Dean Foods came out with earning earlier today, and it wasn’t pretty. The company posted a profit of $44.79 million, or 25 cents per share, on revenue of $2.95 billion. That compares to a profit of $64.14 million, or 38 cents per share, on revenue of $2.67 billion during the same period last year. We’re talking a 30% drop in profits. The stock is down roughly 7% as I write this, but that’s not why I’m down (I have no position in the stock at the time of writing). I like looking at consumer staples for messages, and this one is loud a clear – consumers aren’t buying the brand name milk! They’re buying generic. They’re not buying less of it, just buying the cheaper version. That’s the problem, by the way, of selling commodities. When pressured, demand will flow to the lowest priced substitutes.

Anyway, if it was just DF, I’d hear the message, but not give it too much credibility. But Proctor & Gamble (PG) had the same message waiting. Earnings fell 12% from a year ago. Are people really switching out of their premium-brand toothpaste for the store brand generics?

DF already broke down a few months ago, so the market shouldn’t be THAT surprised. Could it go lower? Obviously. But in my mind, PG, which has held up well is even more vulnerable. It hasn’t participated in the recent rally, and its bretheren like JNJ, had a crappy month when the rest of the market was pricing in who-knows-what.

What’s next? Switching to generic drugs? Is there no end to the sacrifice? For all the inflation talk out there, these companies are sending us a message from the consumer. Spending is coming in, savings rates will rise, luxury and “wants” will be pressured, while “needs”-spending will flow to the lowest cost producers, pressuring margins and (I guess – eventually) valuations.

Disclaimer: no position in any stock mentioned. Not investment advice and should be used for informational purposes only.

Abstract:
Existing studies on individual investors’ decision-making often rely on observable socio-demographic variables to proxy for underlying psychological processes that drive investment choices. Doing so implicitly ignores the latent heterogeneity amongst investors in terms of their preferences and beliefs that form the underlying drivers of their behavior. To gain a better understanding of the relations among individual investors’ decision-making, the processes leading to these decisions, and investment performance, this paper analyzes how systematic differences in investors’ investment objectives and strategies impact the portfolios they select and the returns they earn. Based on recent findings from behavioral finance we develop hypotheses which are tested using a combination of transaction and survey data involving a large sample of online brokerage clients. In line with our expectations, we find that investors driven by objectives related to speculation have higher aspirations and turnover, take more risk, judge themselves to be more advanced, and underperform relative to investors driven by the need to build a financial buffer or save for retirement. Somewhat to our surprise, we find that investors who rely on fundamental analysis have higher aspirations and turnover, take more risks, are more overconfident, and outperform investors who rely on technical analysis. Our findings provide support for the behavioral approach to portfolio theory and shed new light on the traditional approach to portfolio theory.

The authors go on to answer the following:

Our investigation into the role of individual differences focuses on the following questions:
How do investors differ from each other in respect to the type of information upon which they
rely to develop their strategies? How do investors differ from each other in respect to their
general investing objectives and risk attitudes? To what extent do differences among investors
impact the composition of their portfolios, trading activity, and investment performance?

For the full paper, click here.

Fascinating reading for anyone interested in behavioral finance and economics, decision making processes, etc. Additionally, the paper cites numerous studies on the topics, which should serve as a valuable resource in and of itself.

Well, any analyst that is using growth estimates for recommendations might want to readjust their assumptions cells to reflect slower growth – unless they have reason to believe the company’s management is above average. But why? We already know that analysts are too bullish. Instead, I do the opposite. Assume management is below average, then determine if the financials STILL make sense. My little margin of safety.

So today we have GDP estimates coming in at 2.4%. I have some more bad news. The number was boosted by residential real estate, which was supported by the tax credit – now gone. Real personal expenditures, while up, were up by less than last quarter – another bad omen for the third quarter. Private inventories grew at a slower rate – inventory adjustment might be gone too.

On luck vs. skill:

There’s a simple and elegant test of whether there is skill in an activity: ask whether you can lose on purpose. If you can’t lose on purpose, or if it’s really hard, luck likely dominates that activity. If it’s easy to lose on purpose, skill is more important.

Applying this to stock investing is an interesting thought process: could you deliberately choose consistently  losing positions? How would you come up with a repeatable process?

More on luck vs. skill (all emphasis is mine):

The two main ways to assess skill and luck are through an analysis of persistence of performance (with streaks being a particularly useful subset of this approach) and its alter ego, reversion to the mean. The research shows evidence for persistence of performance in sports, business, and investing, although the evidence is strongest in sports. Studies of business and investing point to skill in both domains, although the percentage of companies or investors with skill is small.

Reversion to the mean is also clear in each realm. The central insight is that the more the outcomes of an activity rely on luck (or randomness), the more powerful reversion to the mean will be. As important, it is clear that many decision makers do not behave as if they understand reversion to the mean, and predictably make decisions that are, as a consequence, harmful to their long-term outcomes. This is particularly pronounced in the investment industry.

The two-urn model is a useful mental model because it allows for differential skills and
accommodates luck. Even Paul Samuelson, the Nobel-prize winning economist and efficient
markets advocate, allowed for the possibility of investment skill. He wrote, “It is not ordained in heaven, or by the second law of thermodynamics, that a small group of intelligent and informed investors cannot systematically achieve higher mean portfolio gains with lower average variabilities. People differ in their heights, pulchritude, and acidity. Why not their P.Q. or performance quotient?”

An examination of transitivity also provides insights into where outcomes are most predictable. A lack of transitivity marks large swaths of sports, business, and investing. Since it is not always straightforward to pin low transitivity on skill or luck, the main lesson is to recognize that matchups and strategies can matter a great deal.

Transitivity:

Transitivity is a key concept in assessing the outcomes of one-on-one interactions. An activity has transitive properties when competitor A beats competitor B, competitor B beats competitor C, and competitor A beats competitor C. Activities dominated by skill tend to be transitive.

Mauboussin goes on to discuss skill in investing and defining a good investment process (emphasis mine):

The first part requires you to find situations where you have an analytical edge and to allocate the appropriate amount of capital when you do have an edge. The financial community dedicates substantial resources into trying to gain an edge but less time on sizing positions so as to maximize long-term wealth.

At the core of an analytical edge is an ability to systematically distinguish between fundamentals and expectations. Fundamentals are a well thought out distribution of outcomes, and expectations are what is priced into an asset. A powerful metaphor is the racetrack. The fundamentals are how fast a given horse will run and the expectations are the odds on the tote board. As any serious handicapper knows, you make money only by finding a mispricing between the performance of the horse and the odds. There are no “good” or “bad” horses, just correctly or incorrectly priced ones.

Mauboussin goes on to say:

Finding gaps between fundamentals and expectations is only part of the analytical task. The
second challenge is to properly build portfolios to take advantage of the opportunities. There are two common mistakes in sizing positions within a portfolio. One is a failure to adjust position sizes for the attractiveness of the opportunity. In theory, the positions in more attractive risk-adjusted opportunities should be more prominent in the portfolio than less attractive opportunities. In some activities, mathematical formulas can help work out precisely how much you should bet given your perceived edge. While this is difficult in practice for most money managers, the main idea remains: the best ideas deserve the most capital. The weighting in many portfolios fails to distinguish sufficiently between the quality of the ideas.

The other mistake, at the opposite end of the spectrum, is overbetting. In the past, funds that
have seen their edge dwindle have boosted returns through leverage. This led to position sizes that were too large for the opportunity and ultimately disastrous in cases when the trade didn’t perform as expected. . . The analytical part of a good process requires both disciplined unearthing of edge and intelligent position sizing aimed at maximizing long-term risk-adjusted returns.

The second part of skill is psychological, or behavioral. Not everyone has a temperament that is well suited to investing, and skillful investors approach markets with equanimity. One such skilled investor is Seth Klarman, founder and president of the highly-successful Baupost Group, who shared a wonderful line: “Value investing is at its core the marriage of a contrarian streak and a calculator.” A large source of mispricing is when the collective becomes uniformly bullish or bearish, opening large gaps between expectations (price) and fundamentals (value). The first part of Klarman’s line emphasizes the importance of the willingness to go against the crowd. Academic research confirms what most people know: it is easier and more comfortable to be part of the crowd than it is to be alone. Skillful investors heed Ben Graham’s advice: “Have the courage of your knowledge and experience. If you have formed a conclusion from the facts and if you know your judgment is sound, act on it—even though others may hesitate or differ.” However, Klarman correctly observed that it is not enough to be a contrarian because sometimes the consensus is right. The goal is to be a contrarian when it allows you to gain an edge, and the calculator helps you ensure a margin of safety.

Exposure to diverse inputs is crucial to developing sound contrarian views. As an idea takes hold in the investment community, it tends to crowd out alternative points of view. Skillful investors constantly seek input from a variety of sources, primarily through reading. Phil Tetlock, a psychologist who has done groundbreaking work on the decision making of experts, writes that “good judges tend to be . . . eclectic thinkers who are tolerant of counterarguments.” This part of the process also acknowledges, and takes steps to mitigate, the biases that emanate from common heuristics. These biases include overconfidence, anchoring, the confirmation trap, and the curse of knowledge, to name just a few. Overcoming these behavioral pitfalls is not easy, especially at emotional extremes. Techniques that are helpful include expressing views in probabilistic terms, constantly considering base rates, and maintaining a decision-making journal.

The last component of this part is maintaining what I call a “Mr. Market” mindset. To express a proper attitude toward markets, Ben Graham created the idea of Mr. Market, a “very obliging” fellow who offers to sell his shares to you or to buy yours. Mr. Market shows up every day, but is sometimes very optimistic and, fearful that you will snatch his shares at a low price, posts a very high price. On other occasions he is distraught, and seeks to dump his shares at a bargainbasement price.

Graham’s main lesson is that Mr. Market is there to serve you, not to educate you. You cannot let the prices entrance you. Graham writes, “Basically, price fluctuations have only one significant meaning for the true investor. They provide him with an opportunity to buy wisely when prices fall sharply and to sell wisely when they advance a great deal.” This is easy to say but requires a lot of skill to do.

The third part of the process of skill addresses organizational and institutional constraints. The core issue is how to manage agency costs. Costs arise because the agent (the money manager) may have interests that are different than the principal (the investor). For example, mutual fund managers who are paid fees based on assets under management may seek to prioritize asset growth over delivering excess returns. Actions to serve this priority may include heavily marketing products that have been recently successful, launching new products in hot areas, and managing portfolios to look similar to their benchmarks. Charley Ellis made this point when he distinguished between the profession and business of investing. The profession is about managing portfolios so as to maximize long-term returns, while the business is about generating earnings as an investment firm. Naturally, a vibrant business is essential to support the profession. But a focus on the business at the expense of the profession is a problem. Stated differently, you want the investment professionals focused intently on finding opportunities with edge and building sensible portfolios.

Lastly, Mauboussin ends with:

In 1984, Warren Buffett gave a speech at Columbia Business School called “The Superinvestors of Graham-and-Doddsville.” …Common to all of the investors was that they searched “for discrepancies between the value of the business and the price of small pieces of that business.” These investors had a common patriarch, Ben Graham, but went about succeeding in different ways. Still, Buffett suggested he anticipated their success based on “their framework for investment decision making.” While some luck along the way didn’t hurt, their results were all about skill.

For the full article, click here.

I think the end of the research piece didn’t live up to the beginning, as Mauboussin fails to make process-oriented and research driven statements in the last paragraphs, implying instead that the Oracle of Omaha and the disciples of Graham are skilled investors while all others are not. Instead, I wish he had recognized that within each discipline there were both lucky and skilled investors. Putting that aside, Mauboussin gave a nice summary of the challenges of investment management as a profession and business, the behavioral biases within all of us, and the need to focus on process for any investment strategy.

…Google announced Google Apps for Government, a new version of Google’s suite of cloud-based enterprise applications that have been hardened to meet the government’s more stringent security restrictions.Dave Girouard, Google’s President of Enterprise, kicked off the presentation with a few stats: every year, the federal government spends $76 billion on IT expenses. Another $50 billion is spent on IT by state and local governments. Google is looking to help.

Google says that this is the first multi-tenant cloud application suite that has received FISMA certification at a FISMA-Moderate level, which gives it the ability to store and serve sensitive (but not classified) information. Google’s Matthew Glotzbach says this encompasses 80-90% of all government information.

For the link, click here.

First, the fact that the government is ever growing, to the point that Google finds it necessary (and profitable) to develop government-specific IT programs is pretty astonishing (concerning, amazing, cool, scary, etc.). Second, the fact that even the government recognizes the challenges of closed systems is encouraging (again, it’s also quite scary). Lastly, the fact that Google is developing something to such standards is encouraging for the rest of the world as it will ultimately trickle down into our apps. (No position in GOOG – I just think it’s pretty impressive.)

The S&P 500 has done a lot of moving without getting anywhere. It’s about where it was at the beginning of the year, which is roughly where it was in mid 2008 (and by the way, about where it was in 1998 for those keeping longer term track).

Meanwhile, the 10 year yield is roughly where it was in mid-2009:

On the other side of the Pacific, we’ve been looking at the yen for a long time. And yes, I told my readers that I went short in late 2009. Guess what…I’m still short and the yen is pretty much right were I got into my position. Not that I’m proud of a slightly down position, but the reasons to get into the trade haven’t changed and none of the factors that would get me out have been seen. Can it get stronger from here? Of course and I wouldn’t even be surprised.

But all of this talk of yen being a store of value misses the point of the fundamental challenges Japan is facing with no easy way out. Multiple people have recently recommended books like When Money Dies: the Nightmare of The Weimar Hyper-Inflation by Adam Fergusson and Dying of Money: Lessons of the Great German and American Inflations (see for example this recent article HT MacroMan). I’m not opposed to the possibility, but surely Japan is in much greater danger of the hyperinflation mentioned than the US.

But I digress, because the point of this posting was to mention that we have had a lot of noise. I can show other charts, from EEM to different currencies, but the themes are the same. I continue to look to fundamentals as the critical guides for valuation and long term opportunities, and at least in equities, valuations are expensive – so we wait.