Friday, May 18, 2018

Some Risks Can't be Modeled

My last few posts, The “Future” of Retirement Planning, The Limits of Simulation and Spending Rules and Simulation, have discussed different aspects of retirement planning, specifically, spending rules and Monte Carlo (MC) simulation.

Spending rules calculate a safe amount to spend in the current year. I highly recommend that you reapply your spending rule every year to take new information into account but if that's all you do then you have a one-year planning horizon.

If retirement were a game of combined chance and skill, like backgammon or poker (and it is, of course), then spending rules would identify our best current move. Simulation would tell us the probabilities that this move will ultimately win the game, like knowing the odds that your backgammon opponent will roll a 3 on his next turn (hint: they aren't good — I'd be willing to leave that stone uncovered).

A good poker player will know the odds of the deck and a good backgammon player will know the odds of the dice. They will become second nature. A good retirement planner will know the odds of possible retirement outcomes.

MC provides probability distributions for possible outcomes given a spending rule that would be repeated periodically over many lifetimes. In other words, it identifies financial risks of a retirement plan.

MC, however, only generates “normal” scenarios or those that would probably be drawn from a normal distribution. By design, MC creates most scenarios near the mean or “expected” outcome. The further from the mean, the less likely that a scenario will be created in an MC simulation.

The shortcoming of MC simulation is not that it will create unrealistic scenarios — quite the opposite — it won’t generate many highly unlikely outcomes. So, even after we test retirement plan risk with simulation we still don’t know much about the effects of low-probability catastrophic events.

Simulating such events, even if we could, wouldn’t be very rewarding. After the Great Recession, Nassim Taleb testified before Congress that improbable events are impossible to predict and called those who claim that they can forecast them “charlatans.” (He was referring to Value-at-Risk advocates.)

If Taleb is not to your taste, you can come to nearly the same conclusion by recognizing the huge confidence intervals inherent in our relatively small sample of historical market returns.  We simply can't be confident in predictions based on them.


Avoiding unforeseeable risks is not an option. It's hard to steer around an obstacle you don't know is there.
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After simulations, we still need a way to plan for the unknowable. Risk management generally proposes four strategies:
  1. Avoid the risk. You can avoid the risk of riding a motorcycle by not riding one.
  2. Mitigate the risk. Wear a helmet when you ride a bike.
  3. Insure the risk when insurance is available and affordable.
  4. Accept the risk when there is no realistic alternative. The risk of 30 years of consecutive market losses is a good one to accept. So is death by falling satellite.
Avoiding unforeseeable risks is clearly not an option. It's hard to steer around an obstacle you don't know is there. Mitigating these risks presents a similar challenge.

We can insure some retirement risks by buying annuities, umbrella liability and life insurance, for example, but insurers won't offer me long-term care insurance and premiums can be (or can become) unaffordable.

Regardless, at some point we must face the fact that our retirement plan can’t manage every risk by relying on good fortune in the stock market. (I say this knowing full well that many retirees in the “probabilist school” believe precisely that. I just don’t share their optimism, probably because I have spoken with 80-year old’s who lost that bet and must now get by on Social Security benefits alone.)

The best spending rules won’t eliminate these risks. After a long sequence of poor returns, they will simply reduce safe spending to a level that no longer supports the household’s standard of living. Nor will the best simulation software ferret them out and suggest fixes.

After selecting a spending rule and modeling outcomes with MC simulation we need to address low-probability catastrophic outcomes with insurance when we can. This is the theory behind floor-and-upside strategies — hedge your bet.

I consolidated a list of identified retirement risks in Retirement is Risky Business – Here's a List that should provide a starting point for your review. Low-probability catastrophic outcomes defy avoidance and mitigation but they’re worth contemplating and possibly worth insuring.

The key takeaway is that MC simulation can tell you a lot about fairly normal outcomes but very little about improbable, high-impact events, also known as "tail risk." Consequently, simulation is not the end of the retirement planning process. We have to evaluate tail risk by some process other than prediction and that means "seat of the pants."

It won't be a thorough process and according to Taleb, it can't be. That doesn't mean you shouldn't try. Having a floor of safe income, for example, can mitigate a lot of different, even unpredictable risks.

The best retirement plan will fail if Earth is hit by another dinosaur-ending asteroid but that's a risk we probably have to accept. There may be other low-probability, high-impact risks that we can mitigate, though, without being able to predict them with models.




