Will you have enough money in retirement? A new study could help investors find that number.

Financial Planners


by Robert Powell

Researchers Say Coverage Gives Retirees More Control over Risk

Many retirees and retirees worry about living beyond their means. And for good reason. Most people don’t know their death date, so they don’t know how long their money will last.

To address this risk, also known as longevity risk, financial planners began using Monte Carlo simulations about 25 years ago to try to make uncertain outcomes a little more certain.

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And they had good reasons for doing so. These simulations employ mathematical techniques that model the probabilities of different outcomes and have found great success in many other areas. For example, engineers can use Monte Carlo simulations to estimate the strength of bridges under different loads, meteorologists use Monte Carlo simulations to predict the path of hurricanes, and researchers use Monte Carlo simulations. to model the spread of disease.

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According to Byrd, the retirement planning world first learned about the use of Monte Carlo simulation in retirement planning in 1997, when financial planner Lynn Hopewell wrote in the Journal of Financial Planning, That was when I published an article titled “Decision Making Under Certainty Conditions: Awakening.” -Financial Planning Professional Recruitment

In that article, Hopewell argued that financial planners need to start using Monte Carlo simulations to give clients a more realistic view of their retirement prospects.

Since then, planners have reacted to Hopewell’s arguments, increasing the use of Monte Carlo simulations in retirement planning, and with good reason.

Consider: Monte Carlo simulations allow financial planners to take into account a wide range of variables that can influence a customer’s retirement prospects. Monte Carlo simulations can generate a distribution of possible outcomes, giving retirees or prospective retirees a more realistic view of their retirement prospects. Third, Monte Carlo simulations can be used to test different retirement income strategies. This helps retirees or those planning to retire find strategies that work for them.

Of course, like most technologies, Monte Carlo simulation has its limitations. According to Kitces.com, Monte Carlo simulations may not fully account for occasional extreme market volatility. It is based on historical data and may not be suitable for predicting future earnings. It can be complicated and hard to understand. They are not a substitute for good financial planning. To create a post-retirement income plan.

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According to Javier Estrada, currently in the world of retirement income planning, advisors typically use Monte Carlo simulations to consider withdrawal policies and asset allocations to ensure strategies maintain a retiree’s planned withdrawals. He says he’s learning the percentage of retirements he didn’t get. Professor of Finance at IESE Business School and author of Retirement Planning: Is One Number Enough?

There is no one-size-fits-all target for this failure rate. For example, some advisors want a plan whose probability of failure is only 10% of his, while others say he has goals ranging from 10% to 25%, and even 50%. Some people are satisfied with plans that fail with a probability of .

Read: Why a 50% chance of success is actually a viable Monte Carlo retirement prediction.

But whatever the subject, the methodology is generally accepted practice.

“Finding an asset allocation or exit policy that minimizes or yields an acceptable failure rate is a very common methodology,” Estrada said.

However, Estrada’s study revealed two major flaws in this goal-focused approach, including failure rates. One is the inability to distinguish between early and late failures at retirement. And he said two, the bequest left behind is not taken into account.

coverage

To address these deficiencies, Estrada and Mark Klitzmann, CEO of Wyndham Capital Management and senior lecturer at the MIT Sloan School of Management, wrote a 2019 paper on coverage ratios. He introduced the concept and said it was a “new metric that is better than the coverage ratio.” failure rate. ”

According to Estrada, coverage simply represents how many years you can withdraw the desired amount from your retirement account to support your lifestyle, taking into account your asset allocation and the number of years you need to withdraw. increase.

A strategy that continues withdrawals until the end of retirement without a bequest would have a coverage ratio of 1.

Strategies that continue to withdraw and leave bequests throughout retirement have a coverage ratio greater than 1.

Also, a strategy that exhausts the portfolio before the retirement period ends will have a coverage ratio of less than 1.

For example, consider three strategies with a 30-year retirement period, a $1,000 retirement portfolio, an inflation-adjusted annual withdrawal of $40, and a different stock/bond allocation for each.

The first strategy exhausts the portfolio in 24 years, the second in exactly 30 years. And his third strategy continues her withdrawal for 30 years, leaving a $240 bequest. This will also allow her to support her $40 withdrawal for 6 years. In this example, the coverage ratios are 0.8, 1.0, and 1.2 respectively.

In other words, Estrada said the coverage ratio considers whether the exit plan is underperformed, accurately implemented, or surpassed expectations by leaving a bequest.

And using coverage is a much better way to gauge whether a retiree will last a lifetime.

Now, this approach has pros and cons.

“The advantage is that the coverage rate, unlike the failure rate, takes into account the failure of the strategy and how much bequest it will leave if the strategy succeeds,” Estrada said. “The main drawback at the moment is that failure rate has a long history and is very widely used, whereas coverage rate is new and needs to be popularized and better known. That’s it.”

Distribution of coverage rate

But Estrada said in a recent paper that retirees and advisors shouldn’t focus on just one coverage rate, but rather the entire distribution of coverage rates, or a particular percentile that suits their tastes. suggests that. Retirees will then have a better understanding of the optimal asset allocation and withdrawal strategies to consider given their retirement goals.

Indeed, many approaches have been proposed so far, and it is likely that many others will be proposed in the future. However, the approach proposed by Estrada in his paper has significant advantages from his point of view: “It’s easy to understand for retirees, easy to explain to advisors, and hopefully both will help retirees make important decisions like this.” ”

Now, at the risk of going deep into the weeds, Estrada proposed in his latest paper to calculate coverage for each considered (historical or simulated) retirement period and focus on the distribution of coverage. .

“This will allow retirees and advisors to consider not only the mean (average) or median (middle number) coverage rate for each strategy, but also the relevant percentiles of the distribution, such as extreme scenarios.” he wrote. Occurs with a low probability (1%, 5%, or 10%), especially at the left end of the distribution. The far left is an outlier, a bad and improbable result, for example, where the coverage ratio may be less than 1.

As such, Estrada noted that the relevant percentiles to watch and the relative importance given to each will be a choice for retirees to their own tastes.

For example, his study shows the distribution of coverage rates across various asset allocations from 100% equities to 100% bonds when using a 4% withdrawal rate (see Exhibit 1) and when using different asset allocations We examined the distribution of the coverage rate of . The withdrawal rate he is 2% to 6% (see Figure 2).

And what he finds in the former case is that, naturally, as the percentage assigned to stocks increases, the average and median coverage ratios increase. And in the latter case, not surprisingly, he found that the mean and median coverage steadily decreased as the initial dropout rate increased.

This approach of looking at the entire distribution of coverage rates is not as neat as choosing a strategy that maximizes or minimizes a target value (such as failure rate), but Estrada says it has several desirable properties. I have.

This avoids focusing on just one misleading mean. Consider unlikely scenarios, especially (outliers). It also enables different scenarios to be weighed according to each retiree’s goals and priorities, implicitly incorporating preferences.

So one retiree might prefer a 3.5% exit rate with an average coverage of 3.11, while another with a different goal and risk profile would prefer a 4% exit rate with a lower coverage of 2.53. You may like the rate. In either case, retirees can withdraw the amount they want from their retirement account to support them for the rest of their lives and still leave a bequest. However, for a 3.5% withdrawal rate, coverage offers slightly more certainty than her 4% withdrawal rate.

Ultimately, however, retirees can choose the withdrawal rate and asset allocation that best suits them and their risk tolerance.

And it matters.

(Read more) Dow Jones Newswires

06/28/23 1114ET

Copyright (c) 2023 Dow Jones & Company, Inc.



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