An Updated Google Sheet DIY Withdrawal Rate Toolbox (SWR Series Part 28)

Since I first published Part 7 of the SWR Series with the accompanying Google Sheet in early 2017, I’ve made several changes and enhancements. Sometimes without much explanation or documentation. So, it would be nice to do a quick update and itemize the changes since then. Whether this is the first time using the toolbox or you check it out again after more than a year, I hope you all find the new features useful…

Here again is the Google Sheet Link:

Link to the EarlyRetirementNow SWR Toolbox v2.0

As always, please save your own copy because the current (clean) version posted on Google Sheets has to be write-protected so visitors don’t mess around with my formulas! 🙂

Save Your Own Copy

Main Tab: more detailed results

As before, you enter almost all parameters in the main tab “Parameters & Main Results.” All fields in Orange are user inputs, such as:

  • Equity/Bond/Cash/Gold share. To make sure the weights sum up to 100%, the Gold share is set to 100% minus the sum of the rest.
  • Fama-French style factors. This is new, see item #3 below for more details.
  • Assumed projected asset returns for the asset classes going forward. Why do this? I’d like to be able to simulate 60-year windows of the 1960s and 1970s retirement cohorts and don’t want to constrained by a slightly shorter than 60-year data availability. Since the SWR is overwhelmingly determined by the first 10-15 years of the retirement horizon (Sequence Risk, see SWR series Part 15), the last few years of “made up” returns during retirement don’t have much of an impact on the SWR estimates. Example: the failsafe WR is 3.46% during the 1960s with our assumed 3.75% p.a. equity return. If we increase the equity expected return to 20% p.a., the failsafe increases to only 3.52%. But, of course, the 2000 and especially 2007 fail-safe numbers would be significantly impacted by the return forecasts. So, use those figures with a grain of salt!
  • The retirement horizon in months and the target final value (e.g. for bequests) as a percentage of the initial value.
  • Notice that the supplemental cash flows are no longer inputted here in this main tab, but in a separate tab, see item #2 below.
SWR-Part28-Table01
Main Parameters. Same as before but I added the Fama-French Small Cap Style (SMB) and Value Style (HML)!

The main results table is pretty large so I split it in two, the first part is below:

  • As before, I display the failure rates of different initial withdrawal rates in the top half of the table.
  • The bottom portion of the table is new and presents the calculation the other way around: Pick a desired failure rate and look up the withdrawal rates to match it. The first row in that portion at 0.00%, i.e., this is the fail-safe initial withdrawal rate. But you can also look for other failure rates, 1%, 2%, 5% and 10% as well and see how much extra initial withdrawal you could have sustained in historical simulations. And I hope that nobody would even consider a strategy with a failure rate of 25 or even 50%, but I display those just for reference.
  • The columns calculate the corresponding stats for all retirement starting months and years, since 1926 (the start of the Fama-French database and also the starting point for the Trinity Study) and 1950 and also for different Shiller CAPE Ratio regimes (under 20 vs. 20 to 30 vs. 30+). Notice that as of late August 2018 we’re at over 32! As conservative as I am normally, though, I’d concede that today’s elevated CAPE ratio doesn’t quite “feel” like the 30+ CAPEs of the past. Maybe I’d still consider the current CAPE a high 20s, not really a low 30s!
  • Notice how sensitive the failure rates can be when changing the WR in 0.25% steps, especially when the CAPE is high!
SWR-Part28-Table02
Main Results: The top panel shows the failure rates of specific initial withdrawal rates. The bottom panel goes the other way around: Specify a certain failure rate and find the initial withdrawal rate that would have generated that failure rate.

And Part 2, see below. The table has the same format as the first part, but now the columns are conditional on how far the S&P 500 index is away from its most recent high. Why does this matter? The stock market is a Random Walk and past returns have no bearing on future returns, right? Wrong! As is well-known in finance and as I pointed out in a post a few months ago, stocks have the tendency to mean-revert. So, expected returns tend to be higher after a steep drop and lower after a long run-up in stock prices. That’s reflected in the failure probabilities of the 4% Rule below. The unconditional failure probability was just under 10%, but it’s 18.55% when we were at the market peak. So, failure probabilities are indeed impacted by past returns. File this as another piece of evidence that the stock market isn’t exactly a Random Walk!

