*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.*

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.

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.

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:

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.

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.

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!

### Conclusions

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.:

- 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!
- 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*

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.

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).

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!

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,

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:

https://i1.wp.com/earlyretirementnow.com/wp-content/uploads/2017/09/swr-part19-table011.png?resize=838%2C734&ssl=1

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! 🙂

Hi Big ERN, great post. Have a question. You say that GPs only work if crash happens right after retirement. However, from a practical perspective, one cannot know that in advance. So,

a) is the default option to then pursue the GP anyway?

b) If so, then say the crash happens during the transitionary period e.g. year 5, what are you suggesting based on your analysis?

My thought was to go for the glide path regardless. And shoft from 60/40 to 80/20 over a 10 year period to protect against SR risk either happening at the start or later on in the crucial 10 period. This will minimise to some extent the SR squared that you described in your example above, either happening say at Year 5 of 10, or Year 10? Or am I missing something? Would appreciate your views. Thanks.

one could leave the initial asset allocation in place and the start the GP only when equities tank. That’s what I call “active GPs” in parts 19/20.

Thanks for clarifying. So just to get a better understanding – I stay at 60/40, but when equities do tank, we start gradually increase our stock asset allocation over a 10 year period e.g. 60/40 to 80/20 will involve .5% increase every year. And we do this by selling our bonds generally speaking. Have I got that right?

I simulated different speeds, between 0.2% and 0.5% per MONTH (not year).

Also notice that the rebancing and withdrawals are down monthly. Sometimes you’d sell all bonds and leave the portfolio untouched otherwise. Sometimes, when the stock market tanks really badly, this would involve selling bonds for living expenses and ADDITIONAL rebalance bonds->stocks in the portfolio.

Thanks for clarifying. As an expat we only have access to ETFs and rebalancing monthly would really increase costs. Any advice?

Please see the latest installment of the SWR Series (Part39) where I talk about the rebalance frequency. You don’t have to do the rebalance that often and SWRs are still the same as under the monthly rebalance rule.

Also notice that merely withdrawing from the currently over-weight assets is already a way of rebalancing that doesn’t require any additional t-costs. 🙂

I’m confused by this answer. Does the “active” GP in parts 19/20 always reset to the initial allocation when the stock market hits a new high, or does it merely pause the glidepath during months when the market is at (or close to at) a new high.

Resetting to the initial allocation makes a lot of sense to me. But it wasn’t at all clear from reading Parts 19 and 20 that that is how you ran the test.

It’s a ratcheting system where you keep last month’s allocation if you hit another high. One could also make this “extra-active” and reset to the max again if you hit another ATH for equities. But I didn’t go that far.

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!

SoRR is always around, but weaker. Running out of money after 40 years retirement is ‘better’ than running out after 4 …. So early SORR is the killer here if you measure failure as max damage done (shortfall years). Implies risk should be minimised at retirement.( … and possibly flat or rising thereafter?). Say goodbye to age in bonds.

You won’t run out of money after 4 years with the 4% rule. You merely set things in motion that will make you run out of money after 28 years if things go wrong initially due to SoRR. 🙂

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

There was a typo. The yellow bars are 500k-1m. Thanks for pointing that out! 🙂

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)?

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. 🙂

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!)

Haha, those are stressful times. Hopefully only about 2-3x a year! 🙂

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.

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!

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

Thanks, Al! 🙂

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”

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!” 🙂

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. 🙂

@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:

https://www.theretirementmanifesto.com/what-ive-learned-from-two-years-of-retirement/

https://the-military-guide.com/im-59-5-years-old-and-done-writing-about-my-money/

I

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.

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

Nice links! Thanks for sharing!

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?

