The Hidden Flaw in Monte Carlo Analysis That's Ruining Retirement Plans

Ready For Retirement

James Conole, CFP®

Investment Planning, Bonds, Education, Stocks, Cash, Business, Dividend Investing, Retirement Planning, Retirement, Investing, Tax Planning

5 • 706 Ratings

🗓️ 1 April 2025

⏱️ 25 minutes

🔗️ Recording | iTunes | RSS

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Summary

Many retirees focus on achieving a high Monte Carlo “probability of success” in retirement—but is chasing a 99% success rate always the best move? In this episode, James highlights a real-life story of a man forced to delay retirement after a divorce dropped his probability of success from 99% to 70%. James explores why this single number shouldn't drive such massive decisions. He explains how context—like income sources, spending flexibility, and home equity—matters more than a static succes...

Transcript

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0:00.0	This is another episode of Ready for Retirement. I'm your host, James Cannell, and I'm here to teach you how to get the most of the life with your money. And now, on to the episode.
0:12.7	I was at the gym the other day, and someone came up to me who recognized me from the YouTube channel, and he said, hey, I watched some of your videos, and we got to talking. And he was sharing with me how he had
0:21.3	saved a whole bunch. He and his wife had saved. They've done really well in the retirement
0:25.2	portfolio. They had a paid off home here locally in a very nice part of town. He had a pension
0:30.0	from work. He had social security. And they were planning to retire. And he shared that they had a 99%
0:35.3	plus probability success as they modeled this out with their
0:38.0	financial advisor. Then he went on to share with me that he and his wife actually just went through
0:42.3	a divorce. And after the divorce, after splitting assets, after everything settled, his Monte Carlo
0:47.7	probability success dropped to about 70%. Now, this individual, he was 60 years old and he was planning
0:52.8	to retire very soon until the divorce
0:55.2	happened, until this new financial model showed that his probability of success dropped from
0:59.6	almost 100% probability of success to 70% probability of success.
1:05.1	He then went on to share that because of this change to his financial situation, specifically
1:09.3	this change to his probability of success,
1:11.7	given Monte Carlo simulations, his new plan wasn't to retire soon, but was actually to work
1:16.6	another 10 years until the age of 70, at which time he would max out Social Security in his
1:21.2	probability of success would be right back up there in the high 90%. Now, I don't know any of the
1:25.9	specifics of this individual situation. I don't know dollar amounts. I don't know desired retirement lifestyle. I don't know any of the specifics of this individual situation.
1:27.9	I don't know dollar amounts. I don't know desired retirement lifestyle. I don't know what he
1:31.4	wants to do in retirement. I know none of that information. I don't even know whether his decision
1:36.1	to continue working longer or not was good or bad because I just don't know enough information.
1:41.1	But what struck me about this conversation was how many enormous life
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