The Value of Portfolio Modelling Simulations in Financial Planning


As part of our financial planning process, when clients have to make important decisions, we like to “stress test” their plan. One of the tools that we may use is a Portfolio Modelling simulation.

Portfolio Modelling helps us compare different retirement planning options or scenarios to help project and illustrate which alternatives will have the highest probability of success (success is defined as our client’s reaching financial goals).

Bottom line, Portfolio Modelling is a tool that can help us help our clients make better and more informed retirement and investment planning decisions.

Estimating Investment Returns

All financial forecasts must account for variables like inflation rates, market volatility and investment returns. The catch is that these variables have to be estimated, and the estimate used is key to a forecast’s results. For example, a forecast that assumes stocks will earn an average of 4% each year for the next 20 years will differ significantly from a forecast that assumes an average annual return of 8% over the same period.

Estimating investment returns has its challenges. For example, the volatility of stock returns can make short-term projections almost meaningless. Multiple factors influence investment returns, including events such as natural disasters and terrorist attacks, which are unpredictable. So, it’s important to understand how different forecasting methods handle uncertainty.

Why is a Portfolio simulation useful?

In contrast to more basic forecasting methods, a Portfolio Simulation is designed to account for volatility, especially the volatility of investment returns. It enables you to see a spectrum of thousands of possible outcomes, taking into account not only the many variables involved but also the range of potential values for each of those variables.

By attempting to replicate the uncertainty of the real world, a Portfolio Simulation can provide a detailed illustration of how likely it is that a given investment strategy might meet your needs. For example, when it comes to retirement planning, a Portfolio Simulation can help you answer specific questions, such as:

  • Given a certain set of assumptions, what is the likelihood that you will run out of funds before age 90?
  • If that likelihood is unacceptably high, how much additional money would you need to invest each year to decrease the likely outcome to 10%?
  • Will I be better off if I have a more aggressive portfolio allocation vs. a more conservative portfolio allocation?

Example: Let’s say a Portfolio Simulation performs 1,000 iterations using your current retirement assumptions and investment strategy. Of those 1,000 iterations, 600 indicate that your assumptions will result in a successful outcome; 400 iterations indicate you will fall short of your goal. The simulation suggests you would have a 60% chance of meeting your goal.

Pros and cons of Monte Carlo

A Portfolio Simulation illustrates how your future finances might look based on the assumptions you provide. Though a projection might show a very high chance that you may reach your financial goals, it can’t guarantee that outcome. However, a Portfolio Simulation can illustrate how changes to your plan could affect your odds of achieving your goals.

The likelihood of success in an individual outcome is not what is overly important, but rather it is whether one scenario has a HIGHER likelihood of success versus another alternative that is the trust value of a Portfolio Simulation.  When combined with periodic progress reviews and plan updates, Portfolio Simulations help us to guide our clients into making better and more informed financial planning decisions.

Important note on Monte Carlo: 

The projections or other information generated by Portfolio Simulations regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. Results may vary with each use and over time. Because of the many variables involved, an investor should not rely on forecasts without realising their limitations.