Posts Tagged ‘Shiller PE’

Butler|Philbrick|Gordillo and Associates’ argue in Valuation Based Equity Market Forecasts – Q1 2013 Update that “there is substantial value in applying simple statistical models to discover average estimates of what the future may hold over meaningful investment horizons (10+ years), while acknowledging the wide range of possibilities that exist around these averages.”

Butler|Philbrick|Gordillo use linear regression to examine several variations of the Shiller PE (and other cyclically adjusted PE ratios over periods ranging from one to 30 years), Tobin’s q ratio and Buffett’s total market capitalization-to-gross national product ratio (“TMC/GNP”). They have analyzed the power of each measure to explain inflation-adjusted stock returns including reinvested dividends over subsequent multi-year periods, setting their findings out in the following matrix:

Matrix 1. Explanatory power of valuation/future returns relationships

Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013).
Butler|Philbrick|Gordillo comment:
Matrix 1. contains a few important observations. Notably, over periods of 10-20 years, the Q ratio, very long-term smoothed PE ratios, and market capitalization / GNP ratios are equally explanatory, with R-Squared ratios around 55%.  The best estimate (perhaps tautologically given the derivation) is derived from the price residuals, which simply quantify how extended prices are above or below their long-term trend.The worst estimates are those derived from trailing 12-month PE ratios (PE1 in Matrix 1 above). Many analysts quote ‘Trailing 12-Months’ or TTM PE ratios for the market as a tool to assess whether markets are cheap or expensive. If you hear an analyst quoting the market’s PE ratio, odds are they are referring to this TTM number. Our analysis slightly modifies this measure by averaging the PE over the prior 12 months rather than using trailing cumulative earnings through the current month, but this change does not substantially alter the results.As it turns out, TTM (or PE1) Price/Earnings ratios offer the least information about subsequent returns relative to all of the other metrics in our sample. As a result, investors should be extremely skeptical of conclusions about market return prospects presented by analysts who justify their forecasts based on trailing 12-month ratios.

Butler|Philbrick|Gordillo note:

Our analysis provides compelling evidence that future returns will be lower when starting valuations are high, and that returns will be higher in periods where starting valuations are low.

So where are we now? Table 1 below from the post provides a snapshot of some of the results from Butler|Philbrick|Gordillo’s analysis. The table shows estimated future returns based on an aggregation of several factor models over some important investment horizons:

Table 1. Factor Based Return Forecasts Over Important Investment Horizons

Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013)

Butler|Philbrick|Gordillo note that:
You can see from the table that, according to a model that incorporates valuation estimates from 4 distinct domains, and which explains over 80% of historical returns since 1871, stocks are likely to deliver 1% or less in real total returns over the next 5 to 20 years. Yikes.

They conclude:

[T]he physics of investing in expensive markets is that, at some point in the future, perhaps years from now, the market has a very high probability of trading back below current prices; perhaps far below.

The post is a well-researched, and comprehensive analysis of several long-term market-level valuation measures. It is a worthy contribution to the research in this area. Read Valuation Based Equity Market Forecasts – Q1 2013 Update.

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In Fat Tails: How The Equity Q Ratio Anticipates Stock Market Crashes and The Equity Q Ratio: How Overvaluation Leads To Low Returns and Extreme Losses I examined Universa Chief Investment Officer Mark Spitznagel’s June 2011 working paper The Dao of Corporate Finance, Q Ratios, and Stock Market Crashes (.pdf), and the May 2012 update The Austrians and the Swan: Birds of a Different Feather (.pdf), which discuss the “clear and rigorous evidence of a direct relationshipbetween overvaluation measured by the equity q ratio and “subsequent extreme losses in the stock market.”

Spitznagel argues that at valuations where the equity q ratio exceeds 0.9, the 110-year relationship points to an “expected (median) drawdown of 20%, and a 20% chance of a larger than 40% correction in the S&P500 within the next few years; these probabilities continually reset as valuations remain elevated, making an eventual deep drawdown from current levels highly likely.”

