Last week’s post about the Guyton-Klinger Dynamic Withdrawal Rule only scratched the surface and we ran out of time and space. So, today we like to present some additional and detailed simulation data to present at least four areas where Guyton and Klinger are quite confusing and misleading:
The ambiguity between withdrawal rates and withdrawal amounts. A casual reader might overlook the fact that the withdrawal amounts may very well fall outside a guardrail range. Inexplicably, Guyton and Klinger are very stingy with providing information on withdrawal amounts over time. There aren’t any time series charts of actual withdrawals in their paper.
True, Klinger shows time series charts in this paper, but they are only for the median retiree. Does anyone else see a problem with that? The good old 4% rule did splendidly for the median retiree since 1871 so I haven’t really learned anything by looking at the median. Wade Pfau showed (with a Monte-Carlo study) that the GK rule has a 10% chance of cutting withdrawals by 84% after 30 years. It’s very suspicious that the inventors of the rule don’t show more details about the distribution of withdrawals. You could call this either deception or invoke Hanlon’s Razor and blame it on sloppiness and incompetence, and both options are not very flattering.
The Guyton-Klinger rule (even with a 4% initial withdrawal rate) is very susceptible to equity valuations. Results look much worse if you look at the average past retiree with an elevated CAPE ratio (20-30).
Guyton-Klinger doesn’t afford you to miraculously increase your withdrawal amount without any drawback. The higher the initial withdrawal amount the higher the risk of massive spending cuts in the future.
So, let’s get cranking! We present another case study, the dreaded January 2000 retirement cohort, and also subject the Guyton-Klinger Rule to the whole ERN retirement withdrawal simulation engine to see how all the different retirement cohorts going back to 1871 would have fared. That’s over 1,700 cohorts because we insist on doing our simulations monthly, not annually. Read More »
The number one suggestion from readers for future projects in our Safe Withdrawal Rate Series: look into dynamic withdrawal rates, especially the Guyton-Klinger (GK) withdrawal rate rules. The interest in dynamic rate rules is understandable. Setting one initial withdrawal amount and then stubbornly adjusting it for CPI inflation regardless of what the portfolio does over the next 50-60 years seems wrong (despite the extremely simple and beautiful withdrawal rate arithmetic we pointed out last week).
So, here we go, our take on the dynamic withdrawal rates. Jonathan Guyton and William Klinger proposed a dynamic strategy that starts out just like the good old static withdrawal rate strategies, namely, setting one initial withdrawal amount and adjusting it for inflation. However, once the withdrawal rate (expressed as current withdrawal rate divided by the current portfolio value) wanders off too far from the target, the investor makes adjustments. Also, notice that this works both ways: You increase your withdrawals if the portfolio appreciated by a certain amount relative to your withdrawals and you decrease your withdrawals if the portfolio is lagging behind significantly. Think of this as guardrails on a road; you let the observed withdrawal rates wander off in either direction, for a while at least, but the guardrails prevent the withdrawal rate from wandering off too far, see chart below. It’s all pretty intuitive stuff, though, as we will see later, the devil is in the details.
The Wall Street Journal calls this methodology “A Better Way to Tap Your Retirement Savings” because it allows higher (!) withdrawal rates than the traditional 4% rule. As you probably know by now, we’re no fans of the 4% rule and if people claim that we can push the envelope even further by just applying some “magic dynamic” we are very suspicious. Specifically, we believe that the GK methodology has (at least) one flaw and we like to showcase it here.Read More »
One commenter the other day had a good suggestion: Publish the Excel spreadsheet that we use in our safe withdrawal rate research. Great idea! There is only one problem: we didn’t use Excel to calculate any of the SWRs. We did use Excel to create some tables, but the computation and most charts were all done using GNU Octave, a free number-crunching programming language, similar to Matlab.
But we still liked the idea of creating a tool to run some quick SWR calculations. In Octave, we can calculate a large number of simulations and calculate safe withdrawal rates over a wide range of parameter value assumptions. Millions and millions of SWRs over many different combinations of parameter values (retirement horizons, final asset value target, equity shares, other withdrawal assumptions). That would have been cumbersome, probably even impossible to implement in Excel. But a quick snapshot on how one single set of SWR parameters would have performed over time? That’s actually quite easy to do, even though there are 1,700+ different retirement cohorts between 1871 and 2015.
