Power Tools for Cognition

Journal of Financial Planning: June 2011

Jonathan Guyton, CFP®, is principal of Cornerstone Wealth Advisors Inc., a holistic financial planning and wealth management firm in Edina, Minnesota. He is a researcher, mentor, author, and frequent national speaker on retirement planning and asset distribution strategies, and a former winner of the Journal of Financial Planning’s Call for Papers competition.

Lately I’ve found myself doing quite a bit of observing and wondering. Most of my reflection for this column was inspired by responses to the question of the year posited on the website Edge (www.edge.org): “What scientific concept would improve everyone’s cognitive toolkit?” It’s possible you’ve read a sampling of the 164 replies to this head-scratcher by the likes of Alexis Madrigal (The Atlantic), David Rowan (Wired UK), Christopher Shea (Wall Street Journal), and David Brooks (New York Times). BBC4 described these mini-essays as “the crack cocaine of the thinking world … once you start, you can’t stop thinking about that question.”

As for me, I can’t stop considering what financial planning might learn from the big thinkers in other fields and wondering which of our profession’s blind spots could be illuminated just enough to aid our collective vision. Taken as a whole, I find their insights a grand mix of excitement, affirmation, and challenge.

One-Dimensional Thinking

For starters, we can recognize when unhealthy approaches are applied to complex matters. Emanuel Derman of the Columbia University Business School suggests banning “pragmamorphism,” or the assigning of “one-dimensional thing-metrics to the mental qualities of humans.” Think IQ tests or economists’ assertion that human preferences always boil down to maximizing “utility.” Based on this, I doubt that Derman would be a fan of sound-byte science—the reduction of any field’s great questions to a single measure. Just how valuable is “the number” or “the safe withdrawal rate”?

Nearly as unhealthy is the Einstellung Effect nominated by Evgeny Morozov, author of The Net Delusion. We each experience it whenever we try to solve a problem using solutions that have worked for us in the past instead of approaching the situation on its own terms. Morozov points out the obvious: “While we may eventually solve the problem, we may also be wasting an opportunity to do so in a more rapid, effective, and resourceful manner.” Of course, efficiency, consistency, and practice-makes-perfect are commendable and profitable, but none of us would want to get stuck in an “I’ve always done it that way before,” paint-by-numbers rut.

More dangerous, however, is to become so efficiently Einstellungian that our unspoken assumptions become practices that may not be the best. Most financial planners recognize that, from a quantitative viewpoint, many retirees are more interested in having the greatest chance of maintaining their lifestyle than in maximizing the size of their portfolio on their dying day. That seems clear enough in terms of the objective as well as the steps that matter most in achieving the one as opposed to the other. But is it really that clear? What about rebalancing? We obviously need to do it, and many of us base our rebalancing policies—when, by how much, and to where—on specific research in this area. However, all the work I know around rebalancing tests various techniques in solving for the highest expected return over the time period in question; and rebalancing to maximize expected return is the same as rebalancing to maximize the portfolio’s value at the period’s end—the exact opposite of the client’s objective. Best practices to meet a client’s objectives in the accumulation phase—research-based conclusions around our reversion-to-the-mean assumptions—may not transfer to their objectives in the distribution phase.

One way to at least partially de-Einstellungize ourselves is to be aware of our untested assumptions, even if, as yet, the test results are unavailable. Research into the effectiveness of various rebalancing policies when seeking to maximize the probability that a given withdrawal rate remains sustainable seems to be one such area for inquiry.

Fear and (Mis-) Focusing

For years, financial planners have sought to help clients understand the various types of risk they will encounter en route to achieving their financial planning objectives. For retired clients, this often means that short-term portfolio volatility is the risk to be minimized above all others. Gerontologist Aubrey de Grey specifically identifies aversion to this particular risk in choosing “a sense of proportion about the fear of the unknown” as his top missing cognitive tool.

More significantly for me, Princeton economist Daniel Kahneman enunciates the “focusing illusion”: “Nothing in life is as important as you think it is while you are thinking about it.” Stop and think about that statement for a moment. Read it again. Get it? (Are you smiling now?) We humans have an impressive capacity for self-inflicted distress by telling ourselves stories that may be both out of proportion and illusory.

Such a story may go like this: Greater short-term volatility can produce greater declines in my portfolio, which is all the more dangerous when taking withdrawals because everyone knows that “selling low” is the biggest mistake you can make and can only increase the chance of running out of money. Combine that reasoning with the financial markets’ so-called lost decade for stocks and an ill-equipped cognitive toolkit, and you’ve got quite a recipe for unintended consequences.

Clients experience this fear and frustration; they are real. Both financial planners and product designers are at risk of succumbing to a focusing illusion because of it. First, even though 2008 was a horrible year for the S&P 500 (down 37 percent), the cumulative three-year returns for the periods ending and beginning with 2008 were –23 percent and –8 percent, respectively (and +12 percent cumulatively over the five years from 2006 to 2010). These are hardly Black Swan-esque occurrences, especially when remembering that a balanced portfolio could have easily funded distributions from interest, dividends, and fixed-income shares for those years (and then some!). Furthermore, globally diversified, balanced portfolios rebalanced annually generated annualized returns in the lost decade that were slightly above inflation. Not a loss at all.

Yet any focusing illusion among financial planners (or fear-mongering for profit in product marketing) creates the possibility of granting this fear such a large voice that we unwittingly expose clients to potentially even greater harms to their quality of life: purchasing power loss and distribution formulae that produce fixed incomes and cause mounting cash-flow stress. How fruitful it could be to introduce conversations with clients about this pair of cognitive tools and how they can ease our internal distress in times of financial (and other) disruptions.

Imagination Sparks and Flameouts

For us planners, it is far healthier to invest in both structured serendipity and gedankenexperiment for our own toolkits.

How do you learn creativity or curiosity? Financial author Jason Zweig doesn’t say, but he cleverly suggests a weekly dose of “reading research that ostensibly has nothing to do with our day jobs, in a setting that has nothing in common with our regular workspaces.” In other words, literally get out of the substance and geography of your normal thought patterns. Gino Segre, a University of Pennsylvania physicist and astronomer, offers that German word meaning “thought experiment.” When we find ourselves asking “Could that be true?” or saying “That just doesn’t sound right,” design a test; then, think the thing through until it falls apart. For example, in safe withdrawal rate research that applies withdrawal policies, there is a reason sustainable distribution rates fall when the equity allocation is decreased from 65 percent to 50 percent but rise when it is not.

The University of Chicago’s Richard Thaler redefines the scientific term “aether” as “the thing that makes my theory work” and advises us to call out its presence, especially when that presence causes the theory to seem un-testable. As Thaler points out, aetherists can say with a straight face that the 2008 market crash was caused by a sudden increase in risk aversion (and not vice versa). Worse, such aetheries can be so pervasive that they become almost universally accepted assumptions: human beings always make rational choices, according to classical economic theory. Aether can morph into product design as the untestable, unknowable “thing” that makes “our product uniquely suited.” Slightly short of this is the funding of research by entities that stand to profit (or lose) from the research’s conclusions. If it’s really that unique and that remarkable, some smart person without a vested interest will surely say so and demonstrate why.

A short distance from such aether situations we find the disconnect between what is modeled in research and what is practiced in real life. Clearly, researchers can model approaches that differ from (best) practice, and practitioners may find ivory-tower approaches to be impractical in real life. That is not my point. Rather, the problem is when research draws conclusions that are not based on models that incorporate all the possibilities for best practice, as well as when practitioners base their advice on the research results, but, in fact, are not incorporating the research methods on which the results are based.

This occurs in both directions even now. Regardless of the investment products used to implement a chosen allocation, it is quite easy for practitioners to specify that interest and dividends not be reinvested in additional shares so they can be used to help fund any intended distributions; however, we do not—to my knowledge—have research that evaluates the impact (if any) of this approach on safe withdrawal rates. And going the other way, many practitioners base their sustainable withdrawal advice on research using balanced portfolios modeled exclusively with Treasuries and high-grade corporate bonds for the fixed-income component; however, when practitioners use significant dollops of other debt instruments (for example, high-yield, emerging-market, and floating-rate bonds), their bond holdings differ significantly—especially in times of financial market distress—from the portfolios on which their advice is based. At the least, we should be aware of these disconnects. At best, a Ph.D. candidate now has her dissertation topic!

Beyond Resiliency and Self-Reliance

We can also consider entire systems themselves. Nassim Taleb of New York University, author of The Black Swan, suggests the concept of “antifragility—the property of disorder-loving systems.” Going beyond robustness, antifragility describes a system that—quite the opposite of being fragile, brittle, or inflexible—benefits from variability and/or shocks. Taleb’s contention is that extreme events (those more than three standard deviations from their means) actually occur more frequently than we imagine, so it is worth considering approaches that go beyond simply being robust or resilient. To attempt an illustration of this fragile/robust/antifragile triad, he offers as examples “literature” (e-readers are fragile, books are robust, oral tradition is antifragile) and “business” (industries are fragile, small businesses are robust, artisans are antifragile).

This is fascinating. And somewhat mind-blowing. The idea of systems or approaches that benefit from (or help prepare us for) chaos can clearly be a risk-management tool. Consider his triad for the financial planning process: balance sheets, budgets, planning recommendations, and certain goals may be fragile; client values, certain goals, and planning policies seem robust; and conversations about money as well as securities having negative correlation with market semi-variance (for example, certain options strategies and inverse ETFs) may be antifragile. Also, a variety of our profession’s body of knowledge that tested the impact of policy-based adjustments and systematic flexibility has found that their implementation adds resilience and robustness to the system.

Some contributions to the Edge’s question stated the obvious, but their powerful implications make us far better for the reminder. Artist and composer Brian Eno points out that we no longer see the world as a neat and orderly hierarchical pyramid, but rather as an “ecology: a profoundly complex, interconnected, web-like system with information running in all directions.” More important, though, is to remember that we are financial planning’s web and that “intelligence itself comes into being [in] fertile circumstances where uncountable numbers of minds contribute to a river of innovation.” Our profession has seen this in our constantly evolving knowledge base around such topics as asset allocation and investment policy, money psychology and client communication, and portfolio distribution and sustainable withdrawal policies.

Lastly, as many contributors noted, such web-like systems and communities are born, live, change, and ultimately die through the organic processes of emergence. David Brooks, in his New York Times column, summarized this well: “We often try to understand problems by dissecting and studying their constituent parts…. [But] emergent systems are ones in which many different elements interact. Their pattern of interaction then produces a new element that is greater than the sum of the parts, which then exercises bottom-up and top-down influences simultaneously. Emergent systems have to be studied differently, as wholes and as nested networks of relationships.”

The financial planning profession and the financial planning relationship are such new elements. No wonder they have been so hard to describe and define! Financial planners, then, are only recently “emerged” from many layers of fertile preparation. We are at our best when we can see this, and will be wise to take full advantage of the many powerful tools available for our toolkit.

General Financial Planning Principles