicator, the tracking error on a day to day basis is not necessarily good. But it is also not terribly relevant – how your fund does next week should not affect how you feel about your college fund! The strategy is built on an understanding of what the main drivers of college tuition are, and these turn out to be fairly simple (unlike is the case with, say, Medical Care). Because the main drivers of college tuition inflation are the same as the drivers of the index, the errors tend to be “mean-reverting,” meaning that the longer you hold the index the closer (in annualized terms) you tend to be to the target.

Investing in a product linked to this index will not be a substitute for saving money in the first place. But, having saved, investing in such a product should help to reduce the risk that the money saved for college suddenly evaporates, as it did for many parents in 2000-2002 and 2007-2009.

I am ecstatic that we were able to team up with S&P to create such an important index – one that will help investors save in a goal-driven way, with their eyes turned to the future rather than to the latest wiggle in the markets.

Advertisements

The Gold Price is Not ‘Too Low’

Note: We are currently experimenting with offering daily, weekly, monthly, and quarterly analytical reports and chart packages. While we work though the kinks of mechanizing the generation and distribution of these reports, and begin to clean them up and improve their appearance, we are distributing them for free. You can sign up for a ‘free trial’ of sorts here.


Before I start today’s article, let me say that I don’t like to write about gold. The people who are perennially gold bulls are crazy in a way that is unlike the people who are perennial equity bulls (Abby Joseph Cohen) or perennial bond bulls (Hoisington). They will cut you.

That being said, they are also pretty amusing.

To listen to a gold bull, you would think that no matter where gold is priced, it is a safe haven. Despite the copious evidence of history that says gold can go up and down, certain of the gold bulls believe that when “the Big One” hits, gold will be the most prized asset in the world. Of course, there are calmer gold bulls also but they are similarly dismissive of any notion that gold can be expensive.

The argument that gold is valuable simply because it is acceptable as money, and money that is not under control of a central bank, is vacuous. Lots of commodities are not under the control of a central bank. Moreover, like any other asset in the world gold can be expensive when it costs too much of other stuff to acquire it, and it can be cheap when it costs lots less to acquire.

I saw somewhere recently a chart that said “gold may be forming a major bottom,” which I thought was interesting because of some quantitative analysis that we do regularly (indeed, daily) on commodities. Here is one of the charts, approximately, that the analyst used to make this argument:

I guess, for context, I should back up a little bit and show that chart from a longer-term perspective. From this angle, it doesn’t look quite like a “major bottom,” but maybe that’s just me.

So which is it? Is gold cheap, or expensive? Erb and Harvey a few years ago noticed that the starting real price of gold (that is, gold deflated by the price index) turned out to be strikingly predictive of the future real return of holding (physical) gold. This should not be terribly shocking – although it is hard to persuade equity investors today that the price at which they buy stocks may affect their future returns – but it was a pretty amazing chart that they showed. Here is a current version of the chart (source: Enduring Investments LLC):

The vertical line represents the current price of gold (all historical gold prices are adjusted by the CPI relative to today’s CPI and the future 10-year real return calculated to derive this curve). It suggests that the future real return for gold over the next decade should be around -7% per annum. Now, that doesn’t mean the price of gold will fall – the real return could be this bad if gold prices have already adjusted for an inflationary future that now unfolds but leaves the gold price unaffected (since it is already impounded in current prices). Or, some of each.

Actually, that return is somewhat better than if you attempt to fit a curve to the data because the data to the left of the line is steeper than the data to the right of the line. Fitting a curve, you’d see more like -9% per annum. Ouch!

In case you don’t like scatterplots, here is the same data in a rolling-10-year form. In both cases, with this chart and the prior chart, be careful: the data is fit to the entire history, so there is nothing held ‘out of sample.’ In other words, “of course the curve fits, because we took pains to fit it.”

But that’s not necessarily a damning statement. The reason we tried to fit this curve in the first place is because it makes a priori sense that the starting price of an asset is related to its subsequent return. Whether the precise functional form of the relationship will hold in the future is uncertain – in fact, it almost certainly will not hold exactly. But I’m comfortable, looking at this data, in making the more modest statement that the price of gold is more likely to be too high to offer promising future returns than it is too low and likely to provide robust real returns in the future.

Reversing the “Portfolio Balance Channel”

Note: We are currently experimenting with offering daily, weekly, monthly, and quarterly analytical reports and chart packages. While we work though the kinks of mechanizing the generation and distribution of these reports, and begin to clean them up and improve their appearance, we are distributing them for free. You can sign up for a ‘free trial’ of sorts here.


Today I want to write about something that’s been bothering me a bit recently. It’s about the Fed’s impending decision to start drawing down its balance sheet over some number of years (whether or not we have an announcement about that at tomorrow’s meeting, it seems likely that “balance sheet reduction” is on tap for later this year). Something had been gnawing at me about that, and until now I haven’t been able to put my finger on it.

It concerns the ‘portfolio balance channel.’ This bit of Fed arcana is part of how the central bank explained the importance of the practice of buying trillions in Treasury bonds. Remember that back when the Fed first started doing Large-Scale Asset Purchases (LSAP), they were concerned that a lack of ‘animal spirits’ were causing investors to shy away from taking risk in the aftermath of the credit crisis. Although this is entirely normal, to the FOMC it was something to be corrected – if people and firms aren’t willing to take risk, then it is difficult for the economy to grow.

So, as the Fed explained it, part of the reason that they were buying Treasuries is that by removing enough safe securities from the market, people would be forced to buy riskier securities. When QE1 started, 10-year TIPS were yielding 2.5%, and that’s a pretty reasonable alternative to equities in a high-risk environment. But the Fed’s ministrations eventually pushed TIPS yields (along with other yields, but by focusing on real rates we can abstract from the part of that decline that came from declining inflation expectations rather than the forced decline in real yields) down to zero in 2011, and eventually deeply negative. As expected, despite the risk aversion being experienced by investors they began to move into equities as the “only game in town” – think about how many times you’ve heard people lament they own equities because ‘there’s nothing else worth owning’? The eventual result, of course, was that expected returns to equities began to fall in line with the (manipulated) expected returns to other securities, until we got the current situation where, according to our calculations, TIPS now have a higher expected real return than equities again (but at a much lower level).

What was bothering me, of course, was that shrinking the balance sheet also implies reversing the “portfolio balance channel.” Via QE, the Fed forced investors into stocks because there were fewer Treasury securities outstanding; every time the Fed bought $1 of bonds, some fraction of that went into stocks. The reverse must also be true – for every $1 of bonds the Fed sells, some fraction of that money must come out of stocks.

I’m not the first person to note that reducing the balance sheet should be a negative for equities since it “reduces liquidity.” But I was always uncomfortable with the vagueness of the “liquidity” mechanism…after all, lots of people predicted cataclysm when the Fed “tapered” QE. The reversal of the portfolio balance channel, though, is a real effect. The money to buy the extra bonds that will be on the market – bonds not held by the Fed must be held by someone, after all – will come from somewhere. And some of that “somewhere” will be from equities, some from real estate, some from cash, etc. I don’t know how big an effect it will be, but I know the sign.

Horse Racing and Value Investing

June 28, 2017 1 comment

Momentum and value investing are two classes of strategies that, historically, alternate ascendancy in terms of which strategy is dominating the other. They are largely opposite strategies: a momentum investor buys a security because it has gone higher (because prices aren’t really a random walk, something which has gone up in price is more likely to continue to go up in price) while a value investor buys a security because it has gone lower (since the lower the buying price, the better the return on a security).

You can imagine the two strategies in the context of horse racing. The “momentum” strategy would be represented by betting on the “favorite,” the horse with the best odds to win as determined by the prior betting. (Some people think the track sets the odds on the horses, but that’s not the case. The payouts are based on the proportion of the entire betting pool allocated to bets on a particular horse, less the track’s vig. So, a horse with “good odds of winning” is simply the horse that has the most money bet on it to win.) That’s pretty close to exactly what a momentum investor in stocks is doing, right? A “value” investor, in the context of horse racing, is the person who bets on the long shots because they have big payoffs when they hit (and the bettor believes, obviously, that these unloved horses are irrationally disliked because most people like betting on favorites and winning frequent, small amounts instead of winning infrequent, large amounts.)

So at the track, sometimes the favorites win and sometimes the long shots win, and there are people in each camp that will tell you their strategy is the better one in the long run. I don’t know that there have been many studies of whether “value” or “momentum” investing in horse racing is the better strategy, but there have been numerous such studies in finance. Both value and momentum have been shown to improve investing strategies, with better risk-adjusted returns than simply buying and holding a capitalization-weighted basket of securities. They tend to have “seasons,” by which I mean long periods when one or the other of these strategies tends to be dominant. But it is very unlikely that either of these strategies could ever be the winner over the long run.

To see why, think of the horse track. Suppose everyone noticed that the favorites were winning, and so more and more money came in on the favorites. What would happen then is that the payoffs on the favorite would get worse and worse, and the payoff on the long shots would get better and better. Eventually, it would be very hard to make money betting the favorites unless they always won. On the other hand, if lots of money were to come in on the long shots, they wouldn’t be long shots for long. So neither strategy can dominate forever.

The same is true in finance. If everyone is betting on the previous winners, then eventually the “losers” become easy money, and vice-versa. The chart below (which is imperfect for a reason I’ll mention in a moment) illustrates the give-and-take. It shows the Russell 1000 “growth” index (RLG, in white) and the Russell 1000 “value” index (RLV, in orange). The source of the chart is Bloomberg.

You can see clearly how “growth” (which has similarities to momentum) outperformed in the Y2k bubble, depressing the heck out of value investors. But then value beat growth for a while, until the next bubble in 2007. The ensuing bear market crushed both strategies.

One caveat here is that the composition of the “growth” and “value” indices doesn’t change every day, and isn’t based on momentum, so that at the peak in 2007 a lot of stocks in the “value” index were not truly value stocks. But you get the general point.

The second, and more important caveat, applies to the years since 2009. This chart would lead one to believe that both value and growth stocks are doing equally well. And they are, given this definition of growth and value. But what this chart really means is that the distinction of “growth” and “value” are now less important than the single factor “momentum.” Whether you have a growth stock with momentum, or a value stock with momentum, is less important than if you compare performance to something else that does not have momentum.

We can illustrate this concept by calculating portfolios that are built to maximize momentum or value for a given risk constraint, and comparing the performance of the portfolios. I’ve done this for a bunch of different types of portfolios (different commodities, equities only, broad investor stock/bond/cash/commodity portfolios, etc) and they all look something like this chart, which shows the total returns of these two competing portfolios:

What I’m doing here is for the security universe in question, I’m calculating for each security a “momentum” score that is simply the year-on-year percentage change in price, and a simple “value” score that is the inverse of the four-year price change.[1] Then I optimize two portfolios, one which maximizes the value score and one which maximizes the momentum score, and then track that portfolio’s performance for the following month (whereupon the portfolios are reconstructed). If there was no memory to the momentum or value processes, these lines would wander around 100…a high momentum score would not increase next month’s performance, e.g.. But, evidently, it does and it has. Over the last three years, for this security universe, the “momentum” portfolio outperformed the “value” portfolios 78% of the time by a cumulative 50%. And this happens for every universe of securities I test. Even within commodities, which are universally hated, the high-momentum commodities are hated less.

Note that this is at the same time that in the first chart above the “growth” and “value” stocks have been performing about the same. This just means that the dispersion between growth and value has been narrow, which is another way that volatility is low.

As a value investor, this situation has been tortuous, and has led me to change the way we do certain things to keep from being purely value all the time. But as I said before, the situation cannot remain this way forever. Every computer is chasing every other computer, for now. But at some point, one of the computers will decide it’s time to lean the other way, and the first ones that do so will be the winners while the other computers start to chase momentum lower.

That might not be as fun for investors as the recent period has been, unless you’re the one who was getting paid on the nag at 200-1 odds.

[1] In this I am taking a cue from Asness, Moskowitz, and Pedersen, “Value and Momentum Everywhere,” Journal of Finance Vol LXVIII, #3, June 2013.

What’s Wrong With the Long Run?

June 6, 2017 4 comments

In my last article, I talked about the importance of getting clients to focus on their progress towards a long-term goal rather than on near-term performance. This is to help the clients, not to help the manager, but decreasing performance myopia is also a good thing for the manager. In addition to the obvious reasons this is true – less client turnover means fewer frictional costs for the manager – there is the less-obvious effect that it has on manager behavior. If our clients aren’t demanding that we chase a hot trend or hot stock or hot sector or hot asset class, it means they are also not rewarding those behaviors…and that, in turn, means that the manager can also focus on the long term, to the benefit of the client.

Focusing on progress towards a long-term goal can, unfortunately, introduce other problems. For one thing, it is hard to compare managers on the basis of how their existing clients are progressing successfully towards long-term goals. It is very easy to compare managers on the basis of the historical performance of client portfolios, and indeed both regulators and industry organizations like the CFA Institute have detailed rules about how client performance should be presented to as to make them more easily comparable. So, if my clients are making excellent progress towards their long-term goals but have “underperformed” this year because they didn’t own Tesla, the prospective client who is comparing our performance will probably go to the manager who is invested in that money-losing cult of personality.

Another problem with focusing on the long run is that there are lots of ways to make it appear as if progress is being made, or that the client is doing better than they really are, by tweaking assumptions. An unscrupulous manager could, for example, assume that stocks are going to have a return equal to their prior 5-year return (which right now is pretty darn good), but if the stock market begins to decline the manager could change his mind and instead decide that a 7% nominal return is appropriate. If we are basically trained hamsters pushing the levers that get us the treat from our clients, then there is an incentive to show them good news. In short, it’s harder to disguise adverse changes in current portfolio value than it is to disguise adverse changes in client progress towards a goal.

As an example of this behavior, consider the long-recognized problem that exists in the pension fund industry. A pension fund’s funded status depends importantly on the rate of return it assumes on the assets which are intended to provide for the fund’s future liabilities. And those assumptions have been ridiculously high for years. There is a great recent article by Pension & Investments Online (“Investment return assumptions of public pension funds”) that illustrates the point. Since 2001, the average return assumptions of pension plans has declined from 8% to 7.6%, despite the fact that asset markets are higher now than they were in 2001 (some of them, such as bonds, drastically so). In 2015 pension funds assumed, on average, a 9.7% return on US equities and a 15.2% return (!!) on real estate. Clearly, the models that pension funds use – or hire similarly-incentivized consultants to create – are not consistent with what we know about how markets really behave. But they’re very convenient for showing progress towards being fully funded.

So if a manager wants to help clients focus on the long-term – which he/she should – then he or she needs to use models that are conservative, and that do not get tweaked favorably over time. One way to do that is to employ a third-person analyst that deploys arm’s-length projections, and ideally one who is compensated over time on the basis of the long-term accuracy of the projections…but, since that sort of analytical contract is not generally available, a minimum requirement should be that the manager transparently disclose to clients the asset-class projections currently being used, and the method for generating them.

It is probably self-serving to point this out, but in that vein a manager who frequently exposes his thought processes to the blogosphere, in books, and in speeches is probably a safer bet than a manager who forwards you his company’s latest article on stocks for the long run.

Categories: Investing

The Bias in Investor Perceptions

June 1, 2017 7 comments

We can do the math. We can, until we are blue in the face, explain to investors why 10% returns in the equity market…even 7% returns…are unlikely going forward. We can show the picture below, sourced from data from Robert J Shiller, illustrating that high starting cyclically-adjusted PE ratios are associated with low future returns (the current level of the CAPE is about 29.5), and admonish that higher levels of the CAPE have been seen on only a few occasions that we all agree ex-post were bubbles.

We can do all this, and yet investors still anticipate that 10-20% returns will be delivered by equities going forward. The pessimistic ones think that only 5-10% is what we will see, ‘in line with historical returns’ that are as high as that of course only because our measurement ends at the current high levels. None of our arguments are new, and research illustrating that investors in the main do not get out just in time to avoid the bear market is hopelessly general because each individual enjoys his or her personal fable: “yeah, but I’m not that guy.”

They can be forgiven, perhaps, their poor memories because, after all, the bad events have been few and far between (at least, the bad events in terms of market returns) for a long time. The chart below shows the rolling 52-week returns of the S&P 500, before dividends, since 1979.

The two financial crises in the 2000s stand out for their deeply negative returns, and contrast with the more-frequent, but shallower, bear markets of the 1980s (of course, there weren’t any bear markets in the 1990s!). The compounded nominal price return since the end of 1978 until the end of last week was 8.76%.

But that’s not how people remember returns. Normal people do not take the ending point, divide by the starting point, and raise to the power of 1/(number of years). Perception is influenced by recency. Over the past five years, if you had asked each week “what has the return of the stock market been over the last year?” the answers would have averaged 12.0%. That’s recency. Perception also weights returns by frequency of observation – and over the 38 years covered by this chart, the average rolling 12-month return has been 9.9%.

So you can understand why individual investors resist when we tell them “the long run return of stocks has been about 7%” or admonish them to be careful about current high prices. In their minds, “stocks have been rising about 10-12% per year” for nearly four decades.

Selective memory also plays a part. When we tell stories about why these events occurred, and the story doesn’t include “we started from very high prices,” we excuse them as exceptions. The bear market in the early 2000s was “the popping of the Internet bubble,” and the one in the late 2000s was “the global financial crisis caused by greedy banks.” So the mind tends to dismiss these exceptions, or weight them less. This is where the “but I will get out next time” fantasy comes in – it justifies this mental calculation. But of course, if we eliminate the “exceptions” when stocks went down, the annual returns are even more remarkable. Since 1979, the rolling 12-month return conditioned on it being positive averaged 16.6%.

These are all irrational, but they are part of perception. From a practitioner’s standpoint, these are inconvenient and the industry has worked for a long time to try and educate investors away from these perceptions since otherwise clients only want to hold stocks. But we can’t change how people think, and how they perceive market returns.

This problem has gotten worse since the early 1990s, because of the accessibility of information about market returns. The Financial News Network was launched in 1981, but it wasn’t until CNBC’s launch in 1989, combined with Chairman Greenspan’s decision to open the Fed’s kimono a few years later, that it became very easy to “check the market.” And, since perception of returns is weighted by the number of observations, more frequent observations of positive numbers has increased the expectations of investors when it comes to stock market returns. Some of the lower-quality advisors actually make the problem worse, by calling clients more often when markets are up than when they are down.

I think education is nice, and we as practitioners should of course try to convey to clients proper expectations for returns. But we can’t beat these cognitive errors; instead, what we should be trying to do is to avoid the focus on recent returns and instead present the client with their progress towards a very long-term goal (see illustration below, which is from something we’re designing), such as a particular sort of goal in retirement (“I’d like to have enough to take two major trips every year.”)

This unfortunately can lead to other games, which I will talk about next week, but it also allows us to manage wealth in a way that beats the outcomes offered by Modern Portfolio Theory’s focus on near-term mean-variance optimization. Now, if only we can persuade clients to do it!

Categories: Investing, Stock Market, Theory

Is This Bubble Smaller Than We Thought?

I haven’t written in a few weeks. It has been, generally, a fairly boring few weeks in terms of market action, with inflation breakevens oscillating in a narrow range and equities also fairly somnolent. But I can’t blame my lack of posts on a lack of interesting things to remark upon, nor on March Madness, nor on New Jersey Transit (although each of these is a very valid excuse for the general lackadaisical nature of trading in recent weeks). In my case, I plead business exigencies as we are working on a few very exciting projects, one of which I expect to be able to announce in the next week or two.

But writing a blog post/article is never far from my mind. I’ve been doing it for far too long – since the ‘90s if you count the daily letters I wrote for client distribution when I was on Wall Street – and when I haven’t written something in a while it is a bit like an itch on the sole of my foot: I am constantly being reminded about it and the only way to make it stop is to rip the shoe off and scratch. Which tickles. But I digress. What I mean to say is that I have a long list of things I’ve written down that I could write about “if I have time this afternoon,” and it’s only the lack of time that has stopped me. (Some of these are also turning into longer, white-paper type articles such as one I am writing right now estimating the cost of the “Greenspan Put.”)

Some of these ideas are good ideas, but I can’t figure out how to address my hypothesis. For example, I suspect that inflation swaps or breakevens, now that they are near fair value for this level of interest rates, have some component in them right now that could be interpreted as the probability that the Border Adjustment Tax (BAT) eventually becomes law. If the BAT is implemented, it implies higher prices, and potentially much higher depending on the competitive response of other countries. If the BAT fails, then breakevens may not set back very much, but they should decline some; if the BAT looks like it is fait accompli, then inflation quotes could move sharply higher (at least, they should). But prediction markets aren’t making book on the BAT, so I don’t have a way to test (or even illustrate) this hypothesis.

But enough about what I can’t do or won’t be doing; today I want to revisit something I wrote back in December about the stock market. In an article entitled “Add Another Uncomfortable First for Stocks,” I noted that the expected 10-year real return premium for equities over TIPS was about to go negative, something that hadn’t happened in about a decade. In fact, it did go slightly negative at the end of February, with TIPS guaranteed real return over ten years actually slightly above the expected (risky) real return of equities over that time period. At the end of March, that risk premium was back to +3bps, but it’s still roughly the same story: stocks are priced to do about as well as TIPS over the next decade, with the not-so-minor caveat that if inflation rises TIPS will do just fine but stocks will likely do quite poorly, as they historically have done when inflation has risen.

But I got to wondering whether we can say anything about the current market on the basis of how far stocks have outperformed the a priori expectations. That is, if we made a forecast and a decade goes by and stocks have shattered those expectations, does that mean that the forecast was bad or that stocks just became overvalued during that period so that some future period of underperformance of the forecast is to be expected? And, vice-versa, does an underperformance presage a future outperformance?