Why is this relevant? Well, on August 22, 2018, the market just became the longest running bull market in history (though not everyone agrees on the definition of the longest bull market, see this article on Bloomberg). If history is any guide the retiree in this numerical example will be wise to be more cautious with the initial withdrawal rate and not just blindly apply the 4% Rule mantra. Maybe withdraw a little bit less, 3.25-3.50% to have a bit a cushion. In other words, after a potential drop in the portfolio the effective withdrawal rate might reach 4% right around the time when the S&P had a ~20% drop, which is when, historically, the 4% becomes very safe again!

SWR-Part28-Table03
Same as Part 1 of the results table but conditional on the equity drawdown

I also added a small table with the fail-safe withdrawal rates in five important time intervals around stock market peaks. That’s because I usually like to see during what period the all-time fail-safe occurred. Most of the time it’s either 1929 or the 1960s, depending on the stock vs. bond. vs. cash allocation! It’s always amazing to see that the 1970s and early 80s recessions did an even worse trick on the mid-60s retirement cohorts than the ones that retired around the 1973 market peak!

SWR-Part28-Table04
Fail-safe Withdrawal Rates in five different bear markets.

Supplemental cash flows: now easier to input!

One of the biggest challenges for folks trying to use this spreadsheet used to be how to correctly enter the supplemental cash flows. I tried to make this a little bit easier and intuitive, so I created a separate tab, appropriately named “Cash Flow Assist” to help with that. At the top, we can input the initial portfolio value and a projected inflation rate to discount the value of any non-inflation-adjusted future cash flows, e.g., corporate pensions etc. in the orange fields below. As always, it’s best to go through a simple example:

  • The portfolio is worth $3m at the beginning of retirement.
  • We expect 2% inflation going forward.
  • Spouse 1 expects Social Security after 25 years (=month 301) worth $2,000 per month.
  • Spouse 2 expects Social Security after 26 years (=month 313) worth $800 per month.
  • Spouse 1 expects a small corporate pension of $300 (not inflation adjusted) 11 years into retirement.
  • We expect $1,000 in additional monthly expenses (e.g. medical) 30 years into retirement (in today’s dollars, adjusted for inflation) and that amount rises to $2,000 after 40 years. This corresponds to the two spouses reaching a certain age where they may scale back other expenses (travel) but face increase medical, in-home care expenses, etc. that will case in a net increase in expenses.

How do we input all of this? At the top of the page we input the net worth and inflation figure and leave the other orange fields empty (=$0) for now because there are no supplemental cash flows during the first year, see below:

SWR-Part28-Table05
Enter the Net Worth today and the inflation assumption. Cash flows don’t start until later, so the other orange fields are left blank (=$0).

Next, we input the corporate pension, starting after 11 years (month 133), see below. Notice that we input this in the fifth column where the non-COLA cash flows reside. So, this will be discounted to make sure it’s comparable to today’s real dollars!

SWR-Part28-Table06a

Next, the Social Security payments starting 25 and 26 years into retirement, see below. The benefits are inflation-adjusted so they are entered in the corresponding columns with COLA cash flows:

SWR-Part28-Table06b

And, finally, the additional budget for medical expenses, care, nursing homes, etc., see below. This is now inputted as a negative cash flow!

SWR-Part28-Table06c

In the “green” column on the right, the program translates the different cash flows into percentages of the initial portfolio:

SWR-Part28-Chart05
Monthly supplemental cash flows as a % of the initial portfolio.

Also in the same tab is the same table that showed up in the main tab but the percentages are translated into withdrawal amounts in dollars p.a.:

SWR-Part28-Table12
Translate withdrawal percentages into dollars p.a. for this numerical example.

Fama-French Style Factors (since 1926)

I added that feature pretty early in the spring of 2017, mostly out of curiosity about how much of a difference some of the widely cited style premia such as value and size would have made. See Ken French’s site for the data and more documentation on the construction of the Fama-French factors. For example, let’s simulate the following scenarios:

  1. The 80% S&P500 baseline
  2. Keep the overall equity share at 80%, but use a 25% small caps and 25% value stocks tilt: Set the SMB and HML allocation to 25% each. Make sure you keep the overall stock allocation at 80%!
  3. Keep the overall equity share at 80%, but use 50% growth stocks. Set the HML allocation to -50%. Again, make sure you keep the overall stock allocation at 80%!

