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. In other words, will you outlive your retirement assets or will you have enough money saved to last you well into your late 80s and 90s?
Here is a brief explanation of Monte Carlo simulation. Many simple retirement savings calculation tools produce a projection of anticipated cash flows and investment performance throughout the retirement period using one or more fixed figures for the anticipated rate of return (e.g., 8%). This fixed figure is generally based upon someone’s investment strategy and historical rates of return. Historically, the more stock that is in a portfolio, the higher its long-term average annual return.
While better than doing no calculation at all, fixed rate planning tools have one major flaw. History also tells us that there is not a diversified portfolio that will reliably produce the expected return annually or even after decades have passed. Instead, investment returns, especially for stocks, are usually all over the map and can go through prolonged slumps that can last years.
If you are counting on 10% over 30 years, and spend in accordance with this expectation, but instead you average a return of 7%, you might be living a severely reduced lifestyle 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 most people are worried about. Rather, they are concerned about the chance of outliving their money.
So how does a Monte Carlo simulation help? By inserting additional criteria into the retirement equation. Many financial planners use 30-year standard deviations to test the expected rate of return on retirement projections. Standard Deviation is a measure of volatility of investment returns. Financial advisors use specialized software to randomly change the rate of return to cover about 98% of all possible outcomes. Modern computer technology makes this analysis possible and, with each change, the software records how much money a person is left with at the end of their life.
After a Monte Carlo simulation is complete, a financial planner can show what percentage of the time a client still had money left over (i.e., how often the projection 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. Often, key variables in the simulation (e.g., age at retirement, amount of money needed) are adjusted to find an outcome that works.
Then, of course, it is up to investors and/or their financial advisors to make necessary portfolio asset allocation adjustments to match the desired simulation outcome. They must also monitor and revise the retirement plan as necessary to ensure no unpleasant surprises occur at a time down the road when a retiree can do little about it. Current investment returns are also tracked for an investor’s portfolio and added to the historical database upon which Monte Carlo simulations are made.