When Can We Stop Worrying about Sequence Risk? – SWR Series Part 38

July 15, 2020

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!

I’ve been mulling over an interesting question I keep getting:

Is there a time when we can stop worrying about Sequence Risk?

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. I would normally resist giving a specific time frame. The 10-year horizon indeed has some empirical validity, but I also want to point out a big logical flaw in that calculation. Nevertheless, in today’s post, I want to present three different modeling approaches to shed light on the question. And yes, I’ll also explain what the heck that Mandelbrot title picture has to do with that! 🙂 Let’s take a look…

1: Regress Safe Withdrawal Rates on realized portfolio returns

You can arrive at this 5 to 10-year figure until Sequence Risk becomes less of a problem through at least two different routes.

First, 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. 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. 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 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.

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 1871 and 1990 and then regress that on the realized returns. As you can see in the table below (left panel) you get statistically significant estimates, but a relatively poor R^2. Only about one-third of the variation in the SWR is accounted for by the (geometric) average annualized portfolio return over the retirement horizon. The reason is that the returns early in retirement have a much larger impact on retirement success than the later returns. 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. And also much higher t-stats.

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. Also, recall that a t-stat with an absolute value above 2 is normally considered statistically significant.

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). Reporting the Newey-West, heteroscedasticity-adjusted t-stats to account for overlapping windows.

The conclusion of this exercise is that only about one-third of the variation in the Safe Withdrawal Rate is (statistically) explained by the average return over the retirement horizon, while the other two-thirds come from the sequence of returns. That’s a very powerful result: the sequence matters roughly twice as much as the average return! That’s why Sequence Risk is such a big deal; success or failure of your withdrawal strategy hinges mostly on the returns during the first ten or so years of your retirement.

So, should I now conclude that Sequence Risk is over and finished after 10 years? It looks like the first ten years pick up a majority of betas: 0.286+0.190=0.476 vs. the combined 0.282 of the remaining 20 years of beta estimates. Unfortunately, that would be a complete misinterpretation of my regression result, though. The reason is that after those ten years have passed, and I do another SWR calculation, this time of the remaining 20-year retirement horizon and I regress that SWR on the returns of the remaining 20 years I get the results in the table below, see the panel on the right.

Add the same calculation for a 20-year SWR regressed on its four 5-year windows (and years 1-10 are water under the bridge).

Well, after the first ten years of returns are “water under the bridge” the next 10 years (i.e., years 11-20) of returns are now crucial in determining the success over the 20-year remainder of your retirement. So, remember the Mandelbrot picture where you can zoom in and find ever new Mandelbrot shapes? Or any other self-similar images, e.g. the Koch snowflake, etc.? That’s a bit like Sequence Risk. After the first 10 years passed, the subsequent 10 years are now the main source of Sequence Risk, even though previously they were much less important.

Thus, Sequence Risk will still be an issue even 10 years into your retirement. Strictly speaking, Sequence Risk will be around until you’re done with your withdrawals.


But maybe we should look at a different kind of calculation. Forget about readjusting the SWR after 10 years. Simply look at what kind of portfolio values I would need to see after ten years to get some reassurance that my initial 4% withdrawal plan will still work over the remainder of my retirement. Which brings us to method 2…

2: Success/Failure probabilities conditional on the 10-year portfolio value

Let’s assume we have a 30-year retirement horizon, a $1,000,000 portfolio invested in 75% stocks and 25% bonds and a 4% withdrawal rate ($3,333.33 per month) always adjusted by the CPI. If I run historical simulations with starting dates between 1871 and 1990 (and thus I use portfolio return data all the way to 2020), I get a vast variety of possible outcomes after 30 years:

  • 1.8% of the cohorts completely run out of money
  • An additional 5.5% end up with only about between 0 and $250,000
  • But likewise, almost 50% of the cohorts more than double their initial nest egg in 30 years! The highest final net worth was over $9m, and that’s adjusted for inflation!

By how much can we cut down this vast uncertainty if we are now 10 years into our retirement? By a lot! That’s what I do in the chart below. I take all portfolio time series and I put them into different buckets depending on what range they fell into after 120 months. And then look at the probabilities of the 30-year final portfolio value conditional on falling into different buckets at the 10-year mark. And just for completeness, I also include the unconditional distribution over all the different simulations regardless of their 10-year value, see the bars on the right.

