Long-term expectations and their role in making investment decisions was the subject of chapter fifteen of "More Than You Know: Finding Financial Wisdom in Unconventional Places".
Author Michael Mauboussin pointed readers to John Maynard Keynes’ highly influential book, “The General Theory of Employment, Interest and Money”. From chapter twelve of that book, he pulled the idea that expectations are “embedded” in all our decisions, including investing decisions. Yet, we rarely examine why and how we form our expectations.
Mauboussin wanted to emphasize two aspects of expectations:
- He distinguished between deductive processes (starting with general principles and working toward specific conclusions) and inductive processes (starting with specific facts and then generating a broad conclusion).
- In hindsight, humans overestimate how much they knew about an event before it happened, and, “This hindsight bias erodes the quality of the feedback we need to sharpen our analytical skills.”
Taking Keynes’ ideas a step further, Mauboussin noted that expectations of future returns (yields) can be certain or uncertain (i.e. there are varying degrees of confidence about future events). Those uncertain events were called the “state of long-term expectation”.
Regarding the differences between deductive and inductive approaches, the author also cited economist Brian Arthur. He determined that only simple problems could be solved deductively; in other words, deduction will work for tic-tac-toe, but it may not work for chess.
Mauboussin summarized their work about expectations as follows:
“Keynes and Arthur both draw out a fundamental truth about markets: many investment choices are not, and cannot be, based on mathematical, deductive methods. I would add that, on the whole, a full ecology of strategies is sufficient to generate efficient markets. But when diversity is jeopardized—which it frequently is—markets depart significantly from the underlying fundamentals.”
Naturalistic decision-making
In chapter sixteen, Mauboussin turned his attention to a third path for making decisions: naturalistic decision-making.
The section began with a retired lieutenant general from the Marines, Paul Van Riper, who taught classical decision-making but realized it was not being used in combat simulations. Thus, he met with Gary Klein, a cognitive psychologist, who had researched how firefighters make decisions in complex settings. Klein found that firefighters did not weigh their options as classical theory would suggest; instead, they used the first satisfactory idea that came to them, and if that didn’t work, they tried the next satisfactory idea that popped into their heads.
Mauboussin also brought up Herb Simon’s work on decision-making in the 1950s. Simon argued that humans could not cope with all the information required by the classical school of decision-making, saying that people do not make decisions based on optimal outcomes; instead, they make choices according to what’s good enough. In other words, they “satisfice.”
It’s from that environment that naturalistic decision-making emerged. Robert Olsen has made the case that five conditions present themselves in naturalistic tasks such as investing:
- Problems that are ill-structured and complex: for example, figuring out the fair value for a stock or other security.
- Incomplete, ambiguous and changing information: tock picking relies on expectations about financial performance in the future, making all information speculative.
- Goals that are ill-defined, shifting and competing: while long-term goals may be clear, they can change or evolve in the short term. For example, a portfolio manager may become more aggressive in the short term in hopes of off-setting previous underperformance.
- Stress because of time constraints, high stakes or a combination of the two.
- Multiple participants being involved in decisions.
In the face of such obstacles, Olsen said that naturalistic decision-makers rely on three behaviors to puzzle out the best course of action:
- They use mental imagery and simulation to consider the situation and potential alternatives.
- They also have developed the ability to identify problems through pattern recognition.
- They use analogies to help them reason their way through problems and opportunities.
As an example of mental imagery, Olsen did research among investors who had earned Chartered Financial Analyst (CFA) designations and found that more than 90% of them said it was important to create a story based on the facts. This common result is due to the mental imagery imparted to the investors by the CFA education program.
The art and science of weighing information
In chapter seventeen, Mauboussin took us into the world of statistics and judgments about the value of information.
Thanks largely to technology, today’s investors have mountains of data and information they can use to make investing decisions. However, not all that information is useful, and some of it will even lead to bad decisions. Not all information is created equal. The author wrote, “While there is clearly nothing wrong with pursuing better information—and some firms do it very well—I question the investment value of much of today’s “proprietary” research.”
He saw three key problems with interpreting research:
- Whether investors can properly weigh the information they receive.
- Sampling problems, which arise because the sample population may not be representative of the larger population.
- Current “proprietary” research may not lead to better investment performance.
Regarding how investors weigh information, Mauboussin observed, “Our degree of belief in a particular hypothesis typically integrates two kinds of evidence: the strength, or extremeness, of the evidence and the weight, or predictive validity.”
Second, getting the sampling right can be tricky. He noted that while there are guidelines for population sample sizes, these may not be normally distributed. This means that regardless of the number of samples, the hypothesis may not be a good predictor of future behavior by the population.
Third, on the question of proprietary research generating better returns, Mauboussin reported the evidence is ambiguous. That’s because the market quickly assimilates new information and adjusts to it quickly. In such circumstances, it’s hard to gain an edge. There is also what is known as “baked into the price,” the idea that there is a linkage between changes in fundamentals and expectations incorporated into the current stock price.
He offered this end-of-the-chapter advice:
“Seeking new information is a worthy goal for an investor. My fear is that much of what passes as incremental information adds little or no value, because investors don’t properly weight information, rely on unsound samples, and fail to recognize what the market already knows. In contrast, I find that thoughtful discussions about a firm’s or an industry’s medium- to long-term competitive outlook are extremely rare.”
Conclusion
In the final three chapters of the section entitled “The Psychology of Investing,” Michael Mauboussin has argued that expectations are an important (but often ignored) component of investment decisions, that naturalistic decision-making processes are used by many leading investors and that we must be careful in how much weight we give to information, including what appears to be scientifically-valid information.
The overall goal is to help readers of "More Than You Know: Finding Financial Wisdom in Unconventional Places" to be more aware of how unseen psychological biases may creep into their investing decisions.
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