Early retirement drawdown12/30/2023 ![]() Reporting the Newey-West, heteroscedasticity-adjusted t-stats to account for overlapping windows. Regress the SWR of a 75/25 S/B portfolio (zero final value target) on a constant and the actual realized return over the 30 years (left) and the returns over the six 5-year windows (left). ![]() Also, recall that a t-stat with an absolute value above 2 is normally considered statistically significant. Side note: The results here are slightly different from the post back in 2017, for (at least) two reasons: a slightly different time frame with additional data and a 75/25 portfolio instead of an 80/20 portfolio. To prove that, I disentangle the average returns and split them into six 5-year windows (years 1-5, 6-10,…, 26-30) and when I run a regression of the SWR on an intercept and those 6 different subperiod returns, boom, I get a much higher R^2 and much higher beta estimates on the earlier returns. The reason is that the returns early in retirement have a much larger impact on retirement success than the later returns. Only about one-third of the variation in the SWR is accounted for by the (geometric) average annualized portfolio return over the retirement horizon. As you can see in the table below (left panel) you get statistically significant estimates, but a relatively poor R^2. We can also confirm this 10-year time through a second approach – a more quantitative exercise as I proposed in Part 15 of the series: calculate the safe withdrawal rate (assume a 30-year horizon, a zero final value target and a 75/25 stock/bond portfolio) for all different starting dates between 18 and then regress that on the realized returns. in CPI-adjusted terms! So, instead of 1-2 years, we’re looking at much closer to 5 years for a moderate bear market and often 10+ years for the deep market events. That’s because the portfolio doesn’t merely have to start to rise again (= end of the bear market) but your portfolio has to reach its old peak again to overcome the effects of Sequence Risk. In my post “ Who’s afraid of a Bear Market?” I pointed out that a Bear Market can have a much longer destructive impact on your portfolio than the 1-2 years often quoted in the personal finance world. You can arrive at this 5 to 10-year figure until Sequence Risk becomes less of a problem through at least two different routes.įirst, if you’re unlucky and you retire at the peak of the market right before a recession and bear market hit then it might take about 10 years to get back to the old peak again. And yes, I’ll also explain what the heck that Mandelbrot title picture has to do with that! □ Let’s take a look…ġ: Regress Safe Withdrawal Rates on realized portfolio returns Nevertheless, in today’s post, I want to present three different modeling approaches to shed light on the question. The 10-year horizon indeed has some empirical validity, but I also want to point out a big logical flaw in that calculation. I would normally resist giving a specific time frame. In other words, when is the worst over? When are we out of the woods, so to say? A lot of people are quick throwing around numbers like 10 years. Is there a time when we can stop worrying about Sequence Risk? ![]() I’ve been mulling over an interesting question I keep getting: Welcome back to a new installment of the Safe Withdrawal Series! If you’re a first-time reader, please check out the main landing page of the series for recommendations about how to approach the 38-part series! ![]()
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