Monte Carlo Techniques 'Off the Mark'

September 14, 2004 ( - A retirement systems provider claims a Monte Carlo analysis isn't the best way to help participants understand investment risk.

According to a new research paper by Still River Retirement Planning Software, Inc., a Monte Carlo exercise is “off the mark” when it comes retirement planning. A Monte Carlo analysis involves computing the financial characteristics of a group of scenarios and then compiling the results to figure out the likelihood of a satisfactory scenario.

“Monte Carlo analysis is a powerful tool, but like any tool, works best only when applied to the right situation,” Still River said in the research paper. A Monte Carlo analysis produces success rates that “aren’t what they purport to be,” the results aren’t “meaningful” to most investors, and that the procedure doesn’t address retirees’ actual questions.

“Monte Carlo models are being used to predict the likelihood of retirees not outliving their assets,” Still River researchers wrote. “If a computer model could indeed tell us that, the results would be of interest. But that is not what the computer models actually reveal. What they show is the likelihood of the model coming out OK.”

The Still River researchers also asserted that it would be difficult to carry out a complex Monte Carlo exercise online because it would be too data intense. “Web-based operation has already been ruled out by the developers of most Monte Carlo models,” the researchers wrote. “It would bring a Web site to its knees.”

As far as potential replacements are concerned, the Still River researchers recommended that education/advice vendors should:

  • focus on what retirees should do now and let them update the plan as events in their lives change
  • provide answers on how to handle everything from Social Security to the person’s living situation
  • show the investors how the proposed financial plans will work if there are no surprises and how they can be adapted to integrate late changes in personal circumstances.

The paper, Retirement Income Planning, Part 4: Beyond Monte Carlo, is available at .