How about monte carlo simulation that uses historical volatilities/correlations but forecasted returns. I’d base real stock returns on forward p/e and use current bond yields. Like this:

https://www.portfoliovisualizer.com/monte-carlo-simulation?s=y&fullHistory=true&allocation4_1=15&adjustmentType=2&allocation2_1=35&smoothingRate=75&historicalVolatility=true&volatility=12.0&endYear=2019&years=40&frequency=4&mode=1&inflationAdjusted=true&inflationVolatility=0.0&sequenceStressTest=0&mean4=1.5&inflationMean=1.5&mean3=1.5&mean2=6.5&mean1=6.5&startYear=1972&bootstrapModel=1&inflationModel=2&customIntervals=false&adjustmentPercentage=4.0&dof=30&adjustmentAmount=35000&allocation1_1=40&allocation3_1=10&circularBootstrap=true&simulationModel=4&distribution=1¤tAge=70&timeSeries=1&bootstrapMaxYears=20&asset1=TotalStockMarket&asset2=IntlStockMarket&asset3=Gold&asset4=LongTreasury&historicalCorrelations=true&returnList=0%2C+2.5%2C+5%2C+7.5%2C+10%2C+12.5&lifeExpectancyModel=0&bootstrapMinYears=1&meanReturn=7.0&percentileList=10%2C+25%2C+50%2C+75%2C+90&rollingAveragePeriods=3&initialAmount=1000000

It still doesn’t do a good job at simulating the type of mean reversion observed in the data. See my post on “How much of a Random Walk is the Stock Market?”

https://earlyretirementnow.com/2018/01/24/random-walk/

The correlation of neighboring 15-year return windows. That doesn’t materialize in a MC simulation.

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).

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! 😉

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.

Yeah, maybe I will tilt the focus of my blog to address those issues. Or maybe not. It might not be my expertise. 🙂

Hi Big ERN,

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

https://earlyretirementnow.com/2017/10/25/returned-over-100-percent-year-to-date-still-not-buying-it/

and

https://earlyretirementnow.com/2017/05/10/lump-sum-vs-dollar-cost-averaging/

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.

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! 🙂

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…

These are all reasons I’m probably going to “worry” about risk forever. Not just the first 5-10 years.

All that could potentially knock off 0.5-1.0% from your annual portfolio returns.

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? 🙂

Good point. I’m worried about both extremes: a return of inflation shocks, a la 1970s. But a consistently low inflation (Japan for the last 30+ years) would be even more damaging.

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.

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! 😉

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

Oh, no! I hope not many people take that away from my posts. I’m having a great time, living the dream of FIRE. 🙂

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!

Very well said. Working too long is a risk too. In the words of Dietrich Bonhoeffer:

“Time is the most precious gift in our possession, for it is the most irrevocable.”

That would be a misinterpretation of my work. I retired. Nothing is without risk. Working too long and missing out on life is a risk, too. 🙂

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!

JD

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! 🙂

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.

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. 🙂

Isn’t $40,000 divided by 3.25% = $1,230,769?

40/1229=0.032546786. The 3.25% quoted was rounded. The actual, historical true SWR was a little bit higher.

But even then, it makes only a small difference of not even $2,000. 🙂

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

Hille

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! 🙂

spintwig here – testing an idea I had that might allow me to comment as BigERN 🙂

It worked!

Now, that’s scary…

Indeed that is scary.

Is this “feature” widely known about and/or (ab)used I wonder?

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.

OK, if I ever have hack into somewhere, I know who to call! 🙂

Well, if I ever write something really dumb in the comments section, I’m going to blame it on spintwig. 🙂

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.

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.

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?

OK, that sounds like a good plan! 🙂

So what happens in a 45 year horizon? Or a lower asset allocation. 30/70 or 35/65?

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.

As an engineer I also like mathematical models. But only as long as they are easy to understand and to apply and are consistent with common sense.

This is definitely not the case with sophisticated SWR computations, based on Monte Carlo simulations with the final conclusion:

**”Sequence. Risk. Will. Not. Go. Away!”**

Thus, keep worrying forever during the best time of your life?!

As this cannot be the final answer, I kept searching for better answers and think I found one in this article of the high quality CFA educational blog:

http://www.cfainstitute.org/en/research/foundation/2019/cash-flow-focus-endowments-trusts

According to this, the critical withdrawal rate of eternal endowment trusts with mandatory capital preservation can be determined much better through the only slightly fluctuating “investment cash flows” or their “fecundity” instead of market valuations. This fecundity is based on only one robust estimate of 130% of the average of all dividends in the equity index.