The small-cap plus value bias would have easily lifted the SWR to above 4%, see table below. But I’d probably not get too excited about this result. There’s no guarantee that the size and value premium will persist forever and continue to help future retirees. All this could just be backward-looking bias. Certainly, in 1926 nobody would have known about the work by Fama and French. In fact, if you had been wrong and bet on the wrong style, for example, “growth” instead of value you would have totally ruined your safe withdrawal rates. Fail-safe withdrawal rates are now in the low 2% range. Ouch!

SWR-Part28-Table13
Fail-safe initial withdrawal rates for different equity style premia.

Case Study: glide path simulation

In the tab “Case Study” where you can simulate one single time series of the portfolio values for a specific starting date and initial withdrawal rate, I also added a simple glidepath simulation for comparison (see Part 19 and Part 20 of the SWR Series). This is the simplest possible version with just the static glidepath going between two different equity weights in fixed steps (e.g. 0.3% per month) and investing the residual in bonds, see below:

SWR-Part28-Table09

Compared to an 80/20 static stock/bond allocation, the glidepath would have made a huge difference during the Great Depression! But glidepaths were not a panacea because, during the 1970s, bonds offered much less diversification.

SWR-Part28-Chart02
A portfolio with a 4% initial WR and 80/20 fixed allocation would have run out of money after less than 25 years. A Glidepath would have performed much better!

Simulate CAPE-based Withdrawal Rules

I added another tab to simulate CAPE Rules with different parameters. Just as a recap, the CAPE-based rule, in its simplest form, expresses the annualized target withdrawal rate as a+b times the inverse of the Shiller CAPE (=CAEY = Shiller Earnings yield). See Part 18 for more details and why I like this approach. My preferred rule would be to set the intercept to around 1.5-1.75% and the slope to one half. In the example below I use 1.75%/0.50. Notice that a constant percentage rule would be a special case if we set a=4% (or whatever rate you like) and b=0, i.e., withdraw 4% p.a., regardless of equity valuations.

Running out of money is no longer an issue with the CAPE-based rules. Failure comes in the form of deep and extended cuts to consumption. So, to compare how much (or how little) I like different CAPE I tend to look for 3 key stats:

  1. What’s the change in real, inflation-adjusted withdrawal amounts over a 30-year horizon?
  2. Notice that the point-to-point comparison over 30 years can deep cuts in spending, so I also like to know the lowest withdrawal amount relative to the initial withdrawal amount
  3. And finally, what’s the average over the 30-year window relative to the initial amount.

See below for a numerical example:

SWR-Part28-Chart06
January 1970 cohort: Time series of 12-month rolling withdrawals and the three measures I calculate.

I’m interested in how the three measures would have evolved in the worst case scenarios, so I calculate them for different time intervals (all months vs. 1926 onward) as well as the worst case scenarios in the five different “troublemaker” retirement cohorts (Great Depression, 1960s, early 1973, Dot-Com bust and Great Recession), see the table below. I also add the volatility of year-over-year withdrawals and some stats on the withdrawal rates implied by this CAPE rule:

SWR-Part28-Table10
CAPE parameters and main results.

A little side note: I frequently get questions and comments about the CAPE parameters just like recently when a reader wondered why I assign a weight of 0.5 on the CAEY. Shouldn’t the withdrawal rate be less volatile with a higher intercept and lower slope? Yes, but as a retiree, I’m less worried about volatility in withdrawal rates and more worried about volatility in withdrawal amounts. So if I were to set the intercept to 3% and the slope to 0.3 I’d have a more volatile stream of withdrawals, see below. And the more you reduce the slope parameter the closer you get to the good old constant percentage rule where your withdrawals become just as volatile as the portfolio itself!

SWR-Part28-Table11
A higher intercept and lower slope. The withdrawal rates are less volatile but the withdrawal amounts become more volatile!

I guess it’s up to you and what you feel comfortable with but I like the way the CAPE rule cushions the volatility in withdrawal amounts, see below:

SWR-Part18-Formula03
From the SWR Series, Part 18: Under the constant percentage rule, the withdrawals will move in sync with the portfolio value. In contrast, tying the withdrawals to economic fundamentals has the potential to soften the fall in withdrawals in case of a bear market!

