In his “Intelligent Investor” column in the September 7, 2019 print edition of the Wall Street Journal, Jason Zweig wrote about an idea that we’ve thought about a good deal in the recent past: the fact that not all risk tolerance assessments are created equal. In the piece, Mr. Zweig—himself an accomplished and noted author regarding topics related to the intersection of money and our brains—takes specific aim at what some have referred to as “risk-gamble” type questionnaires that have become somewhat popular in the financial services industry in the last few years. These risk-gamble type questionnaires purport to determine a risk-tolerance level of the respondent based exclusively on theoretical questions in the form of “do you prefer this or that?” Mr. Zweig makes the astute—as well as scientifically accurate—observation that the conclusions reached from administering these types of questionnaires are very unstable and therefore likely unreliable.
Industrial psychologists in the field of psychometrics have known for some time that hypothetical or situational questions along the lines of “how do you feel about risk this morning” are, to put it bluntly, relatively worthless at predicting future behavior. Similarly, asking someone to speculate as to how they will react to something in the future is not a very reliable way to assess any kind of characteristic (except maybe future intention). Mr. Zweig makes this point with a very vivid example: asking someone if they are scared of snakes is a very different thing than tossing a live snake into their lap and watching how they react.
The upshot here is that if you are going to rely on any type of risk-tolerance assessment in building a portfolio for yourself or a client, you need some level of assurance that the output of that assessment is not going to change with the movement of the markets. To put it another way—and at the risk of stating the obvious—results that change based on how the market is currently behaving defeats the purpose of the measurement in the first place. The ideal, of course, is to architect a portfolio with advance knowledge of how the investor will react and behave in future volatile markets, but if the results of the risk-tolerance assessment are unstable, you may not know it until the proverbial stuff hits the proverbial fan.
So what’s a prudent and intelligent investor/advisor to do? Take a guess at risk constitution and hope for the best? Read tea leaves? Mr. Zweig hits upon the answer in his piece: use actual historical behaviors as a guide. The DataPoints psychometric risk-tolerance assessment (called the Investor Profile assessment) does just that—it relies on an expansive inventory of factors including past behaviors in volatile situations (financial and otherwise) to predict future behaviors. The Investor Profile assessment also bases its output on other relevant factors such as self-confidence and self-efficacy in making investment decisions, experience and education as an investor, and long-term versus short-term judgment experience.
The Intelligent Investor piece also highlights the relationship between the concepts of financial goals, risk capacity, and risk tolerance. The DataPoints Investor Profile assessment is designed with the understanding that financial goals and risk capacity will guide the architecture of the plan and the portfolio, but must be implemented within the constraints of an accurate understanding of risk tolerance. This is because an inaccurate understanding of risk fortitude will almost certainly lead to an over- or under-assumption of risk in the portfolio and the attendant adverse impact on portfolio returns. A portfolio that does not take on risk commensurate with tolerance likely means the forfeiture of higher long-term returns; one that assumes too much risk impairs performance as a result of inevitable future rebalancing at inopportune times.
So we offer a thank you to Mr. Zweig for assisting in spreading the word: not all risk-tolerance assessments are created equal. The intelligent investor will take steps now to accurately gauge risk tolerance—before the next market downturn reveals the potential instability of risk-gamble type measurements.