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Posts Tagged ‘Warren Buffett’

Here’s the updated St Louis Fed’s FRED on Warren Buffett’s favored market measure, total market capitalization-to-GNP:

FRED Graph

The Q1 2013 ratio – the most recent point – is 110 percent.

According to the FRED data, the Q1 2000 TTM/GNP peak ratio was 158 percent, and the Q3 2007 TTM/GNP peak was 114 percent. The average for the full period – Q3 1949 to Q3 2012 – is 69 percent. The last time the market traded at a below-average ratio was Q1 2009.

Here’s the log version:

FRED Graph

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Warren Buffett’s favored market valuation metric, market capitalization-to-gross national product, has passed an unwelcome milestone: the 2007 valuation peak, according to GuruFocus:

TMTGNP 2007

The index topped out at 110.7 percent in 2007, and presently stands at 111.7 percent. From GuruFocus:

As of today, the Total Market Index is at $ 17624.4 billion, which is about 111.7% of the last reported GDP. The US stock market is positioned for an average annualized return of 2.2%, estimated from the historical valuations of the stock market. This includes the returns from the dividends, currently yielding at 2%.

I’ve seen several arguments for why this time is different, and why it’s not a bubble. I don’t buy it. When we see clear skies, that’s all we can imagine, and so we extrapolate it over the horizon. From Seth Klarman’s latest:

Investing, when it looks the easiest, is at its hardest. When just about everyone heavily invested is doing well, it is hard for others to resist jumping in. But a market relentlessly rising in the face of challenging fundamentals–recession in Europe and Japan, slowdown in China, fiscal stalemate and high unemployment in the U.S.– is the riskiest environment of all.

[O]nly a small number of investors maintain the fortitude and client confidence to pursue long-term investment success even at the price of short-term underperformance. Most investors feel the hefty weight of short-term performance expectations, forcing them to take up marginal or highly speculative investments that we shun. When markets are rising, such investments may perform well, which means that our unwavering patience and discipline sometimes impairs our results and makes us appear overly cautious. The payoff from a risk-averse, long-term orientation is–just that–long term. It is measurable only over the span of many years, over one or more market cycles.

Our willingness to invest amidst failing markets is the best way we know to build positions at great prices, but this strategy, too, can cause short-term underperformance. Buying as prices are falling can look stupid until sellers are exhausted and buyers who held back cannot effectively deploy capital except at much higher prices. Our resolve in holding cash balances–sometimes very large ones–absent compelling opportunity is another potential performance drag.

For more on market value-to-GNP see my earlier posts Warren Buffett Talks… Total Market Value-To-Gross National ProductWarren Buffett and John Hussman On The Stock MarketFRED on Buffett’s favored market measure: Total Market Value-to-GNPThe Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models.

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Chris Turner has a guest post at Doug Short’s Advisor Perspectives called When Warren Buffett Talks … People Listen examining Warren Buffett’s favored market valuation metric: Market Value divided by Gross National Product. (I’ve also examined market value-to-GNP several times. See Warren Buffett and John Hussman On The Stock MarketFRED on Buffett’s favored market measure: Total Market Value-to-GNPThe Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models)

Here Chris looks at the metric using the CPI deflator on both the numerator — market value — and the denominator — Gross National Product.

Here Chris calculates two fair values for the S&P 500. The blue line shows the historical mean and the green line shows Buffett’s 80 percent value estimate:

Chris comments:

Readers can see from the chart that based on both Buffett’s rule and the historical mean, the S&P would be trading much lower from present levels. The S&P would be sub 1000 based on the historical mean and around 1150 based on the 80% Buffett rule.

Read When Warren Buffett Talks … People Listen.

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Ratio of Corporate Profits-to-GDP and Returns (1947 to Present)

Source: Hussman Weekly Comment “Taking Distortion at Face Value,” (April 8, 2013)

Warren Buffett, 1999

[F]rom 1951 on, the percentage settled down pretty much to a 4% to 6.5% range.

In my opinion, you have to be wildly optimistic to believe that corporate profits as a percent of GDP can, for any sustained period, hold much above 6%. One thing keeping the percentage down will be competition, which is alive and well.

– Warren Buffett, Mr. Buffett on the Stock Market (November 1999)

Jeremy Grantham, 2006

Profit margins are probably the most mean-reverting series in finance, and if profit margins do not mean-revert, then something has gone badly wrong with capitalism. If high profits do not attract competition, there is something wrong with the system and it is not functioning properly.

– Jeremy Grantham, Barron’s (c. 2006), via Katsenelson, The Little Book of Sideways Markets.