OK, so much for today! I hope you enjoy the new features! Please let me know if you find bugs or like to suggest more features!

Please check out the other posts in this series and leave your comments and suggestions below!

Also notice, all the usual disclaimers apply!

Picture Credit: Pixabay

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68 thoughts on “An Updated Google Sheet DIY Withdrawal Rate Toolbox (SWR Series Part 28)

  1. Great summary. I’m using your toolbox very often. It’s quite an awesome resource. Thanks for making this.
    Here seems to be a missing text in the article: “I’d concede that today’s elevated CAPE ratio doesn’t quite “feel” like the”
    I also have a question around that, many have said that the CAPE is “out of wack” recently since the low interest rates and other factors. Have you hear of alternative approaches to correct this CAPE approach? E.g.: https://investornews.vanguard/valuing-the-stock-market-with-a-new-yardstick-the-fair-value-cape/ What do you think about that?

    Liked by 1 person

    • Thanks for pointing that out. That sentence must have gotten cut off!
      The CAPE is out of whack in more than one way, but it’s still a decent measure.
      I’d first give the CAPE a bit of a haircut because we will soon roll out the poor EPS numbers from 2008-2010 and replace them with much better-looking earnings. Heck, even a mild to moderate recession today would still raise the 10-year rolling average.
      I also agree with the Vanguard point: today’s fair-value CAPE is no longer 15 and there are various reasons for it. But what is it? 20? 25? Hard to pin down!

      Like

      • If anyone has more thoughts on CAPE, or links to other articles, it would be great. I seem to recall reading some justification that it ought to be CAPE /7(years). I thought maybe Kitces but can’t find it.

        Liked by 1 person

  2. Thank you for this great spreadsheet! I´m looking forward to playing with it. Even if I´m still far from retirement I feel that it is important to learn from history and consider as many variables as possible as it will help me be a bit more prepared.

    Liked by 1 person

  3. You said “I hope that nobody would even consider a strategy with a failure rate of 25 or even 50%”, but aren’t these useful for determining if you’re in for a bumpy ride or you should eject and get a job? Say you get a few years in and there’s a bad downturn (and your haven’t been bond glidepathing). Match your current portfolio up with your withdrawal numbers and bam!

    Liked by 1 person

    • I had a similar question. If half the US Population lives entirely on Medicare, Medicaid and social security, doesn’t a failure just mean you are average? Although definitely not an ideal state, I don’t think it can be viewed as a total failure.

      Liked by 2 people

      • Good point! You won’t starve, that’s a good news. Personally, I’d not have a comfortable retirement.
        I also don’t think that half of the population lives on public assistance ONLY. You’d be much lower down the ladder than the median…

        Like

    • I’d be concerned that with a SWR too high you might go back to work almost for sure. The 50% failure plus maybe another 25% from false alarms (type 2 errors), so I wouldn’t even call that early retirement. Sounds more like a 2-3 year time off…

      Like

  4. Love this series. As an engineer I gobble up the math although honestly there are points that even I have to re-read several times.

    I was so excited to see this email. I cannot wait to use the new sheet tonight.

    Thank you!

    Liked by 1 person

  5. Hi, I love your SWR series and thanks for the updated spreadsheet, but i get an error when opening the downloaded spreadsheet in Excel, which causes all the graphs to be blank.
    Can you please check this ?
    Thanks
    Ian

    Liked by 1 person

    • I checked this and found that Excel messes up some of the charts, but some are OK. Are you using the latest Excel version?
      In any case, not sure how to fix this. The numerical results seem OK, though. Maybe it’s just a matter of manually inserting the bad Excel Charts…

      Like

  6. Thanks so much for updating this! As a data scientist, I had been having a lot of fun exploring scenarios with the old version and look forward to trying out the new one.

    I was noticing a strange result in the old spreadsheet. It seems the calculation used to get the results in “Parameters & Main Results” tab yield different results than in the “Case Study” tab. I used the same parameters in both tabs and, to get comparable results, ran the calculations in the Case Study tab for all valid Retirement Start Year and Month values (basically, brute-forcing it). I’m not sure if I have a bug somewhere, if it’s a rounding error, if there’s a small difference in your formulas from part 8 and the brute-force approach that the Case Study tab uses, or something else, so I thought I’d mention this. I noticed this discrepancy as I tried to extend your work to let me explore some of the withdraw strategies you discuss in the other parts of this series for my particular case.

