Using Monte Carlo in Financial Planning: The Assumptions

In my blog last week (A Financial Plan’s Two Most Important Assumptions) we talked about the role of Monte Carlo simulation (MCS) and how to use it to determine the most important assumptions in a financial plan.

This week we’ll discuss a list of the assumptions on which I use MCS. First, let’s look at an overview of the information required to create a comprehensive plan. 

The information required to create a comprehensive financial plan can be categorized as follows:

Quantitative Data

• Assets
  Tangible
  Intangible
• Liabilities
  Debt (balances > 12 months)
• Income
  Current and retirement
• Expenses
  Fixed (i.e. debt payments)
  Variable
  One-Time
  Current and retirement

Qualitative Data

• The Client’s Goals and Dreams 

When gathering client data, some advisors prefer to use a legal pad and pen while others opt for a standardized questionnaire. You can easily use the first method if you follow an outline such as the one above. However, to be sure you capture all the necessary information, you might want to use a standardized questionnaire. I’ve used both methods and have developed my own standardized questionnaires. These are very detailed but I prefer to get into the weeds when planning. After all, the output will only be as good as the data you input.

You should consider using MCS on assumptions which contain the greatest variability. I have three categories for assumptions.

• Static
• Low Variability
• MCS Assumptions.

One example of a static assumption is a corporate pension. Other data may not be static but the degree of variability is low and adding MCS to these assumptions will have little impact on the results. The final category includes assumptions which are most suitable for MCS.