Trying to understand Probability of Living Standard Range
I’m struggling to understand the Monte Carlo results and how to use them. I’m making progress, but there are still some things that confuse me. The thing I’m currently stuck on is the fact that on the Probability of Living Standard Range chart, the results seem to be skewed downward, i.e., toward underperforming the projected standard of living trajectory rather than surpassing it.
For example, under the 75%-100% column, the probability figure for 2008 is 69% while the probability figure in the 100%-125% column is 31%. I interpret this to mean two things: first, that my standard of living in that year is virtually certain (100%) to fall within 75% and 125% of the projected trajectory; and second, that my standard of living is over twice as likely to fall below the projected trajectory as it is to rise above it.
Why is the probability of underperforming within the 75%-100% range twice as great as the probability of over-performing within the 100%-125% range? I would think the probabilities would be roughly equivalent, since the target figure (the “projected trajectory”) is derived from the average return for the asset mix I have specified.
This bias toward underperformance becomes very pronounced in later years. In 2026, for example, the figures are 71% (in the 75%-100% range) and 9% (in the 100%-125% range). And to make matters worse, there’s a 13% chance in that year of the standard of living falling within the next lower range: 50%-75%.
Can anyone explain this?
Guillermo
RSS
In the current version of ESPlannerPlus, we assume that households make their spending decisions based on their expected returns independent of the riskiness of their returns. This is a strong assumption (which we are working on modifying). But it has the virtue of showing the potential downside to risky investing. An agressive spending rate, like the one we assume, coupled with an agressive investment strategy spells lots of downside risk -- risk that gets bigger through time. You see this in terms of the percentile living standard distrubution curves heading south.
We are now working to have the program do what's called Expected Utility Maximization. In this new analysis, we'll ask users to specify their tolerance for risk and give them spending advice that is predicated on their self-reported risk aversion and the riskiness of their portfolios. The message we'll be delivering is that if you want to invest agressively, you need to spend defensively.
best, Larry