Update 2/10/2016: I added the gold and cash returns.
Gold returns are only completely trustworthy after 1968 when I got the London Fixing time series via Quandl. Before that, I had to rely on annual data from OnlyGold.com. If someone has a better (monthly) time series for 1871-1967 please let me know!
For cash returns I use:
3-month T-bill interest rates from the Federal Reserve starting in 1934. Monthly data.
I have annual data for going back to 1928 from NYU-Stern. Data gathered via Quandl.
For 1871-1927 I use annual data on 1-year T-bill yields from Prof. Rober Shiller. It’s not exactly ideal to splice it this way but it’s the best I can right now. If someone has better data, please let me know!
If you’ve been following our series on withdrawal rates (part 1 here) you have noticed that we’re quite skeptical about the 4% rule. That would be especially true for early retirees with a much longer horizon than the standard 30 years. Though, by reading through some of the research from the heavy hitters in the retirement research world, even the foundation of the 4% rule over 30 years seems to be crumbling a little bit:
Wade Pfau has been warning that due to high equity valuation and low bond yields the Trinity Study success rates are likely overrated. His argument is similar to ours in Part 3 of this series: we live in a low return world now and comparisons with past average returns could overstate the success probability of the 4% rule. He uses a slightly different methodology (Monte Carlo simulations) but reaches similar results.
Even Michael Kitces, arguably one of the great defenders of the 4% rule, has (inadvertently?) demonstrated that the 4% rule over 30 years isn’t all that sound. In the discussion after the famous “ratcheting post,” some readers (including yours truly) pointed out that we can’t replicate the success of the 4% rule with 1965/66 starting dates. Nothing to worry about, Kitces replied, all you needed to do is to use a very short-term bond (1-year T-bills) for the bond allocation, and you sail smoothly during the 1970s. Who would put 40% of the portfolio into 1-year Treasury bills (essentially CD interest rate) rather than trying to harvest the term premium of longer-term bonds? Very easy: someone with 20/20 perfect hindsight who knew that longer duration 10Y bonds will get hammered in the 70s and sink the 4% rule even over a 30-year horizon.
And I just became a little bit more skeptical about the 4% rule even over a 30-year horizon! But there is (at least) one prominent 4% SWR firewall still standing. In countless blog posts, discussions, forums etc. I have heard this quote (or variations of it):
“The 4% rule worked just fine during the Tech Bubble and Global Financial Crisis”
Welcome back to the Safe Withdrawal Rate Series. Last week we wrote about how Social Security can impact the SWR estimates. Even under the most optimistic assumption (no changes to the Social Security benefits formula), we didn’t think that the 4% withdrawal rate is safe.
But how about tinkering with the inflation adjustments, also called Cost-of-Living adjustments (COLA)? I often hear that one way to save the 4% rule in periods when the stock market doesn’t cooperate is to not do inflation adjustments for a few years. Or simply utilize the fact that we all potentially spend less (in real terms) as we age! How much can we push the initial withdrawal rate in that case?
After a one-week hiatus over the holidays when we wrote about a lighter topic (dealing with debt, booze, and cigarettes, go figure), let’s return to the safe withdrawal rate topic. We’ve already looked at:
the sustainable withdrawal rates over 30 vs. 60-year windows (part 1),
and the current expensive equity valuations (part 3).
The bad news was that after all that number-crunching, the sensible safe withdrawal rate with an acceptable success rate melted down all the way to 3.25%. So much for the 4% safe withdrawal rate! That 25x annual spending target for retirement savings just went up to 1/0.0325=30.77 times. Ouch! Sorry for being a Grinch right around Christmas time!
But not all is lost! Social Security to the rescue! We could afford lower withdrawals later in retirement and, in turn, scale up the initial withdrawals a bit, see chart below. How much? We have to get the simulation engine out again!
