Monte Carlo Simulation

Defined:

Monte Carlo Simulation is a problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables.

Monte Carlo simulation is named after the city in Monaco, where the primary attractions are casinos that have games of chance. Gambling games, like roulette, dice, and slot machines, exhibit random behavior.

Theory:

Monte Carlo Simulation is founded on the belief that one can manage risk. This, of course, has been furiously debated for thousands of years. If you’d like to learn more about this concept, I highly recommend checking out “Against The Gods.”

Who Uses Monte Carlo Simulation:

There are two primary types of individuals that use Monte Carlo Simulation:

• Academics: Anything abstract, unmeasurable, and theoretical is, of course, a fascination of academics.
• Advisers to Rich Men: Individuals managing the money of richer individuals tend to use Monte Carlo Simulation

How does it feel to know that excel jocks are cranking out your future cash flow expectations using a method called, “Monte Carlo”?

Recent Grumblings:

At last grumblings of Monte Carlo Simulation are erupting. Most notably, in the Wall Street Journal’s weekend edition (May 2-3rd 2009), money managers have declared that enough is enough. The Monte Carlo Simulation failed to “simulate” what’s occurred in the markets most recently:

Now, some investors have decided that if risk can’t be accurately measured, they will just have to play it safe. Jeff McComas, a chemical engineer in Woodbury, Minn., has used six or seven Monte Carlo Calculators and found that none highlighted the possibility of a scenario like the recent market downturn. The lesson: “The future is so unknown that your prudent choice is to save as much as you can now and live below your means.”

Bottom Line:

Monte Carlo Simulation is beginning to wear thin.