So where are we now?

Smithers & Co. tracks the equity q ratio for the US. The chart below shows each to its own average on a log scale.

According to Smithers & Co., the equity q ratio currently stands at 1.05, which is some 17 percent above 0.9, the ratio at which “an “expected (median) drawdown of 20%, and a 20% chance of a larger than 40% correction in the S&P500 within the next few years.” Smithers & Co. note:

Both q and CAPE include data for the year ending 31st December, 2012. At that date the S&P 500 was at 1426 and US non-financials were overvalued by 44% according to q and quoted shares, including financials, were overvalued by 52% according to CAPE. (It should be noted that we use geometric rather than arithmetic means in our calculations.)

As at 12th March, 2013 with the S&P 500 at 1552 the overvaluation by the relevant measures was 57% for non-financials and 65% for quoted shares.

Although the overvaluation of the stock market is well short of the extremes reached at the year ends of 1929 and 1999, it has reached the other previous peaks of 1906, 1936 and 1968.

Like the Shiller PE and Buffett’s total market capitalization-to-gross national product measure, the equity q ratio is a poor short-term market timing device. This is because there are no reliable short-term market timing devices. If one existed, its effect would be rapidly arbitraged away. So why look market-level valuation measures? From Smithers & Co.:

Understanding value is vital for investors.

(i) It provides a sound way of assessing the probable returns over the medium-term.

(ii) It provides information about the current risks of stock market investment.

(iii) It enables investors to avoid nonsense claims about value.

Extreme discipline is required at market extremes. Gladwell’s profile of Taleb, Blowing Up, shows how difficult such periods can be:

Empirica has done nothing but lose money since last April. “We cannot blow up, we can only bleed to death,” Taleb says, and bleeding to death, absorbing the pain of steady losses, is precisely what human beings are hardwired to avoid. “Say you’ve got a guy who is long on Russian bonds,” Savery says. “He’s making money every day. One day, lightning strikes and he loses five times what he made. Still, on three hundred and sixty-four out of three hundred and sixty-five days he was very happily making money. It’s much harder to be the other guy, the guy losing money three hundred and sixty-four days out of three hundred and sixty-five, because you start questioning yourself. Am I ever going to make it back? Am I really right? What if it takes ten years? Will I even be sane ten years from now?” What the normal trader gets from his daily winnings is feedback, the pleasing illusion of progress. At Empirica, there is no feedback. “It’s like you’re playing the piano for ten years and you still can’t play chopsticks,” Spitznagel say, “and the only thing you have to keep you going is the belief that one day you’ll wake up and play like Rachmaninoff.”

Finally, even though we can plainly see that markets are presently overvalued on several measures, we can’t know when a sell-off will occur. All we can say is that returns are likely to be sub-par for an extended period, and that the probabilities are quite high that a substantial drawdown will occur in the next two to three years. One thing that we can be sure of, is that when it does occur, the catalyst that ostensibly triggers the sell off will be treated as a black swan, even though the real cause is massive overvaluation. From the perspective of behavioral investment, this story of Gladwell’s is interesting:

In the summer of 1997, Taleb predicted that hedge funds like Long Term Capital Management were headed for trouble, because they did not understand this notion of fat tails. Just a year later, L.T.C.M. sold an extraordinary number of options, because its computer models told it that the markets ought to be calming down. And what happened? The Russian government defaulted on its bonds; the markets went crazy; and in a matter of weeks L.T.C.M. was finished. Spitznagel, Taleb’s head trader, says that he recently heard one of the former top executives of L.T.C.M. give a lecture in which he defended the gamble that the fund had made. “What he said was, Look, when I drive home every night in the fall I see all these leaves scattered around the base of the trees,?” Spitznagel recounts. “There is a statistical distribution that governs the way they fall, and I can be pretty accurate in figuring out what that distribution is going to be. But one day I came home and the leaves were in little piles. Does that falsify my theory that there are statistical rules governing how leaves fall? No. It was a man-made event.” In other words, the Russians, by defaulting on their bonds, did something that they were not supposed to do, a once-in-a-lifetime, rule-breaking event. But this, to Taleb, is just the point: in the markets, unlike in the physical universe, the rules of the game can be changed. Central banks can decide to default on government-backed securities.

