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The Folly of Risk and the 401k Fiduciary

The Folly of Risk and the 401k Fiduciary
July 11
00:04 2017

Anyone with an MBA or with a degree in finance and investments knows the phrase “risk-return” trade-off quite well. Whether we recognize it or not, the “risk-return” trade-off forms the basis of nearly every transaction we make. It doesn’t matter if we’re buying a car (used vs. new? Extended warranty or not?) or buying a stock (upside vs. downside? Growth vs. value?), deep inside we’re measuring the counterbalance between the potential risk we perceive and the prospects of the return we expect. (For detailed examples, see “401k Plan Sponsor & Participant Primer – The Risk-Return Tradeoff.”)

If you’re a student of World War II military history, you’ve learned our success on those battlefields came down to one word: Logistics. Although operations management predates its used in ancient Greece (to build the pyramids) and China (to build the Great Wall), the version we’re most familiar with today was developed in the 1940s. We can sum up the difference between the earlier version of operations management and the modern version as the difference between labor and data.

Modern operations management exploded onto the scene of organization management at the same time computers were introduced into our thinking processes. Computer can produce faster, more accurate, results. This yields both a greater likelihood of success and a greater magnitude of success. All one needs to do is feed the computer, and to feed the computer one needs data. Lots of it. The more the merrier.

Following World War II, the armed services released their systems analysts into the workforce. Armed with these new methods, and with access to greater technological resources, they streamlined American industry just in time to solidify our country’s role as a world Superpower. Most famous among these were the “Whiz Kids” – ten veterans brought on as Ford Motor Company executives in 1946.

This knowledge, however, wasn’t limited to automobile manufacturing. It spread through all areas of the economy, including finance and investing. We see this primarily through Modern Portfolio Theory, which found its fruits (as well as its Achilles’ Heel) through powerful (but, unfortunately, not powerful enough) computers. As one might expect, this demanded data, and the risk component of MPT’s “risk-return” trade-off proved fertile ground for the creation, cataloging, and consumption of this vital processing component. (For a specific listing of these components, see “Investment Risk and the 401k Fiduciary: An Overview of Components.”)

This is where the folly of risk began. It’s not that the formulae were wrong. It was more the use of risk had become misapplied. More precisely, we deviated from the original definition of “risk” and its associated management. Prior to Modern Portfolio Theory, risk management relied on actuaries to manage the theory of large numbers. If this sounds like the world of insurance companies, then you’re onto the general idea of how we had traditionally defined risk and the types of strategies we used to mitigate risk.

Insurance companies sought to align their best interests with the best interests of the insured. You might call this the “fiduciary” definition of risk. While the insured is willing to buy protection against various risks (e.g., house fires, car collisions, and premature death), insurance companies prefer to reduce the number of claims paid (which then reduces premiums which makes insurance less expensive which attracts more people to buy insurance). Insurance company have “risk management” departments that focus on “loss control.” They reduce the likelihood of claims by teaching insurance buyers things like not leaving their iron plugged in (to reduce house fires), defensive driving (to avoid collisions), and the dangers of daredevil behavior (to lessen the chance of premature death).

The MPT use of risk is less like that of an insurance company (though the terminology is similar) and more akin to that of a riverboat gambler. This is all about the sense of and ability to control events. Insurance companies and their customers seek greater control over events by changing behavior to avoid if not eliminate the downside. This means, for example, when you see a dark alley, you simply don’t go down it, even if it represents a significant shortcut. Riverboat gamblers look at a dark alley and try to determine the odds of the downside. If they find the odds attractive enough, they’ll choose to venture down that foreboding path.

We shouldn’t blame MPT solely for this skewed attitude with regard to risk. In truth, MPT merely represents a step-child of econometrics. Again, fueled by advances in computer technology, econometrics uses complex stochastic formulations to develop (and nearly automate) decision-making. It has made economics become, in fact, just another application of game theory. Not that there’s anything wrong with that. Games can be fun, entertaining, and even educational. But it’s one thing when you assess the odds and chose to go down that dark alley while playing COD (where the ultimate downside just means you spawn back into the game), and it’s quite another to go down a dark alley in, say Chicago, (where the ultimate downside means you become just another statistic in America’s murder capital (JK, according to The Trace, America’s murder capital is St. Louis)). (For those interested in understanding the original origins of risk and risk management, read “7 Deadly Sins Every ERISA Fiduciary Must Avoid: The 2nd Deadly Sin – The Joy of ‘Risk’.”)

Redefining the meaning of “risk” and the practice of “risk management” might be forgivable. After all, it’s all marketing sizzle. Redefining the steak of statistics, on the other hand, smacks of border-line fraud, or at the very least bad science. Before we get too further on this, it’s important to distinguish between the work done by scientists and the work done by engineers. Scientists work in the realm of theory. They can afford to make assumptions the violate real world constraints. For example, physicists regularly employ frictionless models when fiddling with motion theory. It’s not practical, but it’s a lot cleaner when testing the viability of the theory.

