Why Straight Lines Don’t Work For Investors
A few weeks ago we discussed some common investor mistakes. If you don’t have the time, expertise, and/or desire to manage your investment portfolio, mistakes are no great surprise. But what about professional financial advisors? What mistakes are made by people who make a living advising others how to invest?
One common mistake is not building a portfolio around the investor’s goals. Investment advisors frequently plan based on deterministic financial models. This is a way of calculating a portfolio’s future value by plugging in a desired rate of return along with inflation, taxes, and other simple variables. All the variables remain static through the entire model.
A big problem with this method is whether the assumptions are reasonable. Only a few years ago, many advisors routinely assumed 12% or even higher returns. Second, straight-line modeling doesn’t give an accurate picture of market volatility or risk. Portfolios do not operate like escalators, moving up at a constant rate. Assuming they do is asking for trouble.
About a decade ago some retirement planners, recognizing the inherent flaws in deterministic modeling, started using Monte Carlo simulations. Monte Carlo analysis computes the probability of an event, such as running out of money through one’s retirement, by testing hundreds of possible results. In other words, it looks at a range of scenarios for variables like return or inflation rather than relying on just one.
Monte Carlo simulations were a great leap forward for investment planning, but even these sophisticated models can be used incorrectly. As Richard Fullmer of Russell Investments explains, “The conventional guidance is that investors should plan using a low — 5% to 10% — probability of failure, although the suitable probability threshold for any particular individual will depend on his or her risk tolerance… the problem with this definition and treatment is that the probability of failure is not a complete measure of risk. Just as not measuring risk can be dangerous, so too can mismeasuring it.”
In reality, risk is not only the probability of an event occurring but also the consequences if it does occur. An event with a high probability and a low magnitude may have the same mathematical results as an event with low probability and high magnitude.
Consider Fullmer’s example: Let’s say the fine for a speeding ticket is $100 when the driver’s speed is less than 15 miles per hour over the speeding limit and $1,000 when the driver’s speed is more than 15 miles over the limit. Now say you are driving on a road where the posted speed limit is 50 miles per hour. ‘Clearly, the risk to you of driving 67 miles per hour on this road is much greater than the risk of driving 63 miles an hour.’
Does this mean Monte Carlo analysis is as worthless as the old straight-line model planning? Not at all, it’s still a wonderful tool as long as the assumptions are grounded in reality. Monte Carlo analysis is not a complete process. A good advisor will also lead clients through a serious discussion of risk and the magnitude of that risk.
Monte Carlo Analysis is a tool; it’s not the only factor in designing your portfolio. Your personality, goals and risk profile should ultimately drive your retirement plan. The analysis shouldn’t be driving you. If your planner/advisor isn’t helping you understand the difference, it may be time to shop for a new one.
If you are currently interested in finding out more about investment management, a great place to start is with our affiliate Capital Cities Asset Management. You can contact them at (800) 767-2595 to discuss your needs or to schedule a free investment consultation.