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Monte Carlo Simulations

May 23, 2017

Monte Carlo simulations are used to determine the probability of outcomes under a range of circumstances. It is used in myriad ways including in financial planning and with life insurance.

A typical use is when making investment or financial decisions, we are usually told that there will be a given result, and it needs a “far-out” circumstance for it not to occur. Well, these are “educated guesses” at best or marketing talk that is just conjecture without any substantial backup. The Monte Carlo simulation is a computer analysis that runs every alternative and provides percentages of probability of the outcomes.

When an investment manager gives you a convoluted asset allocation configuration with a dozen or more investment categories you might be told that the projected portfolio return would be a certain percent. Well, the Monte Carlo program can run thousands of possibilities for each item resulting in the probabilities of attaining almost any return from zero to almost 100%. Somewhere in that model would be the projected result the investment manager told you. Using that projection and looking at surrounding amounts of the selected range you can then judge the probability of attaining the result you are being told. A practical use would be to suggest the sufficiency of assets and cash flow needed when a future retirement is contemplated under favorable and poor market environments.

Another use is with a whole life insurance policy that requires 20 or more annual payments until it is “fully paid.” The Monte Carlo simulation can tell you how likely that projection is. Alternatively you can also enter lower and/or higher payments to see the change in the probability. When I deal with clients in their late 40s to late 50s and they are presented with these policies and I am asked to review the projection, I use a Monte Carlo simulation as a guide. I usually end up telling them that the likelihood of attaining their goal is not as great as they are being told and I suggest a higher premium amount that would increase the likelihood of their goal – they then tell me to mind my own business!

Other uses are with variable rent or loan payments, option and warrant valuations, discounted cash flow models, value at risk analyses, evaluating complex capital structures, quantile modeling, derivatives, financial reporting, executive compensation, and contingent payment and earnout projections. It is also used extensively for scientific, environmental and meteorological purposes.

Monte Carlo simulations are not new; I have been using them for over 30 years. They are helpful, and a tool, and are something to be considered in the appropriate circumstance. Hopefully this blog gives you an understanding of what they are and takes some of the mystery and guess work out of what they are.

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