The concept of “homo economicus,” or the rational economic man, has served as a cornerstone of modern finance theory since formally introduced roughly 50 years ago. This simplified construct of human behavior assumes three key characteristics—perfect self-interest, perfect rationality, and free access to perfect information. Behavioral finance, in what Peter Bernstein referred to as “The only competing doctrine to modern finance theory” (p. 57), challenges these assumptions.¹

The first element of this competing doctrine was introduced by Amos Tversky and Daniel Kahneman with the publication of “Judgment under Uncertainty: Heuristics and Biases.”² In this seminal piece, the authors argued that in making decisions in a complex world with multidimensional alternatives, individuals do not necessarily incorporate all available information in their decision process but, rather, use mental shortcuts (“approximation methods”) to simplify and expedite the decision process. The use of these mental shortcuts, referred to as “heuristics,” assumes that the results will be consistent with those reached through a more rigorous process.

Generally, this assumption is well founded; unfortunately, all too often it leads to suboptimal conclusions and occasionally to severe errors. For example, if asked which of two coins is the “fair” coin when one, tossed six times, results in a sequence H-T-T-T-T-H and the second H-H-H-H-H-H, most respondents would conclude that the first is the fair coin because the second series does not look random. The error is based on the heuristic of “representativeness.” The first series looks more likely than the second. In fact, both sequences are equally likely.

In 1979, Kahneman and Tversky published their second groundbreaking paper, “Prospect Theory: An Analysis of Decision under Risk.”³ In this paper, they challenged the premise of traditional utility theory that decision makers evaluate outcomes by the utility of final asset positions. Instead, they proposed utility-based “outcomes as gains and losses, rather than as final states of wealth or welfare (p. 274).] They also argued that “framing” (i.e., changing the way options are presented) may result in dramatic changes in preferences. As an example, would you prefer to eat a snack that is 10 percent fat or one that is 90 percent fat free, or would you prefer an order of prunes or dried plums?

Subsequent to the publication of their papers, and particularly after the award of the Nobel Prize in economics to Kahneman in 2002, behavioral finance has become an actively debated topic among academics and practitioners. Unfortunately, it would seem that much of the debate either misses or obviates the extraordinary insights and practical strategies behavioral economics provides the practicing wealth manager. What is missing from the debate is a recognition that, in spite of its lack of mathematical rigor, the lessons taught by behavioral economics work for those of us dealing with real people. As David Laibson and Richard Zeckhauser wrote:

…psychology provides no overarching paradigm, and is more like a kludge. It is a patchwork of ideas and conceptions, which, when combined with excellent professional judgment, yields good forecasts about human behavior.⁴ (p.25)

In fact, I believe that the works of Kahneman and Tversky and others in the field, particularly those who study issues related to individual investors, provides extraordinarily relevant and practical material for the practicing wealth manager.⁵ To demonstrate the point and to encourage others to develop additional practical behavioral wealth management applications, the following are examples that have been incorporated in our practice.

Risk Tolerance
Risk tolerance questions can confuse risk tolerance and capacity.  For example, an investor may have the financial capacity to take a 20 percent one year loss or may have a long time horizon.  But does the investor have the emotional willingness to “hold fast” should the portfolio value actually sustain a 20 percent short term loss? Therefore, use questions that will assist in educating your client by framing contradictory goals. As an example, we use the following framing question:

For each of the following attributes, circle the number that most correctly reflects your level of concern. The more important, the higher the number. You may use each number more than once.

Almost everyone circles 6 for the first question, and even the most conservative investor circles 4, 5, or 6 for “growth” and 6 for “inflation protection.” We call this our “gotcha!” question. With this framing, even the least sophisticated investors recognize that they have conflicting goals.

We use a similar approach regarding performance by requesting in the following question that our clients select from among an array of risk–return portfolio choices. Everyone wants to select the diagonals (i.e., high return/no risk), but we explain that the real world requires higher risk for higher returns.

Several portfolio performance projections are listed below. Assuming that inflation averages 3%, check the portfolio that most nearly reflects your goal for your portfolio. [Note that the actual question has 10 choices.]

*We use the term “worse case” to describe the worst annual return that a portfolio is likely to experience 90% of the time. REMEMBER—these are hypothetical projections and they represent the change over a 12 month period, NOT a day or week just after a market crash.

Quarterly Reports
For many years, our quarterly reports provided recent month and year-to-date performance data along with market benchmarks, such as the S&P 500 Index and NASDAQ. Once we started applying a behavioral overlay, we realized that we lectured our clients about long-term performance and investing to meet their goals; however, our reporting focused their attention on short-term returns and market performance. Today, we do not provide any performance for periods less than one year, and we benchmark against CPI, not the S&P 500, to better frame our clients’ understanding.

Loss Averse vs. Risk Averse
Based on prospect theory, we believe that our clients are loss averse, not risk averse, and that our planning reflects this belief. We educate our clients by a variation of the following simple two-part test.

Question #1
(a)  You win $800,000
(b)  You have an 80% chance of winning $1,000,000 (or a 20% chance of winning nothing)

Question #2   
(a)  You lose $800,000
(b)  You have an 80% chance of losing $1,000,000 (or a 20% chance of losing nothing)

In well over 90 percent of the cases, our clients select “a” for Question #1 and “b” for #2. We explain to them that, although their answers seem inconsistent from a rational view, they make total sense to us. We understand that they do not want to take risk to make money but that they are prepared to take risk not to lose money.

For example, suppose you are Mr. Conservative Client. If you were to go to a traditional broker with a portfolio of CDs, she might say “you’ll never get ahead with those CDs; I’d recommend we move half of those funds to stocks to make you some money.” Your reaction would probably be “no thanks.” Working with us, after we complete the planning process, we may end up making exactly the same recommendation (i.e., move half your money to stocks). However, if we do so as wealth managers, it will be for a totally different reason. Our rationale will be we do not want you to lose your standard of living. Based on our planning and accounting for inflation, we believe you need to include equities in your portfolio to maintain your lifestyle. After such reframing, I have had traditional CD investors say, “That makes sense, I’m ready to listen.”

Managing Client Behavior
I am sure most advisers have had a client dash into their office requesting the liquidation of a sizable chunk of his portfolio in order to invest in his best friend’s no-risk, Make-A-Fortune start-up company. In the past, we would try to logically explain the potential risk of such an investment, but our reasoned concern would fall on deaf ears. Today, we use two behavioral strategies. First, we say, “That sounds wonderful, but I’m not familiar with “Make-A-Fortune. Tell me about it.” Next we ask, “What might go wrong?” We find that if the client is forced to think of potential problems and describe them to us, he often listens to himself. Next, we prepare a revised capital needs analysis and say, “Wow, if you make the investment and it works out well, you can increase your annual spending by $xx. Of course, if it doesn’t, you may have to work an extra three years.” It is amazing how effective these strategies can be in changing a client’s mind.

To conclude, I recommend that advisers heed the wise words of Richard Thaler:

…in the not-too-distant future, the term “behavioral finance” will be correctly viewed as a redundant phrase. What other kind of finance is there? In their enlightenment, economists [and wealth management practitioners] will routinely incorporate as much “behavior” into their models as they observe in the real world. After all, to do otherwise would be irrational. (p. 16)⁶