It sounds like something from a James Bond movie, but it actually has to do with your investments. Here we’ll take a high level look at what it is and how it might be applied to your portfolio.
Games of chance — think dice, roulette, or craps — are known for producing random outcomes. But can these outcomes be determined in advance?
That was the question posed by a mathematician named Stanislaw Ulam. He would play game after game of solitaire, plotting the outcome of each game in order to observe outcome distribution, trying to determine how probable it was that he would win.
What started as a way to entertain himself while recovering from brain surgery became a simulation technique applied across industries and around the world to model the probability of varying outcomes to different scenarios.
Ulam and another mathematician, John Von Neumann, partnered up to develop the technique, which they called the Monte Carlo simulation after Monaco’s world-famous gambling destination. This technique is used in prediction and forecasting models to grasp the impact of risk and uncertainty.
How is a Monte Carlo simulation applied to your portfolio?
While investing isn’t a game of chance, it is subject to uncertainty and there are random variables that make determining probability of returns difficult. The Monte Carlo simulation is frequently used in financial planning and portfolio management to predict whether or not an investor will have the amount of retirement income needed.
Let’s look at a specific example. You probably have pretty specific ideas about the lifestyle you would like in retirement. When we work with you, we start with understanding what that goal lifestyle and other objectives in retirement look like for you. Next, we create a financial plan based on those goals.
That plan will drive everything we do for you from a portfolio management perspective. But first, we need to gauge the potential success of that plan. We do that by running Monte Carlo simulations, which supply a risk analysis and help us assess the probability of different outcomes to various scenarios.
We typically use these variables in Monte Carlo simulations:
- The size of your portfolio
- The allocation of your assets
- Your time horizon (or how many years you have until retirement)
- Your planned annual withdrawal rate
- Your planned annual deposits
- Inflation rates
Why not just look at historical performance?
Looking at historical performance of a stock’s prices, for example, just supplies one outcome for reference. That outcome, which took place in the past, may or may not be applicable in the future. Using the Monte Carlo method allows us to consider a wider range of possible outcomes, which can help minimize uncertainty and measure and model risk.
It’s a way to virtually demonstrate a strategy and project probability of that strategy’s success into the future. It looks at different allocations of assets with varying risk profiles, a mix of correlations between assets, and works in several factors from projected lifespan to different withdrawal rates. The ultimate aim of all this is to determine whether or not your portfolio will supply the necessary returns to last for the duration of your retirement.
While there’s no way to absolutely predict market returns or other uncertain variables that will impact your portfolio, this simulation tool is one way we can get a sense of your financial forecast.