As this will preserve the capital base under all circumstances, you only need one more decision for determining your worry-free SWR, if and eventually when you want to have spent your capital. The rest is simple and precise algebra. And it is consistent with the good advice to live agile with the flow in retirement.

The rationale behind this holy grail of determining SWR, ending your worries about SoRR for good, is that dividends are determined with taking all insider knowledge available into account. Thus, it is the best approximation imaginable based on corporate crowd intelligence, focused on the prosperous survival of the corporate world, Not just your own one. It adapts immediately to the flow of all events, including regime and structural changes, you may only detect decades later or never with other approaches.

Even for equity only portfolios without bonds, the withdrawal rate determined in this way fluctuates much less than if the rate for traditional equity/bond portfolios was determined on the basis of unreliable market valuations.

Understanding this approach also makes it obvious that presumed diversification with all non- or low-yielding treasuries, bonds, gold, commodities or the like makes no sense as they only reduce the withdrawal rate with no other advantage. However, it becomes obvious how extremely valuable it is to search for and allocate non- to anti-correlated alternative assets with equity-like levels of return in the long-term, such as active trend or long volatility, smoothing and increasing the withdrawal rate at the same time even more.

Have you considered such cash flow based determination of SWR here already?

Notice: I never meant that you’ll always WORRY about running out of money. You will always be subject to SoRR.

So, if you budget $40k a year and your portfolio runs really well over the first 5 years and the portfolio is at 1.5x target you will no longer have to worry about running out of money at $40k a year.

BUT: if you now raise your withdrawals to $60k and thus start a “new” retirement from that point on, you darn sure have to worry about SoRR again!

And if after 10 years your portfolio is “only” at about 1.0x target? You still face SoRR and you still worry about running out of money.

About the link: Thanks. Will take a look. I’m a fan of dynamic spending rules based on asset valuations. The spending rule should satisfy Bellman’s principle of optimality of dynamic decision problems. Anything that violates this rule is a non-starter for me. (a CAPE-based rule would satisfy this). Will have to check if our fellow-CFA members got that right! 🙂

Hi ERN. I learned a lot from this excellent article… thank you! I’m a bit confused by your comment above on August 29th, 2020.

In the article, you stated that “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.”

Therefore, for someone who is 5 years into their 60-year retirement, if their portfolio has reached 1.5x of its initial retirement value ($1,229,000 x 1.5 = $1,843,500), couldn’t the retiree now safely raise their withdrawals to $60,691 for the next 55 years (indexed to inflation), without worrying about SoRR even if they never looked at their portfolio ever again ($1,843,500 multiplied by the 660-month retirement horizon fail-safe withdrawal rate of 3.292% = $60,691)? This hypothetical scenario is assuming the S&P500 is still at its peak (0% drawdown figure) at the 5-year mark of this individual’s retirement, and also assumes the future will not be worse that the worst history has ever thrown at us 🙂

Yes, that’s how you’d walk up our withdrawal amounts over time in case your portfolio does better than expected! But again: that $60,691 is subject to some uncertainty (hence the title of the blog post) even though the INITIAL $40k is now super-safe. 🙂

The advantage of the real cash flow based SWR approach is that you can both determine the first withdrawal amount and walk it up or down, if necessary, with much less uncertainty. This is because for generating this real cash flow or SWR out of your portfolio sustainably, it is most important to assure an adequately sustainable real cash flow into it through well-diversified investments primarily with high returns.

Then it is best and obviously easiest to estimate this effectively available cash flow through the real dividend yield, flowing into your portfolio. Add a certain percentage to this, fundamentally determined, which the invested companies invest themselves sustainably for their organic growth on average, plus your desired capital consumption rate.

Thus, you need not worry about blindingly wild fluctuations of market valuations around known long-term averages and if these averages still hold true or changed due to some structural changes of the market up or down as quite some experts currently assume. You need no unnecessary sophistication with CAPE or Monte Carlo approaches to determine your individually best SWR estimate.

And you get much better founded orientation, what is worth it to invest in, i.e., assets with sustainably high returns such as equities, real estate/REITs and maybe also suitable alternatives with no or negative correlations for more effective diversification through smoothing the development of the overall absolute portfolio return, not valuation(!), as well as what not to invest, e.g., treasuries, gold, or commodities… with no sustainably high returns, usually only allocated for smoothing irrelevant market valuations. This last advantage even provides for a fundamentally higher SWR overall.

All this fascinates me with this approach primarily based on practical experience and common sense rather than on sophisticated but questionable theories, leaving too much uncertainty. But I am certainly curious how it satisfies “Bellman’s principle of optimality of dynamic decision problems”. I would appreciate if Karsten also explained its application for checking such approaches.

I appreciate the approach since it is quite relevant to my situation. People who want to retire as a early as possible often look at the 25x milestone and then sweat out the SWR. Hence they have a great interest in establishing the true SWR. It seems to me that this big group of people is the main focus of most of ERN’s analysis. After all it is logical that people in the FI community would want to retire as soon as (safely?) possible.

In my case, for better or for worse, I’m at 55x expenses, so I believe I have earned the luxury to worry more about establishing a perpetual endowment, rather than not running out of money in retirement. May sound like a luxury but I had to work an extra 10 years for that. Social pressure in my social environment regarded a non working man as a failure…

In any case, I looked at the link that you provided but it does not offer much detail other than a rather vague suggestion that withdrawal rates should be based on cash flows. Surely that is intuitive as a method to preserve capital and thus preserve the withdrawal power of an endowment, and may work for someone like myself who being at 55x expenses can live with an SWR as low as 1.8%. But, as I said, I’m not the typical focus of ERNs analysis. At 55x expenses I have much greater flexibility in withdrawal rates. ERN primarily focuses on those who want to retire as early as possible without taking undue risk, that is, those wishing to retire around the 25x mark, I believe. In that situation you don’t have that much luxury, you need a stable SWR yet historical data simulations imply some uncertainty.

I suspect that withdrawal rates that are linked to cash flows also have great variability. ERN had a post about the SWR volatility of chasing yields, that is, chasing higher cash flows. That seems like a related topic.

@HB, thanx for your detailed comment. The intention of my contribution was not to minimize SWR and prolong working time. But I wanted to show better approaches from the institutional world with much higher reliability requirements, how to derive a better SWR estimate. Because this is most challenging, considering our VUCA world with black swans, waiting to crush it anytime.

With this more solid base, users can plan their financial future with more confidence, whatever their plans of using up their capital are. In my opinion, better knowledge provides for higher quality of life by avoiding irreversible mistakes.

Completely disagree. Please see my previous posts on this. SWR Series Parts 11, 29, 30, 31.

Dividends can be cut. Dividends have had long, multi-decade drought periods of losing purchasing power. All this income-focus is just a bunch of mumbo-jumbo of people who don’t understand finance. Total Returns matter. Not dividends.

Karsten, thank you for your open feedback and pointing to your relevant articles. However, after looking at them I found that most of them deal with the “widely held misconception that we can easily save the 4% Rule if we were to increase the dividend yield.”

As this is not my point – both the CFA article and I definitely prefer simple indexing of market cap. assets with minimum factor tilts, i.e. S&P 500 or ACWI – what else is their relevancy?

The only critical point I also see is certainly: “Dividends have had long, multi-decade drought periods of losing purchasing power”.

However, at least during the last 70 years from 1950 on, which my referenced CFA article shows that raw S&P500 dividends had a much lower volatility compared to earnings and particularly market valuations. Thus, shouldn’t dividends be a much better basis for further “manipulations”, i.e. transforming their time-series by folding them with fundamental factors and/or smoothing approaches, than market valuation?

And could you please reference historical times with higher dividend volatility and “multi-decade drought periods”.

Looked at it from the other side much more more or less artificial and thus possibly misleading manipulation is needed for market valuations to derive smoothed SWRs from them. Because market valuations are mainly formed by maybe 90% complex mass-psychology, which has to be smoothed out, whereas dividends are set and already per-smoothed by professional insiders based primarily on fundamentals of their own companies they should better than anyone else.

I think we’re not very far apart. I propose tying my withdrawal amount to the Shiller CAPE. Recall, the earnings that go into the CAPE ratio are 10-year rolling windows, adjusted for inflation. Very slow moving, probably even less volatility than real dividends.

And on top of that, the SWR rules I’ve played around with put a multiplier of only 0.5 on the CAPE earnigs yield (but add an intercept). This takes out a lot of the volatility. Please see SWR Series Part 18.

Also see my Google Sheet (Part 28) where I added a tab to simulate different CAPE rule parameterizations.

Yeah, that makes more sense. I do appreciate the effort, that went into the CAPE approach. However, I am not convinced that it is really the best one. Because the CAPE rule is still based too much on the past with all its irrational influences from trends, hypes, government policies such as this insane QE… on both valuations AND earnings.

But as we all know, the past is no… That is why I do not even advocate the earnings based cashflow approach but the dividend based one.

Because dividends are not derived directly from earnings. Again, they are based at least as much on well founded future expectations of the most competent skin in the game in all companies. It has the strongest motivation to survive and to grow sustainably, i.e. continuously!

This is expressed best by companies through continuously growing dividends. To achieve this, they are already smoothed intelligently, strongly based on best fundamental competence and not on numerical tinkering with factors, merely extrapolating the irrelevant past into the volatile future. That is why dividends obviously have the least volatility, compared to earnings and valuations. Or in case you found contradicting evidence so far, please post it.

Thus, the dividend approach needs the least artificial quantitative smoothing. But only if it is not sufficiently smoothed more fundamentally as well through smarter diversification with more contrarian investments than bonds.

Why not utilizing this most valuable crowd intelligence from all its competent skin in the game? Usually, this provides best for superior solutions to complex problems with a high degree of uncertainty such as determining a really save but well yielding SWR.

For your enjoyment here’s a link to an interesting discussion on the topic. Check the initial tweet, replies by Michael Kitces and some of the Dividend honchos:

https://twitter.com/myownadvisor/status/1302264588231159809?s=20

It also includes some of my replies:

https://twitter.com/ErnRetireNow/status/1302452361634299905?s=20

About your reply:

“the least artificial quantitative smoothing. ” You say that without any quantitative proof. My CAPE-based approach has lower vol than the dividend only approach.

And after this quote of yours “Because dividends are not derived directly from earnings”

I decided to shut down this line of discussion with you. We seem to have a different approach/understanding/grasp of basic financial concepts. I don’t think I like to take this discussion with you any further.“But I am certainly curious how it satisfies “Bellman’s principle of optimality of dynamic decision problems”. I would appreciate if Karsten also explained its application for checking such approaches.”

The traditional 4% does not satisfy the principle of optimality. A CAPE-based rule, which is what I like and prefer, does.

Am I missing something?

Isn’t Garland’s Cash Flow Earnings Rule (65% of earnings yield) “just” a variant on the CAPE/CAEY rule (Part 18 of this series), with a = 0, b = 0.65, and the (10yr) CAEY replaced by a not dissimilar 15-yr adjusted average earnings per share (Garland’s NCEPS) expressed as a yield?

Garland’s Cash Flow Dividends Rule has some problems, one of which, (it ignores buybacks) Garland mentions in his paper, and another (relying on “the norms of dividend policy”) is mentioned by Laurence Siegel in his introduction to Garland’s brief.

For those with the time, one of the papers referenced by Garland is an entertaining read on the origin of a 5% rule (analogous to the infamous 4% rule) for UniTrusts: Dobris, Joel C. 2005. “Why Five? The Strange, Magnetic, and Mesmerizing Affect of the Five Percent Unitrust and Spending Rate on Settlors, Their Advisers, and Retirees.” Real Property, Probate, and Trust Journal 40 (1): 39–73.

My favorite line from Dobris’ paper is “Spending principal from a depleted portfolio early on means that even when the market recovers, one’s portfolio will recover more slowly. Shares that have been sold will not rise in value when the market rises, or at least not in your portfolio.”

Ern, many thanks for sharing your insights.

Yes, 0.65xEY is just another way of an earnings-based rule. Not sure what earnings yield Garland uses. If it’s 1Y trailing earnings, this might be really volatile. But 0.65 times Shiller 1/CAPE is indeed the same as a=0 and b=0.65.

Since this is using earnings I don’t see an issue with buybacks. buybacks have to be funded out of earnings. But anything based on the DIVIDEND yield, definitely suffers from the buyback issue.

Yeah, that’s a nice quote. Reminds me something I’ve heard earlier: “your money isn’t gone. Someone else has it” 🙂

“your money isn’t gone. Someone else has it” 🙂

@JSPRING

As Garland also states, buybacks are a temporary phenomenon that is not so relevant for the long-term.

Concerning the “norms of dividend policy”, it’s not a bug, it’s a feature” in my view, even overriding buybacks. The beneficial effect of it is obvious, as is the goal of all norms, reducing too much variation.

Here it is volatility of average dividends obviously much reduced compared to the volatility of earnings and even more so of prices. Thus, dividends should be the best fundamental basis for a smooth and reliable SWR estimate thanks to these norms, assuring reliable business processes for all involved as best as possible in a volatile market environment.

An old thread I know, but…

Norbert, you keep repeating that dividends are best basis, with all sorts of reasoning. But in fact dividend decisions are made by human beings who factor in things like inflation, political environment, tax rates and anticipated changes in tax rates, etc., and in practice their emotions when making dividend decisions, on top of the fundamentals of the individual business as they see it at the time. So while I suppose its *possible* that someone from the future could do the analysis and find that you happen to be correct that it was “best”, there is not a logical argument that you can make to demonstrate that it is so.

I am completely with Kirsten here. Total return from an investment is what matters, not dividends. Dividends have even more of a human element in their determination, and we humans are quite fallible, not omnisicent, whether individually or wisdom of the crowd.

“…dividend decisions are made by human beings who factor in things like inflation, political environment, tax rates and anticipated changes in tax rates, etc…”

Thank you for your interest in my alternative view, Andy. In this your quote is very supportive of dividends as most suitable basis for determining SWR.

Because, not inspite, so many fundamental things are factored in by the crowd intelligence of people, who are some of the most rational, competent insiders of their companies with much skin in the game. Think about it. Exactly for this reason they are not allowed themselves to trade on exactly this insider knowledge, also flowing into setting the dividend, before its publications for fairness! Why should they be less able on this knowledge to set a most appropriate dividend than doing unfairly profitable insider trades?!

This crowd intelligence of an appropriately selected knowledgrable community is also scientifically proven to result in the most precise solution for complex tasks and questions, where a multitude of factors are relevant in an unknown way and general crowds are mostly wrong. This applies to the group of predominantly rational CFOs, defining sustainably well informed and thus efficient dividend policies, vs. the less rational general crowd of all market participants, see:

“In the ideal case, there should be a matching between the aggregation procedure and the nature of the knowledge distribution.”

Source: “Frontiers | Rescuing Collective Wisdom when the Average Group Opinion Is Wrong | Robotics and AI”, Andres Laan et al.

Why ignore this most valuable insider knowledge on fair valuation and of qualified future earnings expectations, expressed through the thus informed definition of the dividend value, available for free in the market?

Let’s also do a most simple, but not simplistic, common sense check on what total return really is. I.e., over the whole life of a company it mainly consists of:

+ sum of all dividends

+ liquidation value

– IPO value

= Total return

Thus, better forget about all the rest of hot air of fluctuating market valuations and earnings in between as basis for a reliable SWR estimation. They are mainly the result of the irrationality of biased total crowds, to be filtered out anyway by thus over-sophisticated CAPE formulas. Because market dividend, least affected by general crowd irrationality, can be taken instead, needing much less misleading smoothing to provide similarly smooth SWR estimates.

But I rather not smooth market dividend at all and prefer real life’s volatility, smartly mitigating its remainig tail risks by truely contrarian long volatility strategies instead of aggravating these short volatility risks by loading up more short volatility option selling. By this I follow the good advice of one of the best risk experts, Nassim Taleb, earning tons of money with it during market crashs in our more and more VUCA world with increasing volatility long-term.

Thus, now I plea even more for the market dividend as most sound and consistent basis for a reliable SWR estimation, least affected by irrational general crowds.

How compelling ist this? 😉