Thanks, Mason Finance Group, for choosing The Retirement Cafe´ for your Best Retirement Blogs of 2018 list. Congrats to Ken Steiner's How Much Can I Afford to Spend in Retirement? blog, as well!


Monday, May 14, 2018

Spending Rules and Simulation

My recent post on Monte Carlo(MC) simulation, The Retirement Café: The “Future” of Retirement Planning, seems to have spawned a strange debate about whether a deterministic "spreadsheet" method of calculating safe current spending from a retirement portfolio is better or worse than using Monte Carlo simulation to estimate the probability of outcomes.

This debate is not unlike arguing whether a screwdriver is superior to a hammer: they do entirely different things, a good toolbox includes both, and even when you use both effectively, you're still probably going to need a saw. (I'll write more about the saw in my next post.)

I'm going to refer to the "method of calculating safe current spending from a retirement portfolio" as a spending rule because that is its purpose. The result is typically a single dollar amount as in, "applying the 4% Rule to a $1M portfolio when expecting a 30-year retirement estimates the retiree can spend $44,000 each year" or "the required minimum distribution(RMD) from your IRA this year is $38,517."

An interesting observation about these spending amounts is that if you recalculate this amount in subsequent years (as you should do with any spending rule but must do by law for IRA and other tax-deferred plans after age 70½), it is possible but extremely unlikely that you will ever calculate the same result again. That's because remaining life expectancy, current portfolio value, and other factors will change over time.

On the other hand, the purpose of Monte Carlo simulation is to estimate the probability of outcomes assuming a retiree were to retire many, many times. The probabilities can be used to identify potential problems and allow a planner to attempt to mitigate them.

The result of simulation is not a single number for a single year as calculated by spending rules but one or more probability distributions showing the odds of various outcomes, as in "there is a 5% chance that you will need to spend less than $20,000 under certain conditions."

While spending rules estimate safe current-year spending, MC simulation can provide additional insight into many questions, such as:
  • The 4% Rule says I can spend $40,000. What are the probabilities that I can safely spend $45,000 or $50,000?
  • How much could I spend if I wanted a 1% or 10% probability of ruin instead of 5%?
  • Which equity allocations most often appear in failed scenarios? (I often find that 40% to 60% equity allocations show up in fewer failures.)
  • What is the value of my safe "floor" over time? Are there gaps? Would annuities help?
  • How often does delaying Social Security benefits improve my outcomes?
The list can go on and on (this is the reason MC is used for academic retirement finance research) but it does not include "how much can I safely spend this year" beyond what the simulation's chosen spending rule can tell you before you even begin simulation.


Monte Carlo simulation and spending rules are different tools for different jobs.
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Wade Pfau's book, How Much Can I Spend in Retirement?[2], provides an extensive inventory of spending rules, including:
  • 4% Rule (constant-dollar)
  • Constant percentage
  • Steiner ABB
  • RMD
  • Kitces’s Ratcheting, and others.
At present, I tend to favor Steiner's ABB[3] for determining current safe spending, an approach which Pfau generally refers to as "actuarial" or "PMT" methods. He notes that Moshe Milevsky also believes this is a great place to start[4].

MC isn't tied to any particular spending rule, although most free online programs model constant-dollar withdrawals, aka the 4% Rule. That's unfortunate in my opinion because I consider it a very poor spending strategy.

There is no "Monte Carlo spending rule."

MC models can implement any of the rules in Wade's book or any other. MC takes the spending rule of the modeler's choice and predicts what would happen if that rule were applied every year throughout many lifetimes.

It doesn't make sense, then, to ask how MC spending compares to these rules. MC uses these rules to calculate annual spending.

If I build a simulation model using the 4% Rule, spending for the first year of my model will look essentially the same as the 4% Rule. If I build it using ABB or a constant-percent spending rule, instead, the first year spending in my simulation model will look like those. Results only begin to differ in year two of the simulation as other modeled factors, like expected market returns, change.

Sometimes when I write an MC model I make up my own rule. MC is a good way to compare spending rules.

Not all spreadsheet or "deterministic" models are the same. Ken Steiner's ABB model, for example, is quite different than spreadsheet models that simply subtract fixed spending each year and then grow the portfolio by the same expected market return growth factor. Unfortunately, there seem to be a lot more of the latter out there.

