I told him: ” Absolutely nothing, if you really believe that some canned program on a stockbroker’s laptop can analyse all the unknowables of the worldwide stock markets over the next fifty years and do it accurately enough to give you that probability within a tenth of a percentage point.” We talked more, and he eventually became a client.
If you want to confuse a client, just throw a few graphs and a bunch of technical jargon at them.
One problem with Monte Carlo Analysis is that it assumes all outcomes have a normal distribution, which means it assumes an equal number of positive outcomes and of negative outcomes. It also assumes that outcomes are random, ignoring the fact that the stock market tends to be random in the short run, cyclical in the mid-term, and trending in the long run.
Another problem with Monte Carlo Analysis is that it ignores the correlation between market events. An example would be a general quickening of market gains when interest rates are lowered and the reverse when interest rates are raised. There are numerous other correlations that are ignored. The stockbroker-salesman would have you believe that none of those correlations affects the probability of achieving your financial goals.
The biggest problem is that Monte Carlo Analysis ignores the sequencing of outcomes. If the stock market crashes early in your retirement, it is very likely your nest egg will never recover. As the brilliant technical analyst Jim Otar explains it: “It only takes a little push of small, adverse events to turn a “median” portfolio into an ‘unlucky’ one, however, it takes a whole lot of large, favorable events to turn a “median” portfolio into a ‘lucky’ one.”
I love Monte Carlo, one of the world’s greatest places, but I hate Monte Carlo Analysis. You should too!