Often, I’ll use a fixed value when modelling portfolio growth. For example, investing $1,000 per month at 9.447% p.a. (Note 1) will produce a very smooth graph like this:
However, in reality, returns are far from smooth. In fact, the above graph is the summarized version for a 20-year investment journey starting on the 31st October 1983. If we overlay the real data it looks like this:
Notice how bumpy the real journey looks in comparison to the smooth exponentially modelled scenario. In this case the investor can be considered to be lucky since for the majority of the journey her portfolio provided higher returns than what was modelled exponentially. It is only during the last few years where a sequence of negative returns, starting with the dot-com bust, brought the overall return down to 9.447% p.a.
Illustrating volatility of returns
Another example of this is the DFA global core equity trust calendar returns. Using an exponential model, returns from 2011 to 2020 averaged 11.387% p.a., however in reality we see that calendar returns vary from -8.68% to 49.47% (DFA 2021).
Starting and finishing dates heavily affect returns
Let’s take a look at 3 additional investment journeys where $1000 per month was invested over 20 years. Notice that by changing the start dates the finishing values, and returns, vary significantly. In these 4 cases, the portfolios produced per annum returns of between 3.77% and 10.56%. The higher of the 2 portfolios provided compounded returns that were more than twice the value of the lowest.
What does this mean for you?
Even though the vast majority of my portfolio modelling is done at an exponentially compounded rate of 7% and many long run portfolio returns are likely to meet, or exceed this value, investors need to understand that there will be significant variations in returns long the way. The first implication of this is that a significant portion of your efforts should be directed towards planning a course of action during periods of negative returns. If you find that you can not cope with the volatility you need to increase your portfolio allocation of volatile assets such as bonds.
The second implication for investors is understanding the fact that your individual long run investment returns will vary significantly depending on when you start and finish your investment journey. Unfortunately, this is something we have less control over than we think. This means that when modelling your time to reach financial independence you must use a variety of returns. When doing our financial planning I’ll typically look at portfolio returns of between 3% and 8% p.a. At this stage we need returns averaging approximately 5.1% in order to be financially independent at the end of 2026. Ideally, I’d like to improve the chances of success via an increase in savings rate.
Concluding thoughts
Exponential modelling of portfolio trajectory is a good way to illustrate growth over long periods of time, however this must be coupled with the understanding that returns will almost always deviate significantly from the average value. As a result, no-investment journey will be smooth and we all need to be prepared to deal with periods of low or negative returns. As always, understanding your cash flow situation; building a high savings rate; and managing debt levels are some of the best ways to reduce the effect of portfolio volatility on your general life.
Engineer your freedom
References
Dimensional, 2021, Global Core Equity Trust Unhedged Class, available from: < https://au.dimensional.com/funds/global-core-equity-trust-unhedged-class>
Notes
1. Compounding calculations at 0.755% per month