Monte Carlo Simulation"
May 12, 2009
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The following is in response to Eleanor Laise’s article, Odds-On Imperfection: Monte Carlo Simulation, which appeared in the Wall Street Journal on May 2.
Dear Ms. Laise:
Thank you for your recent article on how Monte Carlo Simulation is being misused within the financial services industry. As Chairman and CEO of Financeware, Inc., the leading vendor of such tools with tens of thousands of financial advisors as customers serving hundreds of thousands of investors, I appreciate your shedding light on the misrepresentations made by many in the financial services industry with these tools. From erroneous capital market assumption inputs causing garbage outputs, to fat tailed black swans curiously missing from the analysis, you picked up on several of the problems many within the financial services industry have highlighted with this mathematical modeling method.
Unfortunately, you missed the biggest misuse and played right into the hands of an industry focused not on the investor’s wealth but instead on their own.
Our industry suffers from a conflict of interest, perpetuated by your article, which results in scaring people into needlessly sacrificing their lifestyle, only to die on a death bed stuffed with money they could have spent. Unethical product vendors use the “odds of success” and “failure” to scare investors into maximizing how much they have in their portfolios (so they can collect more in fees) at the price of the investor spending as little as possible (sacrificing their lifestyle). Investors are pushed to take needless portfolio risks through excessively aggressive portfolio allocations to compensate for overly conservative assumptions, scary fat tails, or targeting too high a confidence level.
In reality, the result simulated IS NOT the “odds of success” as those you interviewed would like you to believe, but instead, the odds of excess.
Likewise, the "odds of failure" assumes that regardless of what happens in the markets, NOTHING in the plan will ever change. A 12% portfolio decline could easily cause a drop in confidence level from 82% to 67%. Why should the focus be on last year’s confidence number or the original date of the analysis? Monte Carlo analysis is only useful if it is used on a continuous basis as a guide to know WHEN you should change your plan. For most people, even with simulations run at relatively high confidence levels, the odds are usually near 1 in 1,000 that the markets will be so well-behaved that they will avoid becoming over-or under-funded at some time over the course of their life. Think about the simple mathematical reality of this. If it is possible to spend too much or have too little money, it must also be possible to spend too little or have too much money for a particular set of goals. If you can be underfunded, it must also be possible to be overfunded.Display article as PDF for printing.
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