Almost all retail financial advisers use fixed percentage allocation (FPA) to help their clients manage investment risk. FPA is simple, which partly explains its widespread use. However, FPA has significant drawbacks. Newer methods potentially offer a better way to manage risk.
FPA creates an investment policy by assigning a targeted value-based allocation percentage to each asset class. A simple example assigns 60% of portfolio value to stocks and 40% to bonds. If the investor approves the 60%-40% policy, the adviser buys and sells assets to match the policy. After a few months, the adviser and investor compare the true allocation with the policy. If stock values increased more than bonds during the interval, the true allocation might equal, say, 65%-35%. The final step rebalances the portfolio by selling stocks so the true allocation to stocks returns to 60%. After the adviser uses stock proceeds to buy more bonds, the true and policy allocations match again.
At least three factors explain widespread use of the FPA process. First, most investors and advisers understand the FPA process. Second, the process sounds like buying low and selling high. That is, the process sells assets whose values might be higher than they were in the past and buys assets whose values might be lower. Third, FPA provides a discipline, a set of procedures capable of divorcing emotions from investment decisions.
Simple solutions are almost always superior to complicated solutions; this is the principle of Occam’s razor. The main exception occurs when simple solutions fail. Here lies FPA’s first flaw. FPAs simple allocations give a false impression of stability. Risk imposed by a 60%-40% allocation this year is often not the same as risk imposed by the same allocation next year. Changes in risk can threaten the integrity of almost any allocation.
A second flaw lies in the deceptive appearance of a buy low, sell high process. Many investors hold a mistaken understanding of buying low and selling high: They believe the reference point is past prices. However, low and high should relate to future prices, not past prices. FPA’s rebalancing method is based on past prices. However, buying low should only matter if the future price is higher. Past prices might matter in sale transactions, but the idea behind the adage holds that investors sell to take profits or avoid further losses before prices fall in the future.
A third flaw concerns assessment of investor risk tolerance. How does one reduce a psychological construct like “risk tolerance” to an allocation percentage? Typically, financial advisers administer a simple test with 10 or so multiple choice items.[i] Each possible answer is assigned a certain number of points. After adding the points, the advisor consults a key that assigns FPAs based on total points. Most of these tests seem to ask legitimate questions, but they are, at best, naïve, and few of these tests have been checked for validity.
Perhaps investment allocation will always be more art than science. However, psychologists and statisticians have made inroads. John Grable applied psychometric testing criteria to evaluate reliability and validity of a test designed to measure risk tolerance. It has been developed more since its original publication in 1997.[ii] A recent version of the test appears at http://pfp.missouri.edu/research_IRTA.html.
Also, many investors measure risk itself instead of using a risk proxy.[iii] Some of these methods assign allocations based on risk percentiles,[iv] and they use Monte Carlo analysis to simulate risk scenarios.[v]
Investment risk, by its nature, will never be tamed. However, some of these newer methods might improve how we manage it.
[i]To see risk tolerance quiz examples, try an online search with these terms: investment risk tolerance quiz.
[ii]Grable, J. E. (1997). Investor risk tolerance: Testing the efficacy of demographics as differentiating and classifying factors(Doctoral dissertation, Virginia Tech).
[iii]Most investors and advisers would probably benefit from books about risk measurement and portfolio management, and particularly those including the topics of maximum diversification, minimum variance, and risk parity strategies. Here are a few academic sources some investors and advisers might find useful to begin learning about alternatives to the FPA proxy method:
Choueifaty, Y., & Coignard, Y. (2008). Toward maximum diversification. Journal of Portfolio Management, 35(1), 40. Retrieved from https://www.tobam.fr/wp-content/uploads/2014/12/TOBAM-JoPM-Maximum-Div-2008.pdf.
Clarke, R., De Silva, H., & Thorley, S. (2011). Minimum-variance portfolio composition. Journal of Portfolio Management, 37(2), 31. Retrieved from https://361capital.com/wp-content/uploads/Minimum-Variance-Portfolio-Composition.pdf.
Chaves, D., Hsu, J., Li, F., & Shakernia, O. (2011). Risk parity portfolio vs. other asset allocation heuristic portfolios. Journal of Investing, 20(1), 108. Retrieved from https://www.researchgate.net/profile/Jason_Hsu8/publication/228206016_Risk_Parity_Portfolio_vs_Other_Asset_Allocation_Heuristic_Portfolios/links/00b7d532848224ae2d000000/Risk-Parity-Portfolio-vs-Other-Asset-Allocation-Heuristic-Portfolios.pdf
[iv]Imagine ten possible investable asset classes and all of the possible allocation permutations; the number of allocations would be in the hundreds of thousands depending on details. These allocations can be ranked according to the risk each allocation is expected to impose and an investor can be assigned an allocation based on risk tolerance. Of course, this method still aims to reduce the psychological construct, “risk tolerance” to an allocation. However, the allocation directly measures risk, and the allocation can be changed periodically to reflect changes in risk.
[v]Monte Carlo analysis uses statistical distribution parameters to create hundreds or thousands of possible future outcomes.