Not all MC models are the same, either, but like spreadsheet models, most of the free ones are pretty much the same. They often assume a fixed-length retirement, 4% Rule spending and probability-of-success as the evaluation criteria. More concerning, they usually predict outcomes for a portfolio, which is only a small piece of a retirement plan (see The Retirement Café: Three Degrees of Bad). A simulation for retirement planning should simulate retirement finances, not just a retirement savings portfolio.

The practical implications are somewhat complicated. Using a spending rule is relatively straightforward and accessible; good simulators not so much. Steiner offers a free spreadsheet for ABB at his website. Free RMD calculators are widely available. If you are unfamiliar with MC simulation, though, learning enough to use the tool effectively is a daunting task and probably not worth the effort.

Your best bets, in that case, are to find a knowledgeable planner who has access to good software or to pay for Laurence Kotlikoff's E$PlannerPLUS[1].

Screwdrivers are great for removing a screw but terrible at hammering a nail. Spending rules are intended to estimate a safe amount to spend from a savings portfolio in the current year but tell you nothing about the probabilities of lifetime outcomes from applying that rule repeatedly.

The smooth path of a spreadsheet projection (red in the chart below) is not a rational expectation for a real retirement, nor is the terminal portfolio value it estimates. The future projections are not a median or "expected" outcome. They're simply an assumption for estimating current spending.


I'm not even sure how to describe that TPV. We could say that it is the terminal portfolio value we would expect if the stock market returned the identical expected return every year with no sequence risk for a fixed lifetime but since none of those assumptions is realistic it is not a meaningful value.

MC simulations only estimate current safe spending by incorporating a spending rule but they're great for understanding the probabilities that determine the outcomes of the retirement finance "game."

When I suggested in a previous post that if you are planning retirement with a spreadsheet model you should test it with simulation, I wasn't suggesting that MC provides a better estimate of current safe spending — it doesn't do that, at all — but that you understand the probabilities of future outcomes. If you don't, then you probably don't have a good understanding of the risk in your plan.

I read a post complaining that these simulations are useless because the retiree can't know which of those tens of thousands of potential outcomes will be hers. That's like a poker player arguing that knowing the probabilities of the card deck is useless because a player can't predict which card will be drawn next.

If you recalculate a good spending rule every year (variable spending) you are unlikely to deplete your portfolio, although spending could become awfully tight should your portfolio fall on hard times.

(For example, there's an excellent post at EarlyRetirementNow.com[5] showing how Draconian spending cuts could become using the Guyton-Klinger Guardrails spending strategy. "Sustainable withdrawals" means you aren't likely to deplete your portfolio. It doesn't imply that the variable amount you will be able to safely spend will be enough to sustain you.)

On the other hand, simply recalculating spending annually means you're planning one year at a time. I prefer a plan with a longer horizon that is updated every year. Keep your eyes on the prize and make the necessary annual adjustments to get you there.

Spending rules estimate a safe amount to spend in the current year. Monte Carlo simulations estimate the probabilities of future outcomes one should expect when recalculating a chosen safe spending estimate every year over many lifetimes. But, MC only thoroughly covers reasonably-probable outcomes. A good retirement plan still needs a "saw" to cover the improbable.

More on that next time in Some Risks Can't be Modeled.



REFERENCES

[1] ESPlannerPLUS | ESPlanner Inc.


[2] Amazon.com: How Much Can I Spend in Retirement?: A Guide to Investment-Based Retirement Income Strategies eBook: Wade Pfau: Kindle Store


[3] Actuarial Approach – Using Basic Actuarial Principles to Accomplish Your Financial Goals.pdf, Ken Steiner.


[4] It’s Time to Retire Ruin (Probabilities), Milevsky, 2016.


[5] The Ultimate Guide to Safe Withdrawal Rates – Part 10: Debunking Guyton-Klinger Some More – Early Retirement Now




Monday, April 23, 2018

The Limits of Simulation

In a previous post, The “Future” of Retirement Planning, I explained that Monte Carlo simulation of retirement finances provides all the information available from a deterministic “spreadsheet” model and more. Among other advantages, it models sequence of returns risk.

Monte Carlo simulation, however, has its own limitations.

A reader commented on my previous post that Monte Carlo simulation “creates thousands of possible and impossible scenarios.

The “impossible” part of that statement is wrong.

In fact, the opposite is true. Monte Carlo simulation’s biggest shortcoming is that most of the scenarios it produces will be the most likely and simplest scenarios while lots of possible but unlikely scenarios that could destroy a retirement will never be simulated.