The probability distribution over 30-year outcomes, conditional on the 10-year portfolio value. Assuming a 75/25 S/B portfolio, $1m initial portfolio, $3,333 monthly withdrawals (4% annual).

What do we find here? The 10-year portfolio value gives you a pretty good indicator on the 30-year outcomes:

  • If after 10 years your portfolio has dropped by more than 50% (in CPI-adjusted terms) you can pretty much kiss “Good Bye” to the idea of vast riches at the end of your retirement. But I was positively surprised that the risk of running out of money increased from 1.8% (unconditionally) to “only” 13.9%. So even with extreme financial stress, you still have a large chance of making it for another 20 years! But chances are you will exhaust more than 50% of your initial capital. That’s fine for traditional retirees, probably not acceptable for early retirees who have to tag on another 20-30 after that initial 30-year window!
  • If you’re down between 25 and 50%, you still have a 5% chance of running out. but quite surprisingly, you also had a 10%+ chance of getting all the way up to $2m at the end of the horizon!
  • If your portfolio dropped only slightly, by 0-25% after 10 years, you still had a minute probability (0.6%) of running out of money. But you also face a 10%+ probability of severely depleting your portfolio (0-$250k left after 30 years).
  • If you manage to preserve or even slightly grow your capital, you’re definitely out of the woods. There were no historical instances where your portfolio fell into the $1-1.25m range after 10 years and you still run out of money. Even better, there were no historical cohorts where the portfolio dropped to below $250k after another 20 years!
  • And finally, if after 10 years you grow your portfolio by more than 25%, you should definitely splurge a little bit more. Or “risk” a vast overaccumulation of assets after 20 more years! 🙂

So, long story short, if after 10 years you still preserved your capital or at least 75% of it, you should be safe from completely running out of money after 30 years. But again, you still face a vast risk of where your final portfolio will eventually land. That’s due to both average future returns and – even more so – the sequence of returns!

And by the way, this is just the outcome for a generic 30-year retiree without any supplemental cash flow, another positive (pensions, Social Security) nor negative (additional health expenses, nursing home, etc. later in retirement). Everyone who’s not like this academic, generic retiree would have to do his/her own analysis!

3: Fail-safe withdrawal rates as a function of the horizon (and equity valuations)

Another way to look at the “are we out of the woods?” question is to simply calculate the fail-safe withdrawal rates as a function of the horizon. Then, calculate the capital that’s necessary to sustain that retirement horizon.

Specifically, let’s construct the following example:

  • Same allocation as before: 75% stocks (S&P 500) and 25% bonds (10Y U.S. Treasury benchmark bond)
  • Zero dollars final value target
  • No additional cash flows
  • A horizon of 60 to 720 months in 60-month steps…

For example, over a 720-month horizon, the fail-safe withdrawal rate would have been right at about 3.25%. So to sustain a $40,000 a year withdrawal, we’d need $40,000 divided by 0.0325, so it would take $1,229,000 in fail-safe capital to make it through the worst history has ever thrown at us:

Capital needed to guarantee a $40k a year withdrawal plan even for the worst possible historical cohort (1871-2020).

One could now use this chart to get some guidance on where our portfolio value should stand 5 or 10 years into retirement to still guarantee the remainder of our retirement.  But here’s the bad news: if you go from 60 years to 55 years and 50 years, the failsafe capital necessary to sustain a $40k a year withdrawal goes from $1.229m to $1.215m and $1.194m. This approach doesn’t give you much breathing room. The 50-year safe capital level is only about 3% below the 60-year number!

How about traditional retirees with a 30-year horizon? Well, thanks to the shorter horizon, you’d start with a failsafe initial capital of $1.047m over a 30-year horizon. 5 years and 10 years into retirement that’s down to $990k and $898k respectively. In other words, if after 10 years you’ve lost only less than 14% of the initial capital (adjusted for inflation!) then you should still be 100% safe.

Well, that doesn’t really sound too comforting. It means that if we lose even a bit of our initial retirement stash after 10 years, should we now be scared of running out of money? Well, the good news is that this approach is likely overly cautious and conservative. Certainly, if you lose less than a few percents you should be 100% super-safe. But it doesn’t mean that if you had lost 14.0001% after 10 years that you should be hair-on-fire scared about running out of money.

You see, the extreme market peaks that pose a severe retirement and Sequence Risk challenge occur only every 30 years or so: 1929, 1965-68, 2000 (and maybe, maybe 2020, but let’s hope not!). So, if you had the misfortune of retiring with a 60-year horizon right around a multi-decade market peak, it’s not too likely that 10 years into retirement you’re at another 1929-like market peak. So, calibrating your new 50-year retirement safe capital number to the historically worst outcomes seems wayyyy too conservative.

How do we fix this? We should factor in equity valuations! For example, if you had retired in 1965, then 10 years into retirement would put you right at the bottom of the 1975 recession and bear market. The S&P 500 was more than 30% from its peak (inflation-adjusted). Why would you then use the fail-safe withdrawal rate that’s calibrated to the extreme market peaks again?

Rather, we should factor in equity valuations! And that’s something we can easily do with the Big ERN Safe Withdrawal Rate Google Sheet. See Part 28 for more details.

Google SWR screenshot from the tab “Parameters & Main Results”. There’s a section that computes the historical fail-safe WRs conditional on the equity drawdown! Just what we needed!!!

Specifically, I grabbed the fail-safe SWRs, conditional on the relative equity valuation (i.e., relative to the most recent S&P 500 all-time-high). Then calculated the failsafe capital needed (=40,000/SWR) for all the different horizons and equity drawdown figures (0-50% in 10% steps) and plot the whole thing in the chart below.

The same chart as above, but add the fail-safe capital needed conditional on equity drawdowns!

Now we’re talking! If you’re 10 years into a 60-year retirement the fail-safe capital levels can be much reduced if the market is currently well below all-time-high. For example with a 30% drawdown, $899k is the safe capital level. If you’re a traditional retiree and you are 10 years into retirement, you’ll be fine with “only” $667k to sustain the remaining 20 years of $40k/year withdrawals. These are much more palatable “out of woods” targets for your portfolio on your 10th retirement anniversary!



In retirement, you’ll always face risks. The biggest concern for me personally and a lot of other retirees I know would be spending uncertainty because we’ll never know our old-age expenses, especially health and nursing home expenses until we actually get there. But even for flat, perfectly foreseeable expense patterns you will always face Sequence Risk until you’re down to your last and final withdrawal. So, we can’t really declare victory over Sequence Risk. Ever! And certainly not after only a few years into retirement.

Even if you try to answer a question like “will I know after 10 years whether I will make it?” it’s not trivial at all. It’s an inherently mathematical and quantitative issue. It’s not about whether you overcome the risk of running out money after observing 10 years’ worth of return data. It’s about what portfolio value you need to target to eliminate (or at least minimize) the risk of failure. So, general guidance that “Sequence Risk is done after 10 years” sounds like a bunch of mumbo-jumbo to me.

Ideally, I’d want to use the thought process in model 3, similar to what I proposed in Part 37 a few months ago. Whether it’s 10 months or 10 years into retirement, the mathematically and logically sound approach is to pretend it’s your first day in retirement all over again; look at your current portfolio value and your horizon but also the current equity valuations and check what’s a safe withdrawal rate now. Think of your retirement as in the movie “Groundhog Day”: every day is your first day in retirement again. And since this is your new imaginary first day in retirement again, you face a renewed Sequence of Return Risk again over the next roughly 10 years! Sorry: Sequence. Risk. Will. Not. Go. Away!


Updates 7/15, 8 a.m.:

  1. I wanted to but forgot to give a shoutout to Andrew Chen and his podcast and blog “Hack Your Wealth“. We talked about some of the issues of Withdrwawal rates and Sequence Risk, especially the question of “when can I stop worrying” on his podcast: Part 1 and Part 2. Also available as a Youtube video!
  2. Some people pointed out that today’s post seemingly contradicts the usefulness of glidepaths (see Part 19 and Part 20). I don’t think there’a a contradiction. As I’ve pointed out in the earlier posts, a GP didn’t work so well in a long, drawn-out event like the 1960s to 1980s. Also, if the market keeps going up during your first 5-10 years of retirement you might benefit from what I called an “active GP” where you don’t perform the bonds ->stocks shift until the market actually drops. Also, remember that Sequence Risk works both ways. It can hurt you and it can help you. The folks in method 2 that depleted their portfolio down to $500k after 10 years would hope for the benevolent Sequence Risk: high returns for the next 10 years because they find themselves at the bottom of a bear market. And to benefit from that (hopefully) impending rally, you’d be best positioned with 100% equities, not 75/25.


Thanks for stopping by today! Please leave your comments and suggestions below! Also, make sure you check out the other parts of the series, see here for a guide to the different parts so far!

Picture Credit: pixabay.com


65 thoughts on “When Can We Stop Worrying about Sequence Risk? – SWR Series Part 38

  1. Doesn’t this contradict with the idea of glide paths? If every day in retirement is similar to first day of retirement, this suggest portfolio allocation should only be based on retirement horizon.

    1. kind of but not really. as your horizon shrinks, your Sequence risk drops, so you can afford to have more in equities. This aligns with the glide path reverse tent (more bonds before/after retirement with increasing equity going into retirement but after 5-10 years).

      1. Not true. If your horizon shrinks for early retirees from 60 years to 50 years you still have a lot of SR at that time.

        The GP only works if the crash happens right after retirement. If the market bounces around sideways for another 10 years and THEN crashes when you’ve reached 100% equities then you have Sequence-Risk-SQUARED!

        1. I think in the update you meant “bond -> equity”. I don’t think you really addressed the issue here. “active GP” is more of a market timing/portfolio allocation strategy than a glide path.

          I think for early retires, glide paths doesn’t make sense, because, as you said, SoRR might hit just after your bond tent is behind you. I think a better strategy is to have flexibility to come back to work if SoRR hits.

          I think your idea of CAPE based withdrawal rate fits better with this insight. I am planning to use SWR=Average(CAPE-Yield, 3.5%)

          It captures the valuation intuition well. And with current bond rates, only way seems to be having high equity alloc (75%), some gold (10%), and rest in treasuries. And with above mentioned flexibility, I am planning to quit once i hit my number.

          Thanks for all the hard work by the way, i benefited immensely,

          1. GPs are not a panacea, neither for traditional nor for early retirees. As I showed in Parts 19, 20, they do help a little bit even in a 60-year retirement.
            See first large color-scale table in Part 19:

            I also agree that the CAPE-based SWR is a nice way to make the point of the self-similarity. With the CAPE-rule you’re constantly exposed to the whims of the market. Not just during the first 10 years! 🙂

    2. No. As I’ve pointed out in the other comment: The GP works if the market crashes right after retirement. If the market moves sideways for a number of years and then crashes when you’ve reached 100% equities you will notice that Sequence Risk will still haunt you 10 years into retirement. In fact, you make the best case FOR my line of reasoning that SoRR is always around!

  2. Your 3rd chart (the colorful one with 30yr outcomes conditioned on 1yr outcomes) skips $500k-$750k.

  3. Big ERN,
    Nice article. Love the way you took the multi-parameter math and distilled it down. At the end of the day, SoRR never goes away, the time horizon just changes. And with less time, there is a shorter time time for possible recovery. You still have SoRR with a 1 year retirement (be careful during months 1-3) and recovery odds can be dismal.

    Any chance of running the correlation model with shorter (2 or 3) year increments (instead of 5 yr)?

    1. Thanks!
      If you do shorter windows, say 10 windows of 3Y each or 15 windows of 2Y each you’ll get even better R^2 but not really more insights. You’ll see that the fist few windows, spanning the first 10-12 years will account for the almost the entire SWR volatility. 🙂

  4. Thanks Big Ern!
    I love your SWR series and I especially love it when you take a deep dive into SoRR. As an early retiree it is my biggest worry, but you have provided a framework that helps me sleep at night (except when my 2 DTE SPX short put options are below the strike price after the first day!)

  5. So if 5 years is kinda “the number” that you have to weather, do you recommend having that 5yrs living expenses set aside in secured investments like GIC’s or since the “damage” isn’t as great as first thought – just push all the chips in and play those relatively good odds? I realize no one has that crystal ball but I didn’t pull the trigger on the big Spring dip and I keep waiting for that secondary dip that seems like it might never come the way the market seems to shrug off every piece of bad news.

    1. Bonds tend to be a good diversifier. As I’ve written in Parts 19/20, there’s a rationale for having some more bonds initially and then shift to more equities over the first 10 years.
      The hope is that you’ll have enough cash at that time to easily accommodate your target WR. But if you’re again just only on the edge of making it after 10 years, watch out! As I showed in Part 38 here, you’re facing SoRR again for the subsequent 10Y!

  6. Nice post. This is the series that just keeps giving; with every new post adding to the body of knowledge. Thanks for doing this.

  7. Thanks Big Ern. Love your detailed work! In light of this, why does anyone talk about the 4% rule and not just call it the 3.25% rule for FI? Afterall, 4% has a non-negligible probability of failure, but 3.25% never fails per your analysis. In other words, if a 25yr old wants to retire on $40k/yr and already achieved saving a $1mm portfolio, why is the prevailing thought “congrats! you are FI now and you can retire” instead of “great job! now keep working and let your portfolio grow for just ~2-5 more years until your portfolio is $1.25mm and THEN you will be FI”

    1. Well, 3.25% certainly is a floor for someone with a permanent, flat-line spending pattern. It might be lower if you have an increasing spending path.
      But your (initial) SWR might be well above 4%, maybe even above 5% if you’re 50 and you expect large pensions that will eventually reduce your withdrawals.
      So, I always say “I have more a problem with the the word ‘Rule’ than the 4% Part!” 🙂

  8. I have read through most of your series on SWR over the last couple years. While I am continually impressed by the sophistication of your thoughts and models I can’t help but think the inherent error incurred from extrapolating on the underlying data is much larger than the error in the models plumbing themselves. I am left thinking you want to be about 3.25-is percent withdrawal rate to be safe-ish acknowledging that you may have to alter spending or income in some extreme corner cases. And that safety itself isn’t something you can engineer your way to. There are always corner cases…

    I know math is your strong suite as evinced by the fact that your analysis is unique on the interwebs, but I would also appreciate a companion series to your SWR series that is geared toward addressing the “now that we have an exhaustive understanding of the math” lets dive into the practicalities of how you make decisions re:FIRE…strategies and tactics you can deploy along the way….or perhaps how to navigate decision making re:FIRE in an uncertain world.

    At any rate – appreciate your work. 🙂

    1. @Jdoggy1, plenty of other folks to give that view. Retirement manifesto, Kitces, GoCurryCracker, mad fientist, caniretireyet etc or other like Todd Tresidder if you want a cash flow model.

      Two good recent ones:


      End of the day there is no surefire, pun intended, way of doing this. Just manage the risk to a level where you won’t worry about it is my personal approach.

      1. Thanks Dan – I have also read a couple of those links. Some good stuff there. The reason I suggested a similar approach to Ern is that he in particular is blessed, or cursed by a thought process that reasons over the math of early retirement in an uncommon way. As a result, I think his deeper examination of the soft reasoning that ultimately wraps the math of a decision to retire early would be particularly interesting (at least to me). It isn’t so much that writing about what I suggested above was novel per se, but unique in the sense the other authors don’t have the same mathematical understanding of the plumbing as ERN. HTH

    2. I don’t think I blindly extrapolate the data. That is what Bengen, Trinity and a lot of the FIRE community do.
      I’m always the first to point out that the equity market is not a true random walk and we should take into account equity VALUATIONS.
      So, I think it’s proper to extrapolate the past if by “the past” we mean times when equities looked equally expensive.
      If you believe the future will be even bleaker than the past (conditional on being on an expensive market top) you can certainly do that. But what do you want to do now? It takes a model to beat a model. What alternative method do you propose to someone who needs to decide how much to withdraw?

          1. Thanks. I had not read that.

            Seems like limitation of the tool. MC with mean reversion is a known concept. I couldn’t find an existing tool but formulas are available. Maybe I’ll give it a shot.

            The reason i think simulation would be superior to historical analysis is that there aren’t enough samples in the history similar to today (very low yields and very high P/E).

            1. True, MC simulations will give you a higher # of observations. But observations of what? It could be a “garbage in garbage out” problem.
              But said, I’ve thought about running MC simulations using a vector error correction model that takes into account valuation and mean reversion. But I’m too busy being retired! 😉

      1. I am not taking exception with the models you put together they seem as well reasoned as they can be. My observation isn’t a criticism. At least for me, (having recently punched out) the calculous was more involved than running the numbers and coming up with a model with 0% failure rate, or some acceptable alternative threshold. There was a lot of soul searching and reasoning around the decision. Some of the consideration was around “what if the present path is worse than any in series events” – and that is a part of it. But there was a whole lot of consideration around things things like how hard it would be to rejoin the work force if I wanted..or the significant other. etc etc.

        And I get these type considerations aren’t the thrust of your blog. Just suggesting there would be some useful and (I think) interesting content/stories there. But then again, maybe not.

  9. Hi Big ERN,

    I am impressed with the DIY analysis and graphs and charts you performed in your blog posts such as

    Like many readers I cannot get enough of your DIY analysis.

    Can you recommend any blog , podcast , book , video etc that does the same type of DIY analysis and also could teach us how to perform similar DIY investment analysis ?

    Thanks a million for all you are doing.

    1. Thanks for the kind words! That means the world to me.
      Well, I have the “links” page on my blog with fellow blogs and book suggestions.
      I don’t think anyone exactly approaches personal finance the way I do, just like nobody approaches retirement the same way Fritz (Retirement Manifesto) does. So, if you want more of my exact style, you just have to wait 2-3 weeks for a new post! 🙂

  10. How does the impact of the US govt running up huge deficits and printing money factor into this analysis? What about declining future population growth? What about the fact that US equities benefited greatly from the bombing of most foreign productive capacity during WW2 resulting in enormous competitive advantage for at least 40 years that is baked into past stock prices? Is it truly safe to assume past patterns will repeat? It seems that large exogenous events are assumed away here – or the impact of movements away from trend. Or is this addressed somewhere in the first 37 issues? But don’t get me wrong, I love your stuff…

      1. and don’t forget inflation.

        the 4% rule failures (historically) are for those retiring just before times of high inflation…e.g. late-1960s retirees.

        we’ve had, what, 30 years of relatively low inflation?

        so is it time for a “return to the mean” on that metric? 🙂

          1. Hi ERN, I can see that someone in your situation would be concerned about a Japan-style historical 30-year period going forward for the US, — but for someone who is: age 64, soon-to-be-traditional-retiree, renter paying $3300/month Long Island, NY, rent goes up 5%-6% per year, local home condo prices very expensive, currently due to pandemic and my retirement proximity has 87% of portfolio in cash / bonds, eventual glidepath to 50/50, pre-tax private non-cola pension next year of $22k / ~$15k after tax, ~32k soc sec at age 66, planned 3% swr, no planned legacy – wouldn’t no inflation or low rate of deflation actually benefit my situation? – my large cash allocation would be worth more, home prices would become more affordable for me to buy, my private non-cola pension would gain or not lose value…. ? – Thanks.

            1. Good question.
              Very generally speaking, rental rates should become cheaper in a low-inflation and low-interest-rate environment. But there is also the possibility that due to the low rates, speculators bid up the prices of real estate assets if there’s nothing else yielding any income these days. I suspect some of that is going on in NY. I wouldn’t want to be a renter there. Any plans to move? Camas, WA is very nice! 😉

  11. Most of your posts make me think early retire is a bad idea and a lot riskier than keep working. “THank you” for that !

    1. Continuing to work does mitigate financial risk. Doesn’t mitigate other life risks though, like risk of regret and running out of time.
      Big ERN does shine a light on things others don’t, and sometimes that makes it feel like a much larger task.
      I’ve come to think of this as a spectrum of lifestyle planning. For example, both my wife and I chose to stop climbing the corporate ladder years ago so we had time for us and family. Yes, we’ll end up working a little longer but I couldn’t imagine the trade off.
      There are many possibilities, make it your own!

  12. Dear early ERN,

    I’ve been a 2+ years reader of your blog and a lot of your posts are incredibly awesome! Clearly, you have been blessed with a skill to simplify some serious financial engineering concepts in way non-financial folks will understand. Your synthetic roth IRA strategy blew me away and I am not even residing in the US so that gives you an idea of how appreciative I am of your financial acuity. Out of curiosity, I need to ask a question! What is the targeted audience on the SWR series? The deeper you dive into SWR the more I am wondering how typical early retirees are reacting to this!? I’m a big fan, but the deeper it goes the more I am wondering how can Joe who’s looking forward to exit the workforce in his 40ies can grasp the practicality of it? Perhaps it is not intended for him ?! Anyway, I am very grateful for those practical nuggets you gave us through the years!

    Thanks a bunch!


    1. The series and most of my blog is for an audience of one: me. These are my notes and my thoughts. But I thought I share this in case other people are interested in this. A lot of people are.
      Also, keep in mind that a lot of people can use my SWR Google Sheet Tool without understanding all the math behind it. I drive a car without understanding all the mechanical stuff behind it! 🙂

  13. Big ERN,
    I am also starting to be concerned whether it’s a good idea to retire even I would love to do it any day. I think I’m in the same boat as Mark in this case. But then I remember that you mostly base your mathematical PhD level calculations on the value of portfolio and exclude SS benefits, so it helps me to add some positive light because I believe that the gov’t will not eliminate SS ever considering that the economical inequality has widened drastically over the last 2-3 decades and the middle class will not be cut out of the line to receive benefits.

    BTW, I also think that extreme peaks are more frequent now. You said 2020 after 2000. Why did you omit 2008-2009 in this sentence?
    “You see, the extreme market peaks that pose a severe retirement and Sequence Risk challenge occur only every 30 years or so: 1929, 1965-68, 2000 (and maybe, maybe 2020, but let’s hope not!).”

    Sure I definitely hope the market of 2020 will survive even though it reflects the opposite view of current economics.

    1. I think it would be a mistake to argue that one can never retire. If people with a 3.25% WR could have retired in 1929 without running out of money for 60 years, then we should be safe today.

      I mentioned the market peaks that were devestating from a Sequence RIsk perspective. 2007 was scary in real-time, but eventually recovered very quickly. As much of a drop as it was, the recovery was swift and thus the 2007 market peak was relatively benign from a Sequence RIsk point of view. 🙂

  14. hi BErn
    Thanks for this inspiring post – and the awesome thought process behind it. I’d like to add – or rather rephrase – two ideas or believes to the numbers: first, there is NO certainty, no matter how much number crunching is done . As you so correctly point out it’s close to 99.5% certain. But no matter what you do, no matter how much you have, there’s always the possibility of an adverse outcome.
    An the second: I don’t necessarily consider all this SWR/ SR thinking to retire early, but if the comany I work for should consider me to be too expensive I want to know my way out! Being European, I’m used to lower expected inflation, bond yields and returns. Having an idea how much will most likely be enough and thus how to move forward gives me peace of mind.
    So again thanks a bunch for providing these scenarios for us to make the best use
    Grüsse as der Schweiz

    1. Very well said. Even my SWR is not 100% safe because there’s always model uncertainty. The future might look different. But I don’t want to compound risk: SWR risk plus model risk would not be palatable in a 50+-year retirement.
      Gruesse zurueck in die Schweiz! Meine Mutter hat viele Jahre bis zu ihrem Tod in Reichenau am Bodensee gelebt. Gleich gegenueber! 🙂

        1. Not sure – I had a hunch and tried it. Didn’t check to see if it’s published anywhere.

          Much time has been spent as systems architect / engineer, so identifying gaps in tools and processes is in my nature. Formally in IT, but the practice can be applied to many domains. It’s how I was able to get free Amazon Prime for a few months before they crudely but effectively patched the issue.

  15. Hi there, greetings from Germany.
    @ERN: I got an idea especially after your final graphics: if market recovery is such reliable after market drops (see the huge impact on fail save capital needed after losing market valuation in 10%-steps), wouldn’t it be sufficient to just refer to the last market peak and define 3 % of it as your withdrawel, even if the market peak was way higher (or long gone)?

    Your annual spending could then be much higher than using e.g 3,5%-4% of portfolio value after the market drop, but since 3 % represents the “always and forever safe” withdrawel rat, it should just do the job.

    Sounds like a simple but reliable rule to me, please correct me if I’m wrong.

    1. Well, that is the assumption already in the traditional 4% rule. You use 4% of your initial portfolio, then adjusted for inflation. That might wipe out your money. 3.25% seems to be the safe rate over any horizon. 3% is almost a bit too conservative.

      1. Yeah, sure (and 3,5% with an equity glide path 😉
        My point was that during bear markets people can just take 3.25 % of their last max. portfolio evaluation before the crash (and won’t have to worry that 3.25% of todays portfolio is not enough).
        Of course this is a direct implication of that famous 4%-rule, but a handy one which allows for better planning, right?

    1. Qualitatively you have the same results. If you have a 45-year horizon and you made it through the first 10 years, you now face a 35-year horizon with the Sequence Risk again.
      I don’t advise people use 30/70. You can check the simulations in the Google Sheet (Part 28). The SWRs suffer when you have such a low equity portion.

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