Let’s get back to the topic at hand. One advisor commented that my analysis was based on static assumptions, which is true. Since returns were static, I was not taking into consideration the fact that markets fluctuate, which is also true. They suggested I use actual returns of the S&P 500 to model reality. The problem here is determining which two-year period to use. However, since the method I used was equally applied to both scenarios, it shouldn’t matter if I use static assumptions or S&P returns for some period. But it did make me a bit curious. So to satisfy my growing curiosity, I decided to use Monte Carlo simulation on the problem. I used an 8.0% return and a standard deviation of 12.0% on each portfolio (scenario). I also ran 10,000 simulations. Each time a simulation is run, the return varies, based on the standard deviation (risk) of the portfolio, and a new ending balance is recorded. This type of MCS is referred to as the parametric method and the results of the analysis are noted in the following table.
|
Scenario A (Quarterly Fee Deduction) |
Scenario B (Monthly Fee Deduction) |
Mean |
$1,153,493 |
$1,155,703 |
Median |
$1,150,003 |
$1,154,233 |
1 Standard Deviation |
$96,383 |
$56,060 |
Notice the mean and the median were greater when the fees were deducted on a monthly basis. The other very important item to note here is that the standard deviation was smaller when the fees were deducted monthly. So the result was greater growth with less risk in Scenario B, and isn’t that what we’re all trying to accomplish? Deducting the fees monthly had a positive effect on the portfolio. It’s very much like dollar cost averaging in reverse.
Another issue which was brought up was the additional time needed to deduct the fees monthly rather than quarterly. I think this is a valid point. I suppose if you have a large number of accounts, this could pose a problem. I would view it this way. If it’s the right thing to do for the client, then we should find a way to do it efficiently!
I appreciate all your comments.