Most retirement models, deterministic or stochastic, don't model the risks that are most likely to lead to lead to bankruptcy, like spending shocks, divorce or a combination of inter-related risks.[1]

Any planning exercise begins with the basics and is then augmented by a bunch of “what-if’s.”

Planning a picnic? You’ll need a blanket, some food and some lemonade. But, then, what if it rains? What if the park is closed? What if there are too many ants or mosquitoes? What if the sun is too intense? What if someone gets a bee sting? A good plan will consider these possible bad outcomes and prepare for them.

Monte Carlo simulation is a great way to quickly generate a few hundred thousand retirement “what-if” scenarios. Analyzing them with statistics allows us to comprehend the big picture without looking at each scenario individually (an impractical task). They allow much greater in-depth analysis than the spreadsheet approach because they consider more of the key factors of retirement success and provide a lot more what-if’s but here are some of their limitations.

1. They model questionable assumptions.

Most Monte Carlo simulation models assume that market returns are normally distributed, even though we know they aren’t. We see far more — and far more severe — market crises than a normal distribution predicts. We’re either living in a very unlucky universe or we’re using an optimistic distribution for market returns. We use a normal distribution because it's the closest parametric distribution we have and that simplifies the math but we’re pretty sure the market has fatter tails than a normal distribution.

We have a couple of hundred years of market return data but that isn’t enough to create anything near a reasonable confidence interval. That is to say, our (historic) sample size is way too small to make confident guesses of the mean market return and there is no convincing argument that the next thirty years of market returns will look like the last 30 or the last 130.

(These are also problems with deterministic models.)


Monte Carlo is one of the best planning tools we have but it has its limits.
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In “Where is the Market Going? Uncertain Facts and Novel Theories”[2], John Cochrane notes that over the fifty years from 1947 to 1996 the excess return of stocks over T-bills was 8% but, assuming the annual returns are statistically independent, the standard confidence interval for the mean return ranged from 3% to 13%.

Let me say that in simpler terms. If you asked me the mean excess market return, then based on the sample data from that period I would guess it’s about 8%. But, if you then asked me how confident I am that 8% is the mean, I would say that I’m 95% confident (not totally) that it isn’t less than 3% or more than 13%. In other words, I’m not that confident. (This is also the reason that we can’t identify optimal asset allocations.)

Monte Carlo simulation addresses this uncertainty by generating scenarios with a fairly broad range of market returns. Some scenarios might have a return near 3%, for example, and others near 13%, though most would be closer to 8%. Contrast this with a spreadsheet model that assumes a single market return with no variance.

Some financial writers define market volatility as “risk” and they define “uncertainty” as not even knowing the underlying distribution. We don’t know the underlying distribution of market returns or if the underlying mean return changes over time.

The effect of all this uncertainty is that, while Monte Carlo simulations appear to generate accuracy to several decimal places, our sample size of 200 years or so of historical U.S. stock market returns is too small to inspire confidence. That doesn’t render simulation results irrelevant, however. Hurricane forecasts, as Larry Frank points out, are not very accurate but still very useful. It’s a good analogy for dynamic retirement planning.

When someone says, “My Monte Carlo planner says I have only a 5% probability of outliving my savings, so I’m good, right?”, my answer is, “Well, yes. . . assuming the market behaves much as it has in the past, that you invest your portfolio wisely and earn something near market averages, that you don’t experience a 3-sigma market crash early in retirement, that you experience no spending shocks and that you consider a 1-in-20 chance of outliving your savings “good”, then, yeah, you’re probably good.

2. Simulations are only as good as the strategy they model.

The first thing we need to know is what the simulation models. Most model the probability of outliving a portfolio of stocks and bonds but, as I explained in Three Degrees of Bad[3], portfolio depletion can’t be equated with retirement failure. Portfolio depletion can even be part of the plan.

Some retirement financing strategies are simply flawed. I believe fixed-spending strategies and set-and-forget strategies are hopelessly flawed, for example. Monte Carlo simulation of a flawed strategy for an individual household’s retirement plan is pointless.

I find the concept of “retirement ruin” to be meaningless (retirees don’t stop living and spending when their portfolio is depleted) so I have little confidence in retirement models based on probability of ruin[4,5]. U.S. retirees would declare bankruptcy if their retirement failed, emerge with some protected assets, and live off Social Security benefits. Their retirement wouldn’t simply end, though their standard of living might dramatically decline. Instead, