What in the World is Monte Carlo Simulation?

Money 2000 and Beyond Monte Carlo Simulation. It makes one think of gambling, doesn't it? It fact, where personal financial planning is concerned, it is a technique used to reduce the gamble that many people take when they decide to retire and live off of their savings.

Here is a simple explanation. When individuals or financial planners produce a projection of anticipated cash flows and investment performance throughout the retirement period, they invariably use one or more fixed figures for the anticipated rate of return (e.g., 8%, 9%.) which are based upon the expected investment strategy and historical rates of return.

However, history tells us that there IS not a diversified portfolio that will reliably produce the expected return annually or even after decades have passed! We have just lived through one such gut-wrenching 3-year period. Data from Ibbotson Associates shows that the standard deviation for a 100% equity portfolio expected to return 11% over a 30-year period is 1.6%. According to James Putman, CFP, author of the Wealthy Minute, "this means that there is one chance in three that your aggressive, 100% equity portfolio invested in 2003 will return 9.4% or less per annum through the year 2033. There is one chance in ten that it will return 7.8% or less."

It is clear that if you are counting on 11% over 30 years, and spend in accordance with this expectation, but instead you receive 8%, you might be applying for food stamps by the time you are 80. Of course, to be fair, there is also the probability that you will get more and be a multimillionaire. But this "upside risk" is not the one you are worried about.

So how does Monte Carlo simulation help? By inserting some valuable additional criteria into the retirement equation. Many financial planners use these 30-year standard deviations to test the expected rate of return on retirement projections. (Standard Deviation is the measure of volatility of investment returns.) Specialized software is used to randomly change the rate of return (to cover 98% of all possible outcomes). With each change, the software records how much money the person is left with at the end of life.

After the simulation is complete, the financial planner can show what percent of the time the client still had money left over (i.e., how often the project was successful). He/she then seeks to craft a projection that provides for both an acceptable spending level for the person and an acceptable probability that assets won't be depleted. Then, of course, responsible planners, monitor and revise as necessary to ensure no unpleasant surprises occur at a time down the road when the retired client can do little about it.

  1. Rutgers
  2. Executive Dean of Agriculture and Natural Resources
  3. School of Environmental and Biological Sciences