US equity markets are very overvalued on a variety of measures. If Spitznagel’s thesis is correct that the frequency and magnitude of tail events increases with overvaluation, investors need to exercise caution given the extreme level of the equity q ratio. If the eventual event precipitating a sell off is a black swan, but we can expect black swans because of the market’s overvaluation, is it still a black swan?

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I’ve been giving Robert Shiller’s cyclically-adjusted price earnings ratio a run on Greenbackd recently (see 73-Year Chart Comparing Estimated Shiller PE Returns to Actual ReturnsOn The Great Shiller PE Controversy: Are Cyclically-Adjusted Earnings Below The Long-Term Trend? and How accurate is the Shiller PE as a forecasting tool? What backtested returns does the current PE forecast?). He discusses it in some detail in this interview with Consuelo Mack on WealthTrack:

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h/t Redditor Beren

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In The Siren’s Song of the Unfinished Half-Cycle John Hussman has a great annotated chart comparing the ten-year returns estimated by the Shiller PE to the actual market returns that emerged over the following ten years from each estimate (from 1940 to present):

Hussman estimates the ten-year return using a simple formula:

Shorthand 10-year total return estimate = 1.06 * (15/ShillerPE)^(1/10) – 1 + dividend yield(decimal)

He justifies his inputs to the simple formula as follows:

Historically, nominal GDP growth, corporate revenues, and even cyclically-adjusted earnings (filtering out short-run variations in profit margins) have grown at about 6% annually over time. Excluding the bubble period since mid-1995, the average historical Shiller P/E has actually been less than 15. Therefore, it is simple to estimate the 10-year market return by combining three components: 6% growth in fundamentals, reversion in the Shiller P/E toward 15 over a 10-year period, and the current dividend yield. It’s not an ideal model of 10-year returns, but it’s as simple as one should get, and it still has a correlation of more than 80% with actual subsequent total returns for the S&P 500.

Here is Hussman’s application of the simple formula to several notable points on the chart and comparison to the subsequent returns:

For example, at the 1942 market low, the Shiller P/E was 7.5 and the dividend yield was 8.7%. The shorthand estimate of 10-year nominal returns works out to 1.06*(15/7.5)^(1/10)-1+.087 = 22% annually. In fact, the S&P 500 went on to achieve a total return over the following decade of about 23% annually.

Conversely, at the 1965 valuation peak that is typically used to mark the beginning of the 1965-1982 secular bear market, the Shiller P/E reached 24, with a dividend yield of 2.9%. The shorthand 10-year return estimate would be 1.06*(15/24)^(1/10)+.029 = 4%, which was followed by an actual 10-year total return on the S&P 500 of … 4%.

Let’s keep this up. At the 1982 secular bear low, the Shiller P/E was 6.5 and the dividend yield was 6.6%. The shorthand estimate of 10-year returns works out to 22%, which was followed by an actual 10-year total return on the S&P 500 of … 22%. Not every point works out so precisely, but hopefully the relationship between valuations and subsequent returns is clear.

Now take the 2000 secular bull market peak. The Shiller P/E reached a stunning 43, with a dividend yield of just 1.1%. The shorthand estimate of 10-year returns would have been -3% at the time, and anybody suggesting a negative return on stocks over the decade ahead would have been mercilessly ridiculed (ah, memories). But that’s exactly what investors experienced.

The problem today is that the recent half-cycle has taken valuations back to historically rich levels. Presently, the Shiller P/E is 22.7, with a dividend yield of 2.2%. Do the math. A plausible, and historically reliable estimate of 10-year nominal total returns here works out to only 1.06*(15/22.7)^(.10)-1+.022 = 3.9% annually, which is roughly the same estimate that we obtain from a much more robust set of fundamental measures and methods.

Simply put, secular bull markets begin at valuations that are associated with subsequent 10-year market returns near 20% annually. By contrast, secular bear markets begin at valuations like we observe at present. It may seem implausible that stocks could have gone this long with near-zero returns, and yet still be at valuations where other secular bear markets have started – but that is the unfortunate result of the extreme valuations that stocks achieved in 2000. It is lunacy to view those extreme valuations as some benchmark that should be recovered before investors need to worry.

The actual return deviates from the estimated return at several points, including the most recent ten-year period from 2002. Hussman comments:

Note that there are a few points where the estimate of prospective market returns would have differed from the actual market returns achieved by the S&P 500 over the following decade. These deviations happen to be very informative. When actual returns undershoot the estimate from a decade earlier, it is almost always because stocks have moved to significant undervaluation. When actual returns overshoot the estimate from a decade earlier, it is almost always because stocks have moved to significant overvaluation. Note the overshoot of actual market returns (versus expected) in the decade since 2002. The reason for this temporary overshoot is clear from the chart at the beginning of this weekly comment: the most recent 10-year period captures a trough-to-peak move: one full cycle plus an unfinished bull half-cycle.

While Hussman’s formula is exceedingly simple, with a correlation of more than 0.8 it’s also highly predictive. It’s currently estimating very attenuated returns, and investors should take note.

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Earlier this week I posted about the current controversy around the cyclically-adjusted earnings in the Shiller PE, most notably the contention that the real earnings used in the Shiller PE are lower than they would otherwise be because of two serious earnings recessions.

Another question about the Shiller PE is how accurate it has been historically as a forecasting tool. Asness has backtested the performance of the market from various Shiller PE starting points from 1926 to 2012, finding as follows:

Asness Shiller PEs

Asness observes:

Ten-year forward average returns fall nearly monotonically as starting Shiller P/E’s increase. Also, as starting Shiller P/E’s go up, worst cases get worse and best cases get weaker (best cases remain OK from any decile, so there is generally hope even if it should not triumph over experience!).

The Shiller PE at the time of Asness’s article was 22.2, and the current Shiller PE is 23.4. Both are squarely in the middle of the highlighted row:

If today’s Shiller P/E is 22.2, and your long-term plan calls for a 10% nominal (or with today’s inflation about 7-8% real) return on the stock market, you are basically rooting for the absolute best case in history to play out again, and rooting for something drastically above the average case from these valuations. This could happen. For instance, it could happen if total real earnings growth surprises to the upside by a lot for a very long time. But unless you are comfortable with forecasting that, or some other giant positive surprise, we believe one should give credence to the lower forecasted average returns from history. While market timing might not be the answer, changing your plans — assuming a lower expected market return, perhaps saving more or spending less, or making changes in your portfolio structure — are all worth serious consideration. I think the Shiller P/E is quite meaningful for planning.

Asness examines several other interesting market-level valuation metrics, finding that they tend to support the implications of the currently elevated Shiller PE, noting:

Some outright hucksters still use the trick of comparing current P/E’s based on “forecast” “operating” earnings with historical average P/E’s based on total trailing earnings. In addition, some critics say you can’t compare today to the past because accounting standards have changed, and the long-term past contains things like World Wars and Depressions. While I don’t buy it, this argument applies equally to the one-year P/E which many are still somehow willing to use. Also it’s ironic that the chief argument of the critics, their big gun that I address exhaustively above [from the earlier post], is that the last 10 years are just too disastrous to be meaningful (recall they are actually mildly above average).

He concludes:

While it’s indeed important to remember that no valuation measure is near perfect (I stress that in my initial table), I do believe that the Shiller P/E is a reasonable method, an unbiased method (it’s been 15+ years since it was created so nobody cherry picked it to fit the current period), and a method that is decidedly not “broken” based on today’s inputs. It has very limited use for market timing (certainly on its own) and there is still great variability around its predictions over even decades. But, if you don’t lower your expectations when Shiller P/E’s are high without a good reason — and in my view the critics have not provided a good reason this time around — I think you are making a mistake.

The current Shiller PE of 23.4 implies a real return of less than 0.9 percent per year for the next decade, with a best-case scenario less than 8.3 percent annually, and a worst-case scenario of less than -4.4 percent annually.

Read An Old Friend: The Stock Market’s Shiller P/E (.pdf).

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AQR’s Cliff Asness released in November last year a great piece called, “An Old Friend: The Stock Market’s Shiller P/E (.pdf)” dealing with some of the “current controversy” around the Shiller PE, most notably that the real earnings used in the Shiller PE are lower than they would otherwise be because of two serious earnings recessions: the tail end of the 2000-2002 recession, and the monster 2008 financial crisis.

The Shiller P/E represents what an investor pays for the last 10 years’ average real S&P 500 earnings. The ten-year average is believed to be a more stable measure than a P/E based on a single year of earnings, and therefore more predictive of long-term future stock returns and earnings. Asness notes that the selection of a ten-year average is arbitrary (“You would be hard-pressed to find a theoretical argument favoring it over, say, nine or 12 years”), but believes that it is “reasonable and intuitive.”

Asness asks, “[W]hy do some people dismiss today’s high Shiller P/E, saying it’s not a problem? Why do they forecast much higher long-term real stock returns than implied by the Shiller P/E?”:

They point out that we had two serious earnings recessions recently (though only the tail end of the 2000-2002 event makes it into today’s Shiller P/E), including one that was a doozy following the 2008 financial crisis.

So we have to ask ourselves, is the argument against using the Shiller P/E today right? Are the past 10 years of real earnings too low to be meaningful going forward (meaning the current Shiller P/E is biased too high)?

Asness shows the following chart of a rolling average of 10-year real S&P 500 earnings (a backwards looking 10-year average):

Asness 10 Year Rolling Average

The chart demonstrates that 10-year real earnings used in the Shiller P/E are currently slightly above their long-term trend. At their low after the financial crisis, they fell back to approximately long-term trend. Asness comments:

It has not, in fact, been a bad prior decade for real earnings! The core argument of today’s Shiller P/E critics is just wrong.

While the graph speaks for itself, there is some logic to go with the picture. Critics of the Shiller P/E point to the earnings destruction right after 2008 and ask how we can average in that period and think we have a meaningful number? After all, aren’t we averaging in a once-in-a-hundred-year event? But they usually do not object at all to the very high earnings, for several years, right before the bubble popped in 2008. One view of earnings is that the 2008 event stands alone. It didn’t have to happen, and doesn’t have relevance to the future and should be excluded from our calculations lest it bias us to be sour pusses. That is not my view (granted I’m a bit biased to sour puss in general). Another very different view is that the earnings destruction post 2008 was making up for some earnings that, for several years prior, were “too high”, essentially borrowed from the future. In this case, the post 2008 destruction is valid for inclusion as it’s simply correcting a past wrong. Rather than invalidate the Shiller method, the 2008 earnings destruction following the prior earnings boom is precisely why the CAPE was created! Not surprisingly I fall into this latter camp.

I think the above graph is a TKO. Those who say the Shiller P/E is currently “broken” have been knocked out.

So, according to Cliff Asness, despite the recessions in 2000-2002 and 2008, the real ten-year average of earnings used in the Shiller PE is slightly above its long-term trend.  Note that the current Shiller PE multiple of 23.5 is also about 42 percent above its long-term average of 16.5. Together, these two observations make the market look very expensive indeed.

Read An Old Friend: The Stock Market’s Shiller P/E (.pdf).

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