We believe that the current paradigm for measuring risk does not serve the investor as well as it should. To make this point, we will first summarize the current paradigm and then suggest an alternative that we feel is better.
Risk is a common measure to determine what kind of portfolio allocation is appropriate for an investor. There are a variety of measures of risk in the marketplace, some involving more complexity than others. In general, however, most risk tolerance questionnaires we have studied address two key issues: investment time horizon and investor risk tolerance.
Time horizon is a critical measure because real investment risk declines as time horizon grows – the stock market has never lost money over a 20 year period. Time horizon has two key dimensions to it:
These horizons are driven by investment goals and provide the objective side of the risk equation – how does one most effectively accumulate assets to achieve their goals without taking too great a risk of losing the money that they need to achieve these goals?
Investor risk tolerance addresses what investor behavior might be over time – most importantly, will the investor panic-sell when the market drops? For the most part, risk tolerance tends to be a measure of reaction to short-term volatility rather than long-term market performance. This concept is important because we know that most of the loss of investment potential is caused by investor behavior rather than market performance.
Another reason for its importance is that low risk tolerance clients can suffer uncomfortable psychological issues when the market drops, such as stress and sleepless nights. These effects often bleed over into the client-advisor relationship. Low risk tolerance clients can consume their advisor’s time or question the relationship. Risk tolerance measures tend to fall into two to three categories of questions:
These measures are then combined with time horizon to determine a portfolio mix with the appropriate Beta for the investor. Different tools use different algorithms.
Why the Current System Fails the Investor
We believe that the current system fails the investor because it does not do enough to isolate each of these two statistics and show how they are different. The investor would benefit from understanding the consequences of each of these measures before making a decision on how to invest.
Time horizon is a more objective measure that gets at what ideal investment behavior should be based on the investor’s life needs. According to the American College, financial planning is only about two things — time and money. Time horizon-related questions get at these two issues and can provide the ideal investment strategy for the investor.
Risk tolerance, on the other hand, provides a measure of how much the advisor needs to stray from the ideal path because the investor cannot stomach loss. Reducing portfolio risk based on investor sentiment is creating a sub-optimal investment strategy. We understand the need to do this – 2008 certainly taught us that. However, by accepting the investor’s risk-averse behavior at face value, the advisor or the tool is recommending a sub-optimum strategy. As an analogy, if a patient came to a psychologist with a fear of heights, the current industry paradigm would be to tell the patient to “stay away from tall buildings.” In fact, most psychologists would instead try to address the phobia first.
How the process should work
We feel that a risk tolerance tool should provide analysis and feedback based on the investor’s time horizon and risk tolerance. The investor should be shown the results of each of these measures — what a pure time horizon strategy and what and one adjusted for risk aversion would each produce over a full market cycle based on historical projections. The current paradigm does address risk/return trade-off, but only in the short run.
This would be a starting point for a more robust discussion of investment strategy, either with an advisor or with an online tool. If the investor is truly a “flight risk,” then a conventional allocation recommendation can be made that takes risk aversion into account. However, if the investor more fully grasps the cost of risk avoidance and how low the risk of loss is over a long time frame, perhaps the risk algorithm can be adjusted to take on more risk.
We feel that this alternative offers several advantages:
Furthermore, at Greenwald, we are excited about the prospects that this core model offers to design more effective tools. For example, we are exploring the idea of testing additional psychological measures such as personality to determine where on the continuum between ideal and risk-adjusted investing investors should fall. We also feel that a more sophisticated tool might pave the way for a more robust discussion about ideal investment strategies such as using alternative investments.