Engineers, however, live, breathe, and work in the real-world. Not only do they have to account for friction, but also wind resistance and atmospheric pressure. Their profession is very exacting. They can’t cut corners, for, if they do and the bridge falls down, well, let’s just say that’s a fiduciary liability problem financial professionals should be grateful they’ll never encounter.

But financial professionals are like engineers in the sense they cannot mislead when it comes to the mathematics of investment returns, cash flow analysis, and other material and measurable statistics. Yet this is precisely what the industry has been doing for decades – and with both implicit academic and direct regulatory support.

How is this possible? You can point your finger at the ubiquitous “generally accepted principles” excuse. Once an idea becomes “generally accepted,” it fills a void. We all know from marketing 101 that it’s easier to fill a void than to replace something that is already occupying a void. So it is with volatility, the generally accepted proxy for risk.

Volatility has all the traits necessary from a marketing perceptive. It’s easy to measure. It’s easy to show. It’s easy to understand. In fact, there’s only one trait it lacks: accuracy. You see, in order for volatility to work as advertised it needs to do two things. First, it needs to be relevant to the user. In the real-world of investing, returns that exceed their mean by 30% (i.e., performed far greater than expectations) are viewed as “a good thing” compared to returns that miss their mean by, say, as little as 1%. But, on academic blackboards across the ivy-covered land, exceeding the mean by 30% entails greater volatility than missing the mean by 1%; thus, the former is considered “riskier” than the latter. If it’s not obvious, using statistics this way may lead to suboptimal decisions, and that could be a long-term problem for retirement savers, and perhaps an issue of fiduciary liability for plan sponsors (see, “The 401k Plan Sponsor’s Dilemma – What’s Wrong with ‘Risk’.”)

In fact, 401k plan sponsors might want to take another look at the way the service providers they hire talk about risk, especially if those vendors tend to use phrases like “risk adjusted returns.” The term “risk adjusted term” is generally used in a factually correct sense. For example, if a portfolio with 50% stocks and 50% cash performs 10% less than the S&P 500, we can accurately say it outperformed the S&P 500 on a risk-adjusted basis because, by all rights, it should have underperformed by 50%, not just the 10% it did. Problems arise from the more liberal use of the term risk-adjusted return, specifically in the sense that it takes the place of a definitive number to define the retirement saver’s goal. In the real-world, this definitive number (i.e., what’s needed to put food on the table, clothes on the back, and a cover over the head) represents the actual goal. “Risk” or “risk-adjusted” anything simply doesn’t have a place in justifying why a retirement save might miss that goal. There’s an old Wall Street adage that explains this: “You can’t eat risk-adjusted returns.” (There a couple of good examples of this in “Why Risk Doesn’t Matter to the ERISA Fiduciary.”)

What’s the one thing 401k plan sponsors can do right now to make sure employee participants don’t fall prey to the folly of risk? The easiest thing to do is to remove all reference to “risk” in the most basic educational materials. This may sound negligent, especially since the “risk-return” trade-off has become a “generally accepted” principle (there’s that phrase again). This may true if the plan sponsor shoves all references to “risk” down the memory hole, but we’re saying only to leave it out of the introductory materials. It can remain in the more advance educational materials – but only if is placed within the full context of its origins and its misuse. Most importantly, there is one singular favorite industry tool 401k plan sponsors should consider banning outright: The infamous “Risk Tolerance Questionnaire.” (Would you like to know why? Read “Should 401k Plan Sponsors Ban Risk Tolerance Questionnaires?”)

It’s difficult enough for plan sponsors to focus on the business of their company let alone the fiduciary responsibilities that go along with managing their company’s retirement plan. Because of this, it’s quite understandable that plan sponsors seek to default to “generally accepted” principles, particularly those with a long-standing academic history. Luckily, we’ve seen a growing body of new academic research in the field of behavioral finance that has begun to displace the post-World War II studies the industry has relied on for more than half a century. These new studies provide the backbone for the 21st Century 401k plan. Leading plan sponsors already utilize these techniques. They include such actions as emphasizing saving strategies over investment strategies in educational programs, reframing how investment performance is portrayed (here, regulators continue to cause improvement to lag), and, the use of default investment options to remove the temptation for inexpert retirement savers to make ill-suited decisions. (The following article summarizes three such behavioral finance research papers: “Tips 401k Plan Sponsors Can Use to Help Employees Avoid Risk Aversion.”)

Many professionals and most of the current generation of finance professors have long ago removed “risk” from their investment decision-making algorithms. These forward-thinking folks recognize the greater importance of managing retirement saver behavior over managing irrelevant investment risk as it pertains to meeting or exceeding the goal of retiring in comfort.

Christopher Carosa is a keynote speaker, journalist, and the author of  401(k) Fiduciary SolutionsHey! What’s My Number? How to Improve the Odds You Will Retire in Comfort and several other books on innovative retirement solutions, practical business tips, and the history of the wonderful Western New York region. Follow him on Twitter, Facebook, and LinkedIn.

Mr. Carosa is available for keynote speaking engagements, especially in venues located in the Northeast, MidAtantic and Midwestern regions of the United States and in the Toronto region of Canada.

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Christopher Carosa, CTFA

Christopher Carosa, CTFA

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