Posts Tagged ‘Behavioral investing’

Montier Corporate Profit Margins

Source: “What Goes Up Must Come Down!” James Montier (March 2012)

In his recent piece The Endgame is Forced Liquidation John Hussman eloquently describes the reason why investors need to be wary of structural arguments intended to dispose of indicators with a very reliable cyclical record:

On the temptation to disregard proven indicators

As a side-note, it’s important for investors to be wary of “structural” arguments intended to discard indicators that have very reliable cyclical records. For example, hardly a day goes by that we don’t see an attempt to harness some long-term structural factor, such as increasing globalization of trade, to explain away the spike in profit margins over the past few years – in the hope of proving that these margins will be permanent this time. Some of these arguments are discussed in recent weekly comments. But these factors don’t explain the cyclical fluctuations in profit margins at all, and can’t be used to discard the accounting relationships and decades of evidence that corporate profits have a strong secular and tight cyclical mirror-image relationship with the combined total of government and household savings.

Investors get themselves in trouble when they embrace “new economy” theories not because those new theories can be demonstrated in the data; not because existing approaches fail to fully explain the subsequent historical outcomes; but solely because time-tested approaches suggest uncomfortable outcomes in the present instance.

The same sort of structural second-guessing is evident in the gold market here – a good example of what forced liquidation looks like, as my impression is that leveraged longs have been forced into a fire-sale in recent weeks, creating good values for longer-term investors, but with continued near-term risks.  If we look at the ratio of gold prices to the Philadelphia gold index (XAU), we do believe there are structural factors that affect that ratio (primarily the increasing cost of extracting gold over time). But these don’t explain away or eliminate the strong cyclical relationship between the gold/XAU ratio and subsequent returns on the XAU over the following 3-4 year periods. So while we don’t believe that the record high gold/XAU ratio can be taken entirely at face value, there’s no question that it is elevated even on a cyclical basis (that is, even allowing for a gradual structural increase over time), and there’s no question in the data that cyclically elevated gold/XAU ratios have been associated with strong subsequent gains in the XAU index over a 3-4 year period on average, though certainly not without risk or volatility.

As a final example, some analysts (such as the Dow 36,000 authors) have argued that the proper risk premium on stocks, relative to Treasury securities, should be zero. This line of argument was used in 2000 to suggest that stocks were still cheap despite high apparent valuations. But this “secular” argument for high valuations ultimately did not weaken the long-term evidence and tight cyclical relationship between valuations and subsequent market returns. Despite all the new economy arguments about productivity growth,  the internet, globalization, the great moderation, and the outdated relevance of risk premiums, stocks still went on to lose half their value over the next two years, and to produce negative returns over the decade that followed.

The bottom line is that it becomes very tempting – both in speculative markets and fearful ones – to discard well-proven indicators as meaningless by arguing that some “structural” change in the market or the economy makes things different this time. True, those arguments can sometimes be used to explain very long-term changes in the level of an indicator. But even then, new economy arguments are typically ineffective at explaining away the informative cyclical variations in good indicators. Be particularly hesitant about ignoring indicators whose cyclical variations have been effective even in recent data, as is true of the ability of time-tested valuation approaches to explain subsequent 10-year market returns even during the period since the late-1990’s, and the ability of government and household savings to tightly explain cyclical swings in profit margins and subsequent profit growth, even in the most recent economic cycle.

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Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

h/t Joe


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Further to my point that if your valuation models use forward estimates rather than twelve-month trailing data, you’re doing it wrong, here are the results of our Quantitative Value backtest on the use of consensus Institutional Brokers’ Estimate System (I/B/E/S) earnings forecasts of EPS for the fiscal year (available 1982 through 2010) for individual stock selection:

We analyze the compound annual growth rates of each price ratio over the 1964 to 2011 period for market capitalization–weighted decile portfolios.

The forward earnings estimate is the worst performed metric by a wide margin. The performance of the forward earnings estimate is uniformly poor, earning a compound annual growth rate of just 8.63 percent on average and underperforming the Standard & Poor’s (S&P) 500 by almost 1 percent per year. Investors are wise to shy away from analyst forward earnings estimates when making investment decisions.

We focus our analysis on historical valuation metrics in Quantitative Value and leave the forward earnings estimates to the promoters on Wall Street.

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Greenbackd has been quiet over the last few days while I finished “Simple But Not Easy,” my latest white paper for Eyquem (embedded below). If you want to receive similar future missives, shoot me an email at greenbackd at gmail dot com. Thoughts, criticisms, and questions are all welcome too.

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Michael Mauboussin appeared Friday on Consuelo Mack’s WealthTrack to discuss several of the ideas in his excellent book, Think Twice. Particularly compelling is his story about Triple Crown prospect Big Brown and the advantage of the “outside view” – the statistical one – over the “inside view” – the specific, anecdotal one (excerpted from the book):

June 7, 2008 was a steamy day in New York, but that didn’t stop fans from stuffing the seats at Belmont Park to see Big Brown’s bid for horseracing’s pinnacle, the Triple Crown. The undefeated colt had been impressive. He won the first leg of the Triple Crown, the Kentucky Derby, by 4 ¾ lengths and cruised to a 5 ¼-length win in the second leg, the Preakness.

Oozing with confidence, Big Brown’s trainer, Rick Dutrow, suggested that it was a “foregone conclusion” that his horse would take the prize. Dutrow was emboldened by the horse’s performance, demeanor, and even the good “karma” in the barn. Despite the fact that no horse had won the Triple Crown in over 30 years, the handicappers shared Dutrow’s enthusiasm, putting 3-to-10 odds—almost a 77 percent probability—on his winning.

The fans came out to see Big Brown make history. And make history he did—it just wasn’t what everyone expected. Big Brown was the first Triple Crown contender to finish dead last.

The story of Big Brown is a good example of a common mistake in decision making: psychologists call it using the “inside” instead of the “outside” view.

The inside view considers a problem by focusing on the specific task and by using information that is close at hand. It’s the natural way our minds work. The outside view, by contrast, asks if there are similar situations that can provide a statistical basis for making a decision. The outside view wants to know if others have faced comparable problems, and if so, what happened. It’s an unnatural way to think because it forces people to set aside the information they have gathered.

Dutrow and others were bullish on Big Brown given what they had seen. But the outside view demands to know what happened to horses that had been in Big Brown’s position previously. It turns out that 11 of the 29 had succeeded in their Triple Crown bid in the prior 130 years, about a 40 percent success rate. But scratching the surface of the data revealed an important dichotomy. Before 1950, 8 of the 9 horses that had tried to win the Triple Crown did so. But since 1950, only 3 of 20 succeeded, a measly 15 percent success rate. Further, when compared to the other six recent Triple Crown aspirants, Big Brown was by far the slowest. A careful review of the outside view suggested that Big Brown’s odds were a lot longer than what the tote board suggested. A favorite to win the race? Yes. A better than three-in-four chance? Bad bet.

Mauboussin on WealthTrack:

Hat Tip Abnormal Returns.



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Zero Hedge has a great post on the quarterly Goldman Hedge Fund Trend Monitor. The most interesting aspect of the piece is the relative performance of stocks with the highest concentration of hedge fund holders against the performance of stocks with the lowest concentration of hedge fund holders:

We define “concentration” as the share of market capitalization owned in aggregate by hedge funds. The strategy of buying the 20 most concentrated stocks has a strong track record over more than eight years. Since 2001, the strategy has outperformed the market by an average of 312 bp per quarter (not annualized). The back test suggests that this strategy works in an upward trending market but tends to perform poorly during choppy or flat markets. The stocks in the basket tend to be mid-caps (at the lower end of the S&P 500 capitalization distribution), which have outperformed large-caps from 2004 to 2007, contributing to the attractive back-test results. The baskets are not sector neutral versus the S&P 500.

As you might have guessed, the “least concentrated” basket has outperformed the “most concentrated” portfolio since 2007:

The stocks with the “most concentrated” hedge fund ownership have outperformed the S&P 500 in 2010 ytd by 191 bp (+1.1% vs. -0.8%). The “most concentrated” stocks underperformed steadily for most of 2007 and 2008, but significantly outperformed in 2009. Our “most concentrated” basket outperformed the S&P 500 by 237 bp in 1Q 2010 (+7.7% vs. +5.4%) but lagged by 303 bp in 2Q 2010 (-14.5% vs. -11.4%).

Our “least concentrated” basket has outperformed the S&P 500 in 2010 ytd by 693 bp (+6.1% vs. -0.8%). The “least concentrated” basket outpaced the market by 50 bp in 1Q 2010 (+5.9% vs. +5.4%) and by 440 bp in 2Q (-7.0% vs. -11.4%).

So which stocks are currently in the “least” and “most” concentrated baskets:

Read the article.

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Oh dear (Daily Reckoning via Guru Focus):

04/21/10 Gaithersburg, Maryland – Ken Heebner’s CGM Focus Fund was the best US stock fund of the past decade. It rose 18% a year, beating its nearest rival by more than three percentage points. Yet according to research by Morningstar, the typical investor in the fund lost 11% annually! How can that happen?

It happened because investors tended to take money out after a bad stretch and put it back in after a strong run. They sold low and bought high. Stories like this blow me away. Incredibly, these investors owned the best fund you could own over the last 10 years – and still managed to lose money.

Psychologically, it’s hard to do the right thing in investing, which often requires you to buy what has not done well of late so that you will do well in the future. We’re hard-wired to do the opposite.
I recently read James Montier’s Value Investing: Tools and Techniques for Intelligent Investment. It’s a meaty book that compiles a lot of research. Much of it shows how we are our own worst enemy.

One of my favorite chapters is called “Confused Contrarians and Dark Days for Deep Value.” Put simply, the main idea is that you can’t expect to outperform as an investor allthe time. In fact, the best investors often underperform over short periods of time. Montier cites research by the Brandes Institute that shows how, in any three-year period, the best investors find themselves among the worst performers about 40% of the time!

See the rest of the article here.

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