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Posts Tagged ‘Tobin’s q’

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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In 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.”

In his 2011 and 2012 papers, Spitznagel describes the equity q ratio as the “most robust aggregate overvaluation metric, which isolates the key drivers of valuation.” It is also useful in identifying “susceptibility to shifts from any extreme consensus,” which is important because “such shifts of extreme consensus are naturally among the predominant mechanics of stock market crashes.”

He observes that the aggregate US stock market has suffered very few sizeable annual losses (which Spitznagel defines as “20% or more”). Extreme stock market losses are by definition “tail events” as Figure 1 demonstrates.

Figure 1 shows how infrequently large drawdowns occur. However, when the equity q ratio is high, large losses are “no longer a tail event, but become an expected event.”

Figure 3 shows the magnitude of potential losses at various equity q ratios. In the last bucket (equity q > 0.9), the expected (median) drawdown is 20 percent, with a 1/5 chance of a greater than 40 percent correction in the S&P500 within the next few years. Spitznagel describes Figure 3 as “[t]he best picture I have ever seen depicting the endogenous risk control to be had from Benjamin Graham’s margin of safety principle (which insists on cheapness to conservative fundamental assumptions in one’s equity exposures, and thus provides added protection against errors in those assumptions).

Equity q ratios over 0.9 lead to some very ugly results. So where are we now? I’ll discuss it later this week.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

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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) examine the “clear and rigorous evidence of a direct relationship between 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 a 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.”

Today I examine the calculation of the equity q ratio and estimated market-level returns. Later this week I’ll take a look at the likelihood of massive drawdowns at elevated q ratios.

Spitznagel is perhaps best known to we folk who do not trade volatility as Nassim Taleb’s chief trader at Taleb’s Empirica. Here’s Malcolm Gladwell describing Spitznagel in his New Yorker article Blowing Up:

Taleb was up at a whiteboard by the door, his marker squeaking furiously as he scribbled possible solutions. Spitznagel and Pallop looked on intently. Spitznagel is blond and from the Midwest and does yoga: in contrast to Taleb, he exudes a certain laconic levelheadedness. In a bar, Taleb would pick a fight. Spitznagel would break it up.

The three argued back and forth about the solution. It appeared that Taleb might be wrong, but before the matter could be resolved the markets opened. Taleb returned to his desk and began to bicker with Spitznagel about what exactly would be put on the company boom box. Spitznagel plays the piano and the French horn and has appointed himself the Empirica d.j. He wanted to play Mahler, and Taleb does not like Mahler. “Mahler is not good for volatility,” Taleb complained. “Bach is good. St. Matthew’s Passion!” Taleb gestured toward Spitznagel, who was wearing a gray woollen turtleneck. “Look at him. He wants to be like von Karajan, like someone who wants to live in a castle. Technically superior to the rest of us. No chitchatting. Top skier. That’s Mark!”

In his 2011 and 2012 papers, Spitznagel describes the equity q ratio as the “most robust aggregate overvaluation metric, which isolates the key drivers of valuation.”

The “equity” q ratio is similar to Tobin’s q ratio, which is the ratio of enterprise value (market capitalization plus debt) to corporate assets or invested capital. With no debt, Tobin’s q is market capitalization over total assets. The equity q ratio (or “Q ratio”, as Spitznagel describes it in his papers) is market capitalization over shareholders’ equity. Shareholders equity is total assets less total debt. With no debt, shareholders’ equity is equal to invested capital. The equity q ratio is a market level price-to-shareholders’ equity ratio, where shareholders’ equity is calculated using assets valued at replacement cost.

Spitznagel examines the long-run tendency of the equity q ratio to mean revert, noting:

[T]he arithmetic mean to which it has been seemingly attracted is, surprisingly, not 1, but rather about .7. This, then, would be the appropriate “fair value” for use in gauging over- or under-valuation (and the March 2009 low actually came very close to this mean). 

Why doesn’t equity q mean revert to 1?

It would have been expected for this Q ratio level to be where ROIC = WACC, that is, where the price equals the net worth of the businesses, Q=1. Ostensibly, the current value of invested capital (i.e., the replacement cost of company assets) has been systematically overstated (and its depreciation understated). This is evident in the historical aggregate ROIC as computed from Flow of Funds data vis-à-vis the actual known aggregate ROIC (and adjusting thereto is consistent with Q ≈ 1).

Is the equity q ratio predictive?

If the Q ratio … is in fact the most robust and rigorous metric of aggregate stock market valuation and represents all there is to know about aggregate stock market valuation, shouldn’t it be the case that it has empirical validity as well? That is, shouldn’t it tell you something ex ante about subsequent aggregate equity returns? (The caveat of course, from Williams, is that, since “the public is more emotional than logical, it is foolish to expect a relentless convergence of market price toward investment value.“)

Just a casual perusal of Figure 2 [above] (and a basic memory of what U.S. stocks did during this period) tells the story quite well, but let’s put some numbers on it.

Figure 3 from the 2011 paper shows Spitznagel’s backtest of the relationship between mean one-year S&P 500 total returns and the starting level of the equity q ratio going back to 1901:

Spitznagel 1

Spitzagel notes:

When stocks are overvalued on aggregate, as identified by the Q ratio, their returns have been lower (with 99% confidence) than when they are less overvalued, not to mention undervalued. (Whenever one hears a reference to historical aggregate stock returns to support forecasts of future returns, it is good to recall that not all historical returns were created equal.)

Spitznagel’s white papers are important because they demonstrate that, like the Shiller PE and Buffett’s total market capitalization-to-gross national product measure, the equity q ratio is a highly predictive measure of subsequent stock market performance. Spitznagel is a specialist in tail risk, and so the most intriguing part of Spitznagel’s papers is his demonstration of the utility of the equity q ratio in identifying “susceptibility to shifts from any extreme consensus” because “such shifts of extreme consensus are naturally among the predominant mechanics of stock market crashes.” I’ll continue with the rest of the paper later this week.

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Smithers & Co. has updated its calculations for US market valuations according to cyclically-adjusted price earnings (CAPE) and Tobin’s q. CAPE is the Graham PE10, of which I am so fond. Tobin’s q compares the market value and replacement value of the same physical assets. Here’s Smithers & Co.’s chart:

Says Smithers & Co. of the market:

Non-financial companies, including both quoted and unquoted, were 62% overvalued according to q at 31st March 2010, when the S&P 500 index was 1169. Adjusting for the subsequent decline to 1087(10th June, 2010), the overvaluation had fallen to 50%. Revisions to data had little impact on q, with downward revision to net worth for Q4 2009 of 2.9% being offset by a downward revision to the market value of non-financial equities of 2.1%. Net worth for Q1 2010 fell slightly as equity buy-backs exceeded profit retentions.

The listed companies in the S&P 500 index, which include financials, were 58% overvalued at 31st March 2010, according to our calculations for CAPE, based on the data from Professor Robert Shiller’s website. Adjusting for the subsequent decline to 1087 (10th June, 2010), the overvaluation had fallen 46%. (It should be noted that we use geometric rather than arithmetic means in our calculations.)

H/T ZeroHedge.

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