    A minor bug I found when looking at the old spreadsheet that hasn’t been fixed: In the Stock/Bond Returns tab, the Year and Month columns are mislabeled. The same problem is on the new CAPE-based Rule tab. Not a big deal, but since you asked… 🙂

    Again, thanks so much for all your work on this! I’ve been loving this series!

    Liked by 1 person

    • Thanks for the feedback.
      At least in the most recent version, I made sure that the case study file is consistent. So if I set the horizon to 30Y in the main sheet, then do a case study and set the initial WR to the value computed in the tab “SWR time series” (ideally formulaic, not just copy and paste the numbers to avoid rounding errors), then in the case study I reach exactly the final value target (e.g., $0 or 25% times initial, or whatever).
      If there was a bug in the old sheet it should now be corrected! 🙂

      Like

  7. Great work. Thanks for the updates. Can you post an Excel version for download. I downloaded the google.docs version as an Excel, but when opening in Excel it produced errors.

    Liked by 1 person

  8. Amazing spreadsheet, I’m close to experience an org… ahem, anyway, a minor bugfix: in the stock/bond returns sheet month and year are messed swapped (cells A5 and B5)

    Thank you for this incredible work Big ERN!

    Liked by 1 person

  9. Holy smoke. Hat’s off to you, Karsten, for this detailed and refined sheet, as well as the details in this post that links the sheet’s specific features to the relevant SWR postings for further reading. Can’t thank you enough!

    Just wondering… As a PhD economist, you must have published dissertation/papers for peer-review. How do you find the online/blog publishing experience/feedback as compared to publication for the academic community?

    So glad to learn, through your postings, the the Ern family is doing so well in its newest phase of life. Be well, and God Speed!

    Liked by 1 person

  10. Thanks so much for the updated spreadsheet and the rude awakening. I usually just mess around with cfiresim, even if it is a black box. But @#$%, adding those extra monthly figures in really messes with the withdrawal rate for 0% failure. Even assuming we get 75% of social security at 67, we are at a 2.71% withdrawal rate to have 0% failure for capital preservation after 50 years. Cfiresim is at 3.1%, largely because they exclude September 1929 and the other terrible scenario, January 1966, has a near market peak after 50 years. You are making me rethink my consistent belief that 3% withdrawal rate is always safe. Maybe we will get comfortable with the 1% failure rate, otherwise it looks like we just added another year.

    Thanks for another great thought-provoking post! I am so glad you are sticking with the blog after retirement.

    Liked by 1 person

  11. First off, as much as I enjoy your postings I’m glad to see they have slowed down a bit since you left employment. Glad you’re living the plan!

    As far as this sheet, I had added an extra sheet for what you call the “cash flow assist” on a downloaded copy of your original as well so thanks for including that this time around. This piece of work is exceptional, yes, but more than it’s really quite a gift. Thanks for continuing to put your work out there for everyone.

    Like

  12. Thank you for this update! I’ve been torn on whether or not to include my house equity in my total portfolio, since it’s not currently a productive (income-generating) asset but merely reduces expenses (I have no mortgage). I recall that past discussions of housing presented real estate as roughly tracking inflation. Since I have an oversized amount of my portfolio tied up in real estate, I would like to know how I can include an inflation-adjusted asset that could in future years be used for a reverse mortgage or liquidity by selling and switching to renting in a cheaper locale. Should I enter my house equity value as if it were bonds? Do your simulation of bonds only reflect the holding of bonds to maturity, or do they reflect the ups and downs of the bond market due to the change of bond prices and yields?

    Last, this approach will be useful if I wind up getting a rental property, since your v2.0 toolbox helps me track the income but I’ll need a separate way to track the equity. Thanks again!

    Liked by 1 person

    • For rental properties you can use the supplemental cash flows to include them. But don’t include their value in the portfolio value. Only the financial assets.
      Your owner occudped house is a ‘dead’ asset and “only” pays you an in-kind dividend. But you can use it as a last resort asset and tap the equity through a reverse mortgage if things don’t go well. And you add it to your estate!
      Bonds: the bonds are 10y benchmark bonds so you don’t hold to maturity. It’s like a constant maturity bind ETF (like IEF).

      Like

      • I initially made the mistake of thinking Cash Flow Assist was an optional second step of analysis. But since it’s pre-filled with the example you provide here in the blog, it’s important for users of the spreadsheet to double-check the Cash Flow Assist amounts, some of which don’t appear until many months into the analysis (e.g. medical expenses, social security income for spouse).

        This is a super useful tool for what-if analysis. Thank you!

        Liked by 1 person

  13. Good morning ERN, (or evening, depending on where you are on the globe!).

    Just love the updates you have made, especially the cash flow assist tab and glide-path. Lots of intuitive ways to change key parameters. An amazing and invaluable financial planning resource for the early retiree

    I hope ER is treating your family well. The world trip sounds wicked awesome.

    Sitting here on the deck looking over the mountains with an early morning coffee, 12 weeks into retirement, and wondering my god, how did i get here? Channeling my Talking Heads there…..I am not sure when we stop pinching ourselves…..

    All the best,

    Mr. PIE.

    Liked by 1 person

    • Thanks, Dr. Pie! We are cruising right now visiting Ireland!
      The world trip is still a lot of fun (pinching ourselves every day, too!!!) but we also look forward to our back porch time once we settle down.
      Thanks for stopping by and stay in touch!
      Karsten

      Like

  14. Greetings Ern. For the Safe Withdrawal Rates/Amounts, might you mean Safe Spending Rates/Amounts?

    Example: The Google sheet reports a SWR under the various CAPE values, as well as providing a Safe Withdrawal Amount for these conditions based on our initial portfolio and inputted Social Security payments.

    Do the withdrawal percentages/values reflect our total annual safe spending (i.e., withdraw the outputted figures less Social Security), or is the Safe Withdrawal in addition to payments such as Social Security?

    Thank you for these great sheets! Many of we lay-people would never have (before your SWR series) seen personal finance and planning as so cool!

    Liked by 1 person

    • Very important point! Thanks for this!
      I mean the safe initial spending rate. So, when you get Social Security you reduce the withdrawals. I will still use the phrase “SWR” because that’s what everybody uses but the withdrawals are supposed to be adjusted by the supplemental cash flows to keep the consumption amounts constant (after CPI inflation).

      Like

  15. […] We have written about our retirement withdrawal strategy before and not much has changed. We expect to execute a glide path strategy and slowly ramp up our equity allocation over a 8-10 year period. For those of you who follow the Early Retirement Now blog, Karsten has published an updated SWR tool box Google sheet that has some great new features related to income streams and glide paths. Check it out at the link here. […]

    Like

  16. Great work. A question. Lower half of first table indicates failsafe at CAPE>30 of 3.25% SWR. But upper half of table indicates a failure rate of 1.75% for the same 3.25% withdrawal rate. How to reconcile?

    Liked by 1 person

  17. I’d love your thoughts on

    1. Quantifying political risk in your retirement models. Its possible with the Trump administration’s craziness that poicymaking regarding retirement may be suboptimal.

    2. Why not much on real estate? Most Americans own their own home and can factor that into their retirement planning.

    Liked by 1 person

    • We’ve had political risk before. And financial markets priced it in correctly, e.g. Nixon resignation.
      For the record, Trump is good for the economy, at least on a net basis. Less regulation, lower taxes, more business-friendly environment. I think that 99% of the breathless reporting about Trump’s disasters is totally exaggerated by the media. Mind you, these are people who went to journalism school and never ran a business and who are too dishonest or too stupid to acknowledge that Obama was a disaster for the economy and a guy with an orange face and orange hair is able to fix the Obama mess.

      Real estate: if I had reliable returns on RE with a long enough time series I’d gladly include it. I factor in my owner-occupied RE quite easily: I will have a lower out of pocket expenditure because I don’t pay rent. I also can afford to leave a lower financial assets estate because of the house we will soon own.
      Real estate investments are harder to model in this spreadsheet. If you have a rental property with reliable cash flow, probably model it through the supplemental cash flow sheet.

      Like

      • I’ve seen historical analysis of the efficiency of stock markets ability to price in political risk. I think their ability is overstated. Frankly, nobody knows what will happen with Trump’s administration – a war or low level civil conflict is highly unlikely, but not completely impossible.

