In 2014, Robert Merton lamented in “The Crisis in Retirement Planning” that “investment value and asset volatility are simply the wrong measures if your goal is to obtain a particular future income”. Which is an important concept to emphasize, as many basic financial planning strategies focus only on solving for an asset-based goal to be achieved at a specific point in time (e.g., needing to have $X by the time I retire at age Y), and at best project a range of wealth outcomes around that target at the intended future date.
In this Guest Post, Charles Fox, a financial advisor with Integrity Wealth Partners (an RIA in Walnut Creek, CA) shares how a more robust analysis that accounts for real world outcomes and the potential for retirement delay (or retiring early) can be a powerful tool to really help clients plan for their goals. In other words, the variability of time (and not just the variability of wealth) is a key variable to include in a retirement planning analysis, and when used together with retirement cashflow and desired asset-based goals, financial advisors can help clients better understand how to connect their actual saving and spending behaviors with the trade-offs illustrated in their financial plan.
However, even with plans that incorporate time-based factors to examine asset-based goals, if the plan is limited by a deterministic analysis (i.e., one that does not consider the impact of random events on the results), the client may not have a realistic perspective of the potential impact that market risk and volatility will have on their plan. Which means that Monte Carlo simulations can still be a valuable tool to help clients put these factors into perspective, but by demonstrating not only how asset-based goals would change in dollar amounts but also over time, when affected by the impact of a wide range of potential market conditions.
Accordingly, by using dynamic retirement dates and asset goals that make sense for the client, and by adjusting the simulation parameters to factor in variable times actually spent in retirement (i.e., dependent on the actual retirement date), advisors can present simulation-based results in terms that are relevant and relatable to the client (e.g., not just answering the question “how much do I need to save to retire” but answering the more direct question, “When might I be able to retire?”), while accounting for potential market risk and volatility. In other words, advisors can illustrate how target goal thresholds (e.g., the amount needed to retire at a certain point in time) can change over time as the required assets to meet that goal change as well. Additionally, Monte Carlo-based simulations can be used to effectively illustrate how changing the cost of a goal can affect the timeframe required to achieve that goal, as well as showing the impact of changing small habits over long periods of time (not just in terms of wealth accumulation, but in the speed of reaching a retirement goal in the first place).
Ultimately, the key point is that dynamic time-oriented reporting (as contrasted with traditional deterministic wealth-oriented reporting), when coordinated with flexible retirement goals, can help clients understand not just the timeframe required to complete a goal, but also how different factors (e.g., a delay – or acceleration – in retirement date, the costs associated with reaching the goal, market variability, etc.) play into and trade off with each other in reaching their goal. And using simulation-based analyses provides even more texture than can be communicated in a single probability of success. Perhaps most importantly, time-oriented reporting can help facilitate conversations with the client about how the variables considered in a multifactorial, simulation-based analyses affect their financial plan – in a manner that the client can understand and use!