6. Plans, Risks and Monte Carlo: Dealing with uncertainty

Previous articles have been focused on understanding broad market behavior and how best to deal with the uncertainties of what lies ahead. But equally, important is to understand how future expectations play out relative to your needs and plans.

When constructing a financial plan (which is a good idea) you should come to the table with a few basic assumptions: income, spending, assets, time-frames and risk tolerance. Now if you are willing to work with average values, you can ignore the risk and assume the averages will work. I wouldn’t do that for several reasons. Your needs may change and investment returns are not constant. You really should understand the probabilities and the degree to which your plans will succeed (or won’t). That is the role of a Monte Carlo Simulator.

The future is filled with uncertainties: investment returns, interest rates, inflation, and your income and spending needs. All of this can mean that a plan that will work with the average values, won’t work if things deviate from those averages. Using average values may yield a positive outcome for a given plan. But that means there is 50/50 possibility that plan will end above or below you're goals. Do you want a 90% chance you goals are met? Or do you want a 99% chance. And what is the worst case you could tolerate? In a nutshell, that is your risk tolerance. A Monte Carlo simulator applies all your assumptions, adds in the variables and calculates the probability that your plan will work.

At first blush that may seem an esoteric and complex exercise. When I first retired, my financial adviser ran a Monte Carlo simulation for my needs. But when I questioned many of the assumptions, I was left with more questions than answers. For instance, how did the return and volatility metrics match up with my portfolio going forward? What if future returns were worse. If I reduce volatility in my portfolio, and my returns suffer, is that better or worse?

So I built my own Monte Carlo Simulator. It includes lots of places to test all those assumptions. Things that would affect the outcome: spending, assets, earnings, taxes, inflation, investment returns, investment volatility, time frame and more, including sequence risk (This is an important and often overlooked phenomenon; Bad things that happen early in a plan can have a more negative effect than bad things that happen later. Any plan or Monte Carlo analysis should include its possible effects. A thirty year plan's outcome could change by a factor of 2X depending when it starts relative to long term expectations.) The data generated by InvestEngines includes all the investment metrics you need for the Monte Carlo simulator. You put in those values, click a button and out pops a probability distribution of outcomes. If you aren't happy, try different assumptions and see if that makes things better or worse. If you would like a copy of a simple Excel Monte Carlo simulator to explore your own situation, please contact me at InvestEngines@gmail.com.