Description
Monte Carlo simulations have become the dominant method for conducting financial planning analyses for clients. They are a feature of most comprehensive financial planning software programs, and advisors often use this data point as the centerpiece when they present a financial plan. However, a Monte Carlo simulation ultimately captures an outrageous spectrum of outcomes, then puts a probability of success number on a client’s plan which is supposed to help them make sense of that outrageous spectrum, but doesn’t necessarily leave them with a true peace of mind. Further, most advisors don’t really understand how to best interpret a Monte Carlo simulation, let alone communicate the analysis to clients in a way that creates the peace of mind they’re looking for. As an alternate strategy, advisors use guardrails, which are guidelines to increase or decrease spending when portfolio withdrawal rates reach certain levels. Yet, most retirees do not spend at the constant distribution rates assumed . So what is available to the advisor who wants to provide an effective retirement analysis to clients that reflects how dynamic retired life can be?
Learning Objectives
- LO #1: Define the risk-based guardrail approach and its advantages.
-LO #2: Examine how guardrail strategies perform in the real world.
- LO #3: Understand which levers really matter in a risk-based guardrails plan.
- LO #4: Examine the impact of different risk-based guardrail parameters.
- LO #5: Identify practical considerations of using risk-based guardrail parameters.