In the world of advice, discussion can be a very healthy thing. Even if you don't agree with a particular point of view, it can still be beneficial. Because we are emotional creatures, we often make decisions based not on empirical data, but rather on our gut instinct. With this as a backdrop, I'd like to follow up on last week's blog in which I discussed the frequency of the advisor fee deduction. There seems to be a lot of interest in this topic. On my blog, from last week, there were some interesting points brought up.
Before we discuss them, I had a typo in my last blog pertaining to the ending values that I should correct here. Although Scenario B (monthly fee deduction) did outperform Scenario A (quarterly fee deduction), the ending balance in Scenario B was $1,156,455, not $1,554,535 as I wrote. I apologize for the error.
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.