        Liked by 1 person

        • Well, this whole trade issue seems to be getting old. The other day they announced tarrifs on another $270b of Chinese imports. The S&P 500 dropped by 6 points. Not 6% but 6 points=0.2%. But if someone thinks not enough uncertainty is priced in, please go ahead and short the market. I would not take that risk.

          Like

      • Well this is the first time we’re hearing your perspective on politics, and I suppose it’s a good way to re-bias your recommendations. You’re usually thoughtful and sober with your analytical claims, but these are pretty extreme statements backed with no nuance or data. Stating Trump is good for the economy without discussing the business planning uncertainty caused by tariffs is naive. Stating Obama created a mess without examining the Greenspan put and excessive credit injected into the market during Bush’s term is almost a hostile form of willful ignorance.

        Liked by 1 person

        • No bias here; just the facts…

          – The “exsessive credit” injected into the market was in the last few months of the Bush Presidency (in the wake of the home mortgage crisis and Lehman Bros Bankruptcy). This additional liquidity should have been a tail wind to propel the Obama economy.

          – “Greenspan Put” – that policy ended in calendar year 2000.

          The tariffs are a drag and a possible catalyst for economic disaster but, thus far, have not been sufficient to counteract the positive effects of tax reduction and deregulation.

          In what universe do added regulation and taxes lead to economic growth? It is not a coincidence that growth under Trump has reached levels not seen in many years.

          Karsen is correct in his response. The original poster decided to inject a gratuitous political jab.. Too bad for that.

          Liked by 1 person

        • Well, someone asked me for my opinion on political uncertainty. This was my opinion. I won’t paste in a 2,000 words with data tables and charts. Maybe I should do a blog post on it if I have more time again.
          But for the record, I’m a free-trader at heart. I’ve taken enough econ classes to understand that. I’ve also taken enough game theory classes to understand that it’s not a bad strategy for the U.S. to use trade policy as a stick to enforce compliance with bad actors.

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  18. Such useful tool, thank you for updating and sharing. Even though I appreciate how results can be dramatically impacted over long periods of time, I still somehow seem to be amazed at how quickly the failure rates jump with just a 25 basis point increase in withdrawal rate.from 3.00% to 3.25% with CAPE at 30+. Wow – such a good reminder to not cut things too short or be too aggressive with assumptions.

    Question: The tool has the flexibility to adjust projected future returns for the next 10 years and then after 10 years. I am curious why you chose 10 years as the cutoff versus some other time frame (perhaps five years) given the sequence of return risk factor – especially in the early years after retirement. Would results be drastically different if the tool allowed a 0-5 year future return assumption, 5-10 year, and 10+?

    Thanks again for all your insightful work around SWRs – they have been instrumental in my personal financial planning!

    Liked by 1 person

    • Thanks! Yes, small changes in withdrawals will mess around with the failure probabilities. Just like small changes in savings contributions make a big difference over the decades, they could also wipe out a fortune!
      Great question! Ten years is a sweet spot for both bonds and stocks. Say, the 10y yield is 3% today and inflation is forecast to be 2% then I’d use a 1% real return for bonds.
      For stocks it appears that today’s CAPE is mostly correlated with the next 10 years of returns. After that initial 10 year window it’s safe to assume that returns go back to their longer term averages.
      But nothing keeps you from “hacking” the sheet and using your own 0-5, 6-10 and 10+ window. 🙂
      Hope this helps!

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  19. Glad I stumbled on these. All these people shouting about 4% always struck me as pretty irresponsible.

    Oddly enough once I add my withholding taxes to my expense ratios, the “0%” failure rate on 100% equities exactly matches my dividends over the last 4 quarters: 2.25%. I’m invested globally, though, so using CAPE30+ may be a little conservative, but then again maybe not.

    Still, living purely off dividends of a bog-standard portfolio at least for the first 10 years of my retirement doesn’t seem so crazy in this 30+ CAPE environment.

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  20. Thanks Karsten for the updated spreadsheet, I like the CAPE based tab which help quantify estimated withdraw rate based on Equity valuation it is crucial particularly after the next market correction to re-evaluate the SWR.

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    • I can’t replicate that result. Not tha it makes much sense to have 100% cash, but if I use that the failure probs clearly change when changing the assumptions about the 2018+ return estiamates. Can you “share” your sheet with me? I’ll take a look! 🙂

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