Expert forecasters were, on balance, deeply unimpressive. But Tetlock found some were better than others. What separated the forecasters was how they thought. The experts who knew a little about a lot—the diverse thinkers—did better than the experts who knew one big thing.

Source:   More Than You Know

Two sources in particular have inspired my thinking on diversity. The first is the mental-models approach to investing, tirelessly advocated by Berkshire Hathaway’s Charlie Munger. The second is the Santa Fe Institute (SFI), a New Mexico-based research community dedicated to multidisciplinary collaboration in pursuit of themes in the natural and social sciences.

Source:   More Than You Know

Charlie Munger’s long record of success is an extraordinary testament to the multidisciplinary approach. For Munger, a mental model is a tool—a framework that helps you understand the problem you face. He argues for constructing a latticework of models so you can effectively solve as many problems as possible. The idea is to fit a model to the problem and not, in his words, to “torture reality” to fit your model.

Source:   More Than You Know

First, in any probabilistic field—investing, handicapping, or gambling—you’re better off focusing on the decision-making process than on the short-term outcome.

Source:   More Than You Know

That leads to the second theme, the importance of taking a long-term perspective. You simply cannot judge results in a probabilistic system over the short term because there is way too much randomness.

Source:   More Than You Know

The sad truth is that incentives have diluted the importance of investment philosophy in recent decades. While well intentioned and hard working, corporate executives and money managers too frequently prioritize growing the business over delivering superior results for shareholders. Increasingly, hired managers get paid to play, not to win.

Source:   More Than You Know

...investors often make the critical mistake of assuming that good outcomes are the result of a good process and that bad outcomes imply a bad process. In contrast, the best long-term performers in any probabilistic field—such as investing, sports-team management, and pari-mutuel betting—all emphasize process over outcome.

Source:   More Than You Know

Probabilities alone are insufficient when payoffs are skewed.

Source:   More Than You Know

Four attributes generally set this group apart from the majority of active equity mutual fund managers: 1) [Low] Portfolio turnover. 2) [High] Portfolio Concentration. 3) Investment Style - [intrinsic-value investment approach]. 4) Geographical Location - [being away from money-centers like New York or Boston].

Source:   More Than You Know

In the real world there is no “easy way” to assure a financial profit. At least, it is gratifying to rationalize that we would rather lose intelligently than win ignorantly. —Richard A. Epstein, The Theory of Gambling and Statistical Logic.

Source:   More Than You Know

Constantly thinking in expected-value terms requires discipline and is somewhat unnatural. But the leading thinkers and practitioners from somewhat varied fields have converged on the same formula: focus not on the frequency of correctness but on the magnitude of correctness.

Source:   More Than You Know

Economists use the CAPM to test market efficiency, while the CAPM assumes market efficiency. In the words of noted financial economist Richard Roll, any test of CAPM is “really a joint test of CAPM and market efficiency.” Christensen et al. suggest that a number of central concepts in economics should be properly labeled as “constructs” rather than “theories” precisely because they cannot be directly falsified.

Source:   More Than You Know

Changing the nature of the investors changes the nature of the market. If all investors were long-term oriented, the market would suffer a diversity breakdown and hence be less efficient than today’s market.

Source:   More Than You Know

Portfolio managers who underperform the market risk losing assets, and ultimately their jobs. So their natural reaction is to minimize tracking error versus a benchmark. Many portfolio managers won’t buy a controversial stock that they think will be attractive over a three-year horizon because they have no idea whether or not the stock will perform well over a three-month horizon. This may explain some of the overreaction we see in markets and shows why myopic loss aversion may be an important source of inefficiency.

Source:   More Than You Know

A quality manager can absorb and weigh contradictory ideas and information as well as think probabilistically. I add hesitantly that this aspect of learning is borderline academic. I like CEOs who read and think.

Source:   More Than You Know

So an investor who has taken a position in a particular stock, recommended it publicly, or encouraged colleagues to participate, will feel the need to stick with the call. Related to this tendency is the confirmation trap: postdecision openness to confirming data coupled with disavowal or denial of disconfirming data. One useful technique to mitigate consistency is to think about the world in ranges of values with associated probabilities instead of as a series of single points. Acknowledging multiple scenarios provides psychological shelter to change views when appropriate.

Source:   More Than You Know

Ivo Welch shows that a buy or sell recommendation of a sell-side analyst has a significantly positive influence on the recommendations of the next two analysts. Analysts often look to the left and to the right before they make their recommendations.

Source:   More Than You Know

In markets, a symbiotic relationship between positive and negative feedback generally prevails. If all speculators destabilized prices, they would buy high and sell low, on average. The market would quickly eliminate such speculators. Further, arbitrage—speculation that stabilizes prices—unquestionably plays a prime role in markets. But the evidence shows that positive feedback can dominate prices, if only for a short time. Imitation can cause investors to deviate from their stated fundamental investment approach and likely provides important clues into our understanding of risk. Next time you buy or sell a stock, think of the guppies.

Source:   More Than You Know

Here’s my main point: markets can still be rational when investors are individually irrational. Sufficient investor diversity is the essential feature in efficient price formation. Provided the decision rules of investors are diverse—even if they are suboptimal—errors tend to cancel out and markets arrive at appropriate prices. Similarly, if these decision rules lose diversity, markets become fragile and susceptible to inefficiency. So the issue is not whether individuals are irrational (they are) but whether they are irrational in the same way at the same time.

Source:   More Than You Know

Given what we know about suboptimal human behavior, the critical question is whether investors are sufficiently diverse to generate efficiency. If you think across multiple dimensions, including information sources, investment approach (technical versus fundamental), investment style (value versus growth), and time horizon (short versus long term), you can see why diversity is generally sufficient for the stock market to function well.

Source:   More Than You Know

The most direct consequence of more rapid business evolution is that the time an average company can sustain a competitive advantage—that is, generate an economic return in excess of its cost of capital—is shorter than it was in the past. This trend has potentially important implications for investors in areas such as valuation, portfolio turnover, and diversification.

Source:   More Than You Know

While recognition that price-earnings ratios are likely nonstationary is critical, knowing why they are nonstationary provides more practical insight. Three big drivers of price-earnings ratio nonstationarity are the role of taxes and inflation; changes in the composition of the economy; and shifts in the equity-risk premium.

Source:   More Than You Know

Because price-earnings ratios are likely nonstationary, investors should use them sparingly and cautiously, if at all. The attraction of a ratio, of course, is that it is often a useful rule of thumb. I argue, however, that investors who insist on using multiples will find them much more useful if they unpack the embedded assumptions.

Source:   More Than You Know

One of the best examples of a complex adaptive system—generically, a system that emerges from the interaction of lots of heterogeneous agents—is the stock market. Research suggests that when investors err independently, markets are functionally efficient. What’s more, defining the conditions under which markets are efficient provides us with a template to consider when markets are inefficient.

Source:   More Than You Know

Many models in standard finance theory assume that stock price changes are normally distributed around the well-known bell curve. A normal distribution is a powerful analytical tool, because you can specify the distribution with only two variables, the mean and standard deviation. The model, despite its elegance, has a problem: it doesn’t describe real world results very well. In particular, the model is remiss in capturing “fat tails”: infrequent but very large price changes. The failure of risk-management models to fully account for fat tails has led to some high-profile debacles, including the 1998 demise of the hedge fund Long Term Capital Management.

Source:   More Than You Know

[Gary] Gladstein, who has worked closely with Soros for fifteen years, describes his boss as operating in almost mystical terms, tying Soros’s expertise to his ability to visualize the entire world’s money and credit flows. “He has the macro vision of the entire world. He consumes all this information, digests it all, and from there he can come out with his opinion as to how this is going to be sorted out. He’ll look at charts, but most of the information he’s processing is verbal, not statistical.”

Source:   More Than You Know

In a triumph of modeling convenience over empirical results, finance theory treats price changes as independent, identically distributed variables and generally assumes that the distribution of returns is normal, or lognormal. The virtue of these assumptions is that investors can use probability calculus to understand the distribution’s mean and variance and can therefore anticipate various percentage price changes with statistical accuracy. The good news is that these assumptions are reasonable for the most part. The bad news, as physicist Phil Anderson notes above, is that the tails of the distribution often control the world.

Source:   More Than You Know

Is there a mechanism that can help explain these episodic lunges? I think so. As I have noted in other essays, markets tend to function well when a sufficient number of diverse investors interact. Conversely, markets tend to become fragile when this diversity breaks down and investors act in a similar way (this can also result from some investors withdrawing). A burgeoning literature on herding addresses this phenomenon. Herding is when many investors make the same choice based on the observations of others, independent of their own knowledge. Information cascades, another good illustration of a self-organized critical system, are closely linked to herding.

Source:   More Than You Know

The standard model for assessing risk, the capital-asset-pricing model, assumes a linear relationship between risk and reward. In contrast, nonlinearity is endogenous to self-organized critical systems like the stock market. Investors must bear in mind that finance theory stylizes real world data. That the academic and investment communities so frequently talk about events five or more standard deviations from the mean should be a sufficient indication that the widely used statistical measures are inappropriate for the markets.

Source:   More Than You Know

Do financial data neatly conform to such assumptions? Of course, they never do. —Benoit B. Mandelbrot, “A Multifractal Walk down Wall Street”

Source:   More Than You Know

In an important and fascinating book, Why Stock Markets Crash, geophysicist Didier Sornette argues that stock market distributions comprise two different populations, the body (which you can model with standard theory) and the tail (which relies on completely different mechanisms). Sornette’s analysis of market drawdowns convincingly dismisses the assumption that stock returns are independent, a key pillar of classical finance theory. His work provides fresh and thorough evidence of finance theory’s shortcomings.

Source:   More Than You Know

Complex adaptive systems include governments, many corporations, and capital markets. Efforts to assert top-down control of these systems generally lead to failure, as happened in the former Soviet Union. Thinking about the market as a complex adaptive system is in stark contrast to classical economic and finance theory, which depicts the world in Newtonian terms. Economists treat agents as if they are homogenous and build linear models—supply and demand, risk and reward, price and quantity. None of this, of course, much resembles the real world.

Source:   More Than You Know

The stock market has all of the characteristics of a complex adaptive system. Investors with different investment styles and time horizons (adaptive decision rules) trade with one another (aggregation), and we see fat-tail price distributions (nonlinearity) and imitation (feedback loops). An agent-based approach to understanding markets is gaining broader acceptance. But this better descriptive framework does not offer the neat solutions that the current economic models do.

Source:   More Than You Know

In investing, our innate desire to connect cause and effect collides with the elusiveness of such links. So what do we do? Naturally, we make up stories to explain cause and effect. The stock market is not a good place to satiate the inborn human desire to understand cause and effect. Investors should take nonobvious explanations for market movements with a grain of salt. Read the morning paper explaining yesterday’s action for entertainment, not education.

Source:   More Than You Know

Economists have long understood the role of expectations in shaping economic outcomes, including the performance of the stock market and the robustness of capital spending. Yet most economic models presume rational agents, a convenient modeling assumption that also happens to be safely removed from reality. An agent-based model of markets not only offers results consistent with the empirical facts but also accommodates periodic deviations between price and value.

Source:   More Than You Know

Practitioners spanning the centuries have documented the role of sentiment in investing and speculation. Perhaps the best way to think about sentiment is Ben Graham’s Mr. Market metaphor. Graham suggested imagining market quotes coming from an accommodating fellow named Mr. Market, who never fails to show up and offer you a price to either buy or sell your interest in a business.

Source:   More Than You Know

When describing markets, financial economists generally assume a definable tradeoff between risk and reward. Unfortunately, the empirical record defies a simple risk-reward relationship. As Benoit Mandelbrot has argued, failure to explain is caused by failure to describe.

Source:   More Than You Know