John Hussman, 2013

In general, elevated profit margins are associated with weak profit growth over the following 4-year period. The historical norm for corporate profits is about 6% of GDP. The present level is about 70% above that, and can be expected to be followed by a contraction in corporate profits over the coming 4-year period, at a roughly 12% annual rate. This will be a surprise. It should not be a surprise.

– John Hussman, Two Myths and a Legend (March 11, 2013)

h/t Butler|Philbrick|Gordillo and Associates

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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 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.

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Update: Now with a log version.

Here’s the St Louis Fed’s FRED on Warren Buffett’s favored market measure, total market capitalization-to-GNP.

FRED Graph

According to the FRED data, the Q1 2000 TTM/GNP peak ratio was 158 percent, and the Q3 2007 TTM/GNP peak was 114 percent. The average for the full period – Q3 1949 to Q3 2012 – is 69 percent. The last time the market traded at a below-average ratio was Q1 2009.

Compare this to the Q3 2012 ratio – unfortunately the most recent point – at 100 percent. If we assume ~1 percent GNP growth in Q4 2012 and Q1 2013 (the long-run CAGR is about 1 percent per quarter), and the market has rallied around 10 percent, the ratio now stands at ~107 percent, which is around 40 percent over the long-run mean (since 1949). This level of overvaluation accords with the level of the Shiller PE and Tobin’s q at 40 and 44 percent respectively.

Here’s the log version, per commenter Jim’s request:

FRED Graph

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My piece on S&P 500 forward earnings estimates and the overvaluation of the market generated a number of heated emails and comments. I didn’t know that it was so controversial that the market is expensive. I’m not saying that the market can’t continue to go up (I’ve got no idea what the market is going to do). My point is that there are a variety of highly predictive, methodologically distinct measures of market-level valuation (I used the Shiller PE and Tobin’s q, but GNP or GDP-to-total market capitalization below work equally as well) that point to overvaluation.

The popular price-to-forward operating earnings measure does not point to overvaluation, but is flawed because forward operating earnings are systematically too optimistic. It’s simply not predictive, mostly because it fails to take into account the highly mean reverting nature of profit margins. Here’s John Hussman from a week ago in his piece Investment, Speculation, Valuation, and Tinker Bell (March 18, 2013):

From an investment standpoint, it’s important to recognize that virtually every assertion you hear that “stocks are reasonably valued” is an assertion that rests on the use of a single year of earnings as a proxy for the entire long-term stream of future corporate profitability.  This is usually based on Wall Street analyst estimates of year-ahead “forward operating earnings.” The difficulty here is that current profit margins are 70% above the long-term norm.

Most important, the level of corporate profits as a share of GDP is strongly and inversely correlated with the growth in corporate profits over the following 3-4 year period.

While I believe the Shiller PE and Tobin’s to be predictive, there are other measures of market valuation that perform comparably. Warren Buffett’s favored measure is “the market value of all publicly traded securities as a percentage of the country’s business–that is, as a percentage of GNP.” Here he is in a 2001 interview with Fortune’s Carol Loomis:

[T]he market value of all publicly traded securities as a percentage of the country’s business–that is, as a percentage of GNP… has certain limitations in telling you what you need to know. Still, it is probably the best single measure of where valuations stand at any given moment. And as you can see, nearly two years ago the ratio rose to an unprecedented level. That should have been a very strong warning signal.

A quick refresher: GDP is “the total market value of goods and services produced within the borders of a country.” GNP is “is the total market value of goods and services produced by the residents of a country, even if they’re living abroad. So if a U.S. resident earns money from an investment overseas, that value would be included in GNP (but not GDP).” While the distinction between the two is  important because American firms are increasing the amount of business they do internationally, the actual difference between GNP and GDP is minimal as this chart from the St Louis Fed demonstrates:

FRED Graph

GDP in Q4 2012 stood at $15,851.2 billion. GNP at Q3 2012 (the last data point available) stood at $16,054.2 billion. For our present purposes, one substitutes equally as well for the other.

For the market value of all publicly traded securities, we can use The Wilshire 5000 Total Market Index. The index stood Friday at $16,461.52 billion. The following chart updates in real time:

Chart

Here are the calculations:

  • The current ratio of total market capitalization to GNP is 16,461.52 / 16,054.2 or 103 percent.
  • The current ratio of total market capitalization to GDP is 16,461.52 / 15,851.2 or 104 percent.

You can undertake these calculations yourself, or you can go to Gurufocus, which has a series of handy charts demonstrating the relationship of GDP to Wilshire total market capitalization:

Chart 1. Total Market Cap and GDP

GDP WIlshire Total Market

Chart 1 demonstrates that total market capitalization has now exceeded GDP (note the other two auspicious peaks of total market capitalization over GDP in 1999 and 2007).