The first thing that we have to confess is that the way we project expected real returns will not produce something that we expect to hit the target every decade. Indeed, the misses can be huge in real dollar terms – so this is not a short-term or even a medium-term trading system. Consider the following chart (Source: Enduring Investments), which shows the difference of the actual 10-year return compared with the a priori forecast return from 10 years prior. A positive number means that stocks over the period ending on that date outperformed the a priori forecast; a negative number means they underperformed the forecast. In context: a 5% per year miss in the real return means a 63% miss on the 10-year real return. That’s huge.

What you can really see here is that stocks have – no surprise – very long ‘seasons’ of bear and bull markets where investors en masse are disappointed with their returns, or excited about their returns. But let me update this chart with an additional observation about real yields. During the period covered by this chart, there have been three distinct real yield regimes. In the 1960s and 1970s, real yields generally rose. In the late 1970s, 10-year real yields rose to around 4.25%-4.50%, and they didn’t begin falling again in earnest until the late 1980s. (This is in contrast to nominal yields, which started to fall in the early 1980s, but that was almost entirely because the premium for expected inflation was eroding). Between the late 1970s and the late 1980s, real yields were more or less stable at a high level; since the late 1980s they have been declining. In the following chart (Source: Enduring Investments), I’ve annotated these periods and you may reasonably draw the conclusion that in periods of rising interest rates, stocks underperform a priori expectations in real terms while in periods of falling real interest rates, stocks outperform those expectations.

These rolling 10-year rate-of-change figures are interesting but it is hard to see whether periods of outperformance are followed by underperformance etc. It doesn’t look like it, except in the really big macro picture where a decade of outperformance might set the stage for a decade of underperformance. I like the following look at the same data. I took the a priori 10-year real return forecast and applied it to the then-current real price level of the S&P 500 (deflated by the CPI). That produces the red line in the chart below (Source: Enduring Investments). The real price level of the S&P is in black. So the red line is the price level forecast and the black line shows where it ended up.

As I said, this is not a short-term trading model! It is interesting to me how the forecast real level of equities didn’t change much for a couple of decades – essentially, the declining market (and rising price level) saw the underperformance impounded in a higher forecast of future returns. So the “negative bubble” of the 1970s is readily visible, and the incredible cheapness of stocks in 1981 is completely apparent. But stocks were also cheap in real terms in 1976…it was a long wait if you were buying then because they were cheap. Value investing requires a lot of patience. Epic patience.

However, once equity returns finally started to outpace the a priori forecast, and the actual line caught up with the forecast line, the market leapt higher and the twin bubbles of 1999 and 2006 are also apparent here (as well as, dare I say it, the current bubble). But since the forecast line is climbing too, how bad is the current bubble? By some measures, it’s as large or nearly as large as the 1999 bubble. But if we take the difference between the black line and the red line from the prior chart, then we find that it’s possible to argue that stocks are only, perhaps, 30% overvalued and not as mispriced even as they were in 2006.

This may sound like slim solace, but if the worst we have to expect is a 30% retracement, that’s not really so terrible – especially when you realize that that’s in real terms, so if inflation is 3% per year then you’re looking at a loss of 10-15% per year for two years. That’s almost a yawner.

On the other hand, if we are entering an up cycle for real interest rates, then the downside is harder to figure. In the last bear market for real yields, stocks got 60% cheap to fair!

None of this is meant to indicate that you should make major changes in your portfolio now. If all of the evidence that stocks are rich hasn’t caused you to make alterations before now, then I wouldn’t expect this argument to do it! Rather, this is just a different rationality-check on the idea that stocks are overvalued, and my words could actually be taken as soothing by bulls. The chart shows that stocks can be overvalued, and outperform a priori expectations that incorporate valuation measures, for years, even decades. Maybe we’re back in one of those periods?

But we have to go back to the very first point I made, and that’s that if you don’t feel like betting the 30% overvaluation is going to get worse, you can lock in current real return expectations with zero risk and give up nothing but the tails – in both direction – of the equity bet. The equity premium, that is, is currently zero and stocks are additionally exposed to rising inflation. I see nothing tantalizing about stocks, other than the possibility that the downside is perhaps not as bad as I have been fearing.


Administrative Note: Our website at EnduringInvestments.com is about five years overdue for a facelift. We are currently considering how we want to change it, the look & feel we want, and the functionality we desire and require. If you have a suggestion for something you think would be helpful for us to include, please let me know. (Note that this is not a solicitation for web design services so please do not ask! We have picked a firm to do that. I’m just curious what customers and potential customers might want.)

Categories: Investing, Stock Market
%d bloggers like this: