We all have spent the year learning in the harshest way what extreme environments mean, both economically and emotionally. From September to April, it was tough to be clear-headed, with frozen credit markets and an equity market so volatile that many investors felt paralyzed.
But now, as the markets slowly emerge from crisis and the bad news has finally relented, it's time to assess the impact of the economic turmoil. So Financial Planning asked leading minds in the industry to share what they learned during the past year. We start with a provocative essay by noted planner and blogger Carl Richards, founder of BehaviorGap, who muses on the nature of risk. In addition, you'll find wise observations and gauntlets thrown down by industry leaders and observers like Michael Kitces, Chip Roame, Tom Bradley, Roger Ibbotson and more. Read on, and share with us online: What did the past year teach you?
Carl Richards, Principal, Clearwater Asset Management
Founder, Behavior Gap
Salt Lake City, Utah
RISK IS RANDOM
I recently had a conversation with an engineer friend who works on problems associated with storing nuclear waste—pretty important stuff. At the time, I was trying to understand some of the statistical tools that make up the foundation of modern portfolio theory (MPT), including Monte Carlo simulations. Turns out, the engineer told me, he also uses Monte Carlo in his work to simulate the physical systems associated with storing nuclear waste.
I asked him how many years' worth of data he needed to feel confident about his conclusions. He said that nuclear engineers start to feel sort of, kind of comfortable with 200 to 400 years of data. Let's stop here for a second. The foundation of almost everything financial planners do, whether it's portfolio design, comprehensive planning or risk management, depends on data that starts in 1926 with the predecessor of the S&P 500. That is 82 years of data! Some of us have tried to stretch the data farther back into history, but it really isn't there.
Back to my conversation with my engineer friend. I asked him how he would feel about using 82 years of data to make decisions. Not from an ethical or moral perspective, but from a risk perspective. He replied, "I don't know how you sleep at night!" Since that day, I haven't slept all that well.
QUESTIONING THE FAITH
I started questioning everything. You see, I've been a member of the community of believers that took MPT theory as gospel. To me, it was settled doctrine and not up for debate. As Russ Thornton, an advisor from Atlanta, recently pointed out, MPT is a theory accepted as scientific fact and elevated to religious status. I find myself questioning the faith. As I allowed myself the freedom to look at my assumptions objectively, I've been surprised at the degree to which I accepted MPT as the scientific way to invest when it is was really intended to be nothing more than a theoretical model. As an industry, we've treated MPT as a scientific law.
How did it happen? The root of the problem is our very human desire to find a way to make intuitive sense of the complex issues surrounding risk and return. With the uncertainty we deal with in this profession, we want a model that will help us accurately explain what is going on in our clients' portfolios, and help us frame, to some degree, what we can expect in the future.
This need to put a framework around risk and return, along with a desire for simplicity, led us to this deep, unquestioning embrace of MPT and planning tools based on similar statistical assumptions.
In fact, Andrew Lo, director of MIT's Laboratory for Financial Engineering, names the desire "to capture 99% of economic behavior in three simple laws" a "deep psychological disorder." He calls MPT "physics envy," and says it has led us to want to fit this complex and uniquely human endeavor into a model that will help us make sense of it.