Chart 2. Ratio of Total Market Capitalization and GDP

Total Market Cap GDP Ratio

Chart 2 shows that the current ratio is well below the ratio achieved in the last two peaks (1999 and 2007), but well above the 1982 stock market low preceding the last secular bull market.

But, so what? Is the ratio of total market capitalization to GDP predictive?

In this week’s The Hook (March 25, 2013) Hussman discusses his use of market value of U.S. equities relative to GDP, which he says has a 90% correlation with subsequent 10-year total returns on the S&P 500:

Notably, the market value of U.S. equities relative to GDP – though not as elevated as at the 2000 bubble top – is not depressed by any means. On the contrary, since the 1940’s, the ratio of equity market value to GDP has demonstrated a 90% correlation with subsequent 10-year total returns on the S&P 500 (see Investment, Speculation, Valuation, and Tinker Bell), and the present level is associated with projected annual total returns on the S&P 500 of just over 3% annually.

Here’s Gurufocus’s comparison of predicted and actual returns assuming three different ratios (TMC/GDP = 40 percent, 80 percent, and 120 percent) at the terminal date:

Chart 3. Predicted and Actual Returns

Predicted and Actual Returns GDP Total Market Cap

Chart 3 shows the outcome of three terminal ratios of total market capitalization to GDP. Consider the likelihood of these three scenarios:

  1. A terminal ratio of 120 percent (equivalent to the 1999 to 2001 peak) leads to annualized nominal returns of 8.1 percent over the next 10 years.
  2. A terminal ratio of 80 percent (the long-run average) leads to annualized nominal returns of 3 percent over the next 10 years.
  3. A terminal ratio of 40 percent (approximating the 1982 low of 35 percent) leads to annualized nominal returns of -5 percent over the next 10 years.

For mine, 1 seems less likely than scenarios 2 or 3, with the long run mean (scenario 2) the most likely. For his part, Buffett opines:

For me, the message of that chart is this: If the percentage relationship falls to the 70% or 80% area, buying stocks is likely to work very well for you. If the ratio approaches 200%–as it did in 1999 and a part of 2000–you are playing with fire.

Gurufocus’s 80-percent-long-run-average calculation agrees with Hussman’s calculation of average annualized market return of 3%:

As of today, the Total Market Index is at $ 16461.5 billion, which is about 104.3% of the last reported GDP. The US stock market is positioned for an average annualized return of 3%, estimated from the historical valuations of the stock market. This includes the returns from the dividends, currently yielding at 2%.

Here’s Buffett again:

The tour we’ve taken through the last century proves that market irrationality of an extreme kind periodically erupts–and compellingly suggests that investors wanting to do well had better learn how to deal with the next outbreak. What’s needed is an antidote, and in my opinion that’s quantification. If you quantify, you won’t necessarily rise to brilliance, but neither will you sink into craziness.

On a macro basis, quantification doesn’t have to be complicated at all. Below is a chart, starting almost 80 years ago and really quite fundamental in what it says. The chart shows the market value of all publicly traded securities as a percentage of the country’s business–that is, as a percentage of GNP. The ratio has certain limitations in telling you what you need to know. Still, it is probably the best single measure of where valuations stand at any given moment. And as you can see, nearly two years ago the ratio rose to an unprecedented level. That should have been a very strong warning signal.

The current ratios of total market capitalization to GNP and GDP should be very strong warning signals. Further, that they imply similar returns to the Shiller PE and Tobin’s q, suggests that they are robust.

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This letter from Howard Buffett, the highly libertarian “Old Right” United States Representative father of Warren, to anarcho-capitalist historian and economist Murray Rothbard, if real, is incredible. Buffett the Elder wrote to Rothbard that he “read that Rothbard had written a book on ‘The Panic of 1819‘” and wanted to know where he could buy a copy for his son “who is a particularly avid reader of books about panics and similar phenomena.”

Here is the letter:

Howard-Buffett-715x1024

The timing of the letter – July 31, 1962 – is interesting. The first “flash crash” occurred in May 1962, and was at the time the worst crash since 1929. Time LIFE described the 1962 “flash crash” thus:

The signs, like the rumblings of an Alpine ice pack at the time of thaw, had been heard. The glacial heights of the stock boom suddenly began to melt in a thaw of sell-off. More and more stocks went up for sale, with fewer and fewer takers at the asking price. Then suddenly, around lunchtime on Monday, May 28, the sell-off swelled to an avalanche. In one frenzied day in brokerage houses and stock exchanges across the U.S., stock values — glamor and blue-chip alike — took their sharpest drop since 1929.

Memory of the great crash, and the depression that followed, has haunted America’s subconscious. Now, after all these years, was that nightmare to happen again?

The article continues that, “although the Dow Jones Industrial Average fell almost 6 percent on that one vertiginous Monday and the market was anemic for a year afterwards, the markets as a whole, at home and abroad, did bounce back.” Good to know.

h/t: Mises.org

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Robert Novy-Marx, whose The Other Side of Value paper we quoted from extensively in Quantitative Value, has produced another ripping paper called The Quality Dimension of Value Investing (.pdf). Novy-Marx argues that  value investment strategies that seek high quality stocks are “nearly as profitable as traditional value strategies based on price signals alone.”

Accounting for both dimensions by trading on combined quality and price signals yields dramatic performance improvements over traditional value strategies. Accounting for quality also yields significant performance improvements for investors trading momentum as well as value.

Novy-Marx’s The Other Side of Value paper showed that a simple quality metric, gross profits-to-assets, has roughly as much power predicting the relative performance of different stocks as tried-and-true value measures like book-to-price.

Buying profitable firms and selling unprofitable firms, where profitability is measured by the difference between a firm’s total revenues and the costs of the goods or services it sells, yields a significant gross profitability premium.

Most intriguingly, Novy-Marx finds that “the signal in gross profits-to-assets is negatively correlated with that in valuation ratios.”

High quality firms tend to trade at premium prices, so value strategies that trade on quality signals (i.e., quality strategies) hold very different stocks than value strategies that trade on price signals. Quality strategies tilt towards what would traditionally be considered growth stocks. This makes quality strategies particularly attractive to traditional value investors, because quality strategies, in addition to delivering significant returns, provide a hedge to value exposures.

Novy-Marx argues that investors can “directly combine the quality and value signals and, in line with Graham’s basic vision, only buy high quality stocks at bargain prices. By trading on a single joint profitability and value signal, an investor can effectively capture the entirety of both premiums.

Performance of Quality, Value and Joint Strategies

(Click to enlarge).

Novy-Marx 2.1

Figure 1 shows the performance of a dollar invested in mid-1963 in T-bills, the market, and strategies that trade on the quality signal, the value signal, and the joint quality and value signal. The top panel shows long/short strategies, which are levered each month to run at market volatility (i.e., an expected ex ante volatility of 16%, with leverage based on the observed volatility of the unlevered strategy over the preceding 60 months). By the end of 2011 a dollar invested in T-bills in 1963 would have grown to $12.31. A dollar invested in the market would have grown to $84.77. A dollar invested in the quality and value strategies would have grown to $94.04 and $35.12, respectively. A dollar invested in the strategy that traded on the joint quality and value signal would have grown to more than $2,131.

The bottom panel shows the performance of the long-only strategies. While a dollar invested in the market would have grown to more than $80, a dollar invested in profitable large cap stocks would have grown to $241, a dollar invested in cheap large cap stocks would have grown to $332, and a dollar invested in cheap, profitable large cap stocks would have grown to $572.

Drawdowns to Quality, Value, and Joint strategies

(Click to enlarge).

Novy Marx 2.2

Figure 2 shows the drawdowns of the long/short strategies (top panel) and the worst cumulative under performance of the long-only strategies relative to the market, i.e., the drawdowns on the long-only strategies’ active returns (bottom panel). The top panel shows that the worst drawdowns experienced over the period by the long/short strategies run at market volatility were similar to market’s worst drawdown over the period. The joint quality and value strategy had, however, the smallest drawdowns of all the strategies considered. Its worst drawdown (48.7% in 2000) compares favorably to the worst drawdowns experienced by the market (51.6% in 2008-9, not shown), the traditional value strategy (down 59.5% by 2000), and the pure quality strategy (51.4% to 1977). Similar results hold for the worst five or ten drawdowns (average losses of 35.5% versus 41.1%, 38.9%, and 35.6% for the worst five drawdowns, and average losses of 25.8% versus 28.5%, 28.7%, and 26.5% for the worst ten drawdowns).

The bottom panel shows even more dramatic results for the long-only strategies active returns. Value stocks underperformed the market by 44% through the tech run-up over the second half of the ‘90s. Quality stocks lagged behind the market through much of the ‘70s, falling 28.1% behind by the end of the decade. Cheap, profitable stocks never lagged the market by more than 15.8%. Periods over which these stocks underperformed also tended to be followed quickly by periods of strong outperformance, yielding transient drawdowns that were sharply reversed.

Importantly, the signal in gross profitability is “extremely persistent,” and works well in the large cap universe.

Profitability strategies thus have low turnover, and can be implemented using liquid stocks with large capacities.

Novy-Marx’s basic message is that investors, in general but especially traditional value investors, leave money on the table when they ignore the quality dimension of value.

Read The Quality Dimension of Value Investing (.pdf).

Tomorrow, I show in an extract from Quantitative Value how we independently tested gross-profits-on-total-assets and found it to be highly predictive.

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