So, the point we like to make today is that looking at long-term average equity returns to compute safe withdrawal rates might overstate the success probabilities considering that today’s equity valuations are much less attractive than the average during the 1926-current period (Trinity Study) and/or the period going back to 1871 that we use in our SWR study.
Thus, following the Trinity Study too religiously and ignoring equity valuations is a little bit like traveling to Minneapolis, MN and dressing for the average annual temperature (55F high and 37F low, see source, which is 13 and 3 degrees Celius, respectively). That may work out just fine in April and October when the average temperature is indeed pretty close to that annual average. But if we already know that we’ll visit in January and wear only long sleeves and a light jacket we should be prepared to freeze our butt off because the average low is 8F =-13C! Likewise, be prepared to work with lower withdrawal rates considering that we’re now 7+ years into the post GFC-recovery with pretty lofty equity valuations.Read More »
Welcome back! This is our 50th post, as I just learned from WordPress. Cheers to that and thanks to our readers for coming back every week! As promised in last week’s introductory post, we present some additional results about safe withdrawal rates for early retirees. Today’s post deals with an important issue that all retirees (whether retiring early or in their mid-60s) should ask themselves:
Do we want to deplete our savings or maintain a certain minimum real value of the principal to bequeath to our heirs?
We are amazed by how little discussion there is in the personal finance community about this. Hence, today’s topic:
Capital Preservation vs. Capital Depletion
capital preservation: target a certain minimum asset level (as % of the initial value) at the end of the retirement horizon. Under full capital preservation we’d aim to keep the real, inflation-adjusted value constant, by consuming “only” the capital gains, dividends, and interest over time, while keeping the principal (plus inflation-adjustment!) in place.
capital depletion: target a zero (or at least positive) final portfolio value, by consuming gains as well as principal over time
We just calculated over 6.5 million safe withdrawal rates. Well, not by hand, of course, but by writing a computer program that loops over all possible combinations of retirement dates, and other model parameters. Not a big surprise here, but it took a lot of work to put this together. We can’t possibly fit all results into one single post, so we publish our results in multiple parts. Today, we briefly introduce our research and some baseline results. Stay tuned for more to come in the next few weeks/months:
The plan to work on this research came after one of those moments when we realized that if you want something done right and exactly applicable to our own situation, we just have to do it ourselves. We wanted to do a lot more robustness analysis than we had seen anywhere in the blogging world.
One of the idiosyncrasies of the ERN family early retirement plan is that it involves a relocation. It’s not that we don’t like our current location. But even with our nest egg solidly in the seven figures we likely couldn’t afford to retire here comfortably because of the insanely high housing costs. The state income tax rates are also unpleasantly high. So, if everything goes well we will relocate to another state with low or no income tax and lower housing costs.
The options we consider:
Own a house, mortgage-free
Own a house, plus mortgage. But what term: 30-years or 15-years?
Rent a house or apartment, long-term
Nomadic lifestyle: have no fixed residence, move from place to place with light luggage
Ok, I have to admit, I threw in that last option just for fun. Some people can pull it off (GoCurryCracker), but I doubt that the nomadic lifestyle is for us. I like to have a home base! The way I can tell is that as much as we love to travel, it’s always nice to come back home to sleep in our own bed. Even if I know I have to head back to the office the next day. Seriously!
Quantifying the tradeoffs
We can write as much as we want about the pros and cons of renting vs. owning, but in the end, it all boils down to the numerical assumptions, especially the rental yield (annual rent divided by purchase price):
If we can rent a house for only 5% p.a. of the purchase price or less it’s likely a no-brainer to rent. The opportunity cost of our money tied up in a house plus the depreciation and taxes would be too large. Unless, of course, we factor in huge property appreciation. But our baseline assumption is that property values appreciate with the rate of inflation. The last time folks were budgeting outsized returns in housing it didn’t end so well, remember 2008/9? So, renting can be much smarter than owning, see some examples at 10!Rocks and Millenial Revolution.
If the annual rent is 10% or more of the purchase price, it’s almost a slam dunk to buy.
Somewhere in between has to be the sweet spot. Let’s check where’s that crossover point in the rental yield!Read More »