Black Swans & Monte Carlo

Imagine heading off into retirement with a financial plan that you took great care in developing. You carefully determined your budget including adjustments over time for various lifestyle changes … Perhaps more travel early in retirement, but less in your later years … Increasing medical expenses as you grow older … You assumed a conservative rate of withdrawals from your investments of 4-5% with the expectation that you would be able to maintain your purchasing power against inflation and that you would not run out of money … even if you lived to be 100. You entered into your Golden years confident that you future was secure.

Then along comes an event that is considered to happen perhaps once in a generation. That event is a dramatic drop in the stock market. It profoundly changes your finances and forces you to consider radical changes to the plan you felt was nearly infallible. The author Nassim Nichosals Taleb calls this a Black Swan event. The term comes from the assumption that “all swans are white.” In this sense, a Black Swan is a metaphor for something that cannot happen. However, in the 18th century, Black Swans were discovered in Western Australia.

If Black Swans exists and we know it, then perhaps we can plan for the possibility that we will experience one. In the financial planning field, advisors use computer modeling technology called Monte Carlo Analysis to test the sustainability of a client’s plan. The problem is that basic retirement planning software relies on values that are assumed to be static. For example, the rate of inflation and the growth rate for investments are assumed to never change. This is, on the surface, wholly unrealistic. Inflation is hardly fixed and the returns in the stock market are far from a steady X (pick your return) percent.

Monte Carlo Analysis attempts to resolve the problem of static variables inside a retirement plan. It randomly assigns different values to each of the key variables inside a retirement plan. The plan is then simulated to determine that unique outcome. With modern computers this can be done for tens of thousands of scenarios in a matter of seconds.

The good Financial Planner wants to know how many of these iterations results in an outcome that is satisfactory to the client. This might mean not running out of money before age 100 or it could mean leaving behind a substantial inheritance to one’s heirs. The computer will tell us how many of these outcomes were “failures” and how many were “successes” depending on our definition. At our firm we prefer to see a success rate of at least 90%. Anything less than that suggests a level of risk we feel is too great to bear.

Black Swans exist. Events that are unexpected and profound occur. Rather hope you never experience one (because you will), it’s better to plan for them. Monte Carlo Analysis is one tool that can help you.