Monte Carlo simulation is a technique that models complex systems with multiple components each of which has its own risk profile of achieving different outcomes using a large number of random simulations. Its called Monte Carlo after the famous casino because it really is like rolling dice many times over. For our purposes Monte Carlo simulation can be used to model the different probabilities of your investment portfolio achieving different results. It is also used in other areas such as modelling the probabilities of different outcomes of large complex projects in industry and commerce. Again for our purposes to do a Monte Carlo simulation on your portfolio well you need to have a good understanding of the probabilities of different outcomes of each individual stock, fund or investment position. If you are familiar with statistics and bell curves, then for each stock you would have to know or determine whether the probability of that stock achieving a spread of outcomes follows a standard bell curve, or whether the curve is skewed to the lower or to the higher end or follows another pattern. If you are going to let someone else do a Monte Carlo simulation on your portfolio – and chances are you aren’t going to be able to do this yourself – then recognize that the model can only deliver quality output if it receives quality inputs. If your portfolio is compose of index funds and mutual trusts then you stand a chance of getting a reasonably valid output from a Monte Carlo simulation since the probabilities of the outcomes of such funds are somewhat known. But an important thing to know about Monte Carlo simulation – like all risk modelling systems – garbage in garbage out.
