It generates returns for the market based on the covariance matrix and returns assumptions. These do fluctuate, but long-term estimates of these values are pretty well defined. The simulation here generates several thousand random returns based on these assumptions, and the results indicate the distribution of possible outcomes.
The results you are seeing suggest that under these assumptions, there is a 1% chance that you will have -$5M and a 1% change that you will have $20M at the end of the simulation. (1st and 99th percentile outcomes).
With different parameters (less savings, lower income, etc) you may have a much high likelihood of running out of money.
Knowing what this distribution looks like can be quite informative.
I could modify the market returns generator to allow for variance around the historical market assumptions, or provide some sensitivity analysis. On the whole, though, that will simply expand the distribution of the final results. I believe it is better to target more conservative assumptions than it is to include both conservative and aggressive assumptions. If you know that your conservative scenario still plays out well, then you can be confident that your plan is sound.
I guess, to sum up: the fact that monte carlo returns a distribution is a feature, not a bug. You can't know the future for sure, but you can put some bounds around the likely outcomes. If you have a 10% of running out of money (for example), you should probably save more.
The results you are seeing suggest that under these assumptions, there is a 1% chance that you will have -$5M and a 1% change that you will have $20M at the end of the simulation. (1st and 99th percentile outcomes).
With different parameters (less savings, lower income, etc) you may have a much high likelihood of running out of money.
Knowing what this distribution looks like can be quite informative.
I could modify the market returns generator to allow for variance around the historical market assumptions, or provide some sensitivity analysis. On the whole, though, that will simply expand the distribution of the final results. I believe it is better to target more conservative assumptions than it is to include both conservative and aggressive assumptions. If you know that your conservative scenario still plays out well, then you can be confident that your plan is sound.
I guess, to sum up: the fact that monte carlo returns a distribution is a feature, not a bug. You can't know the future for sure, but you can put some bounds around the likely outcomes. If you have a 10% of running out of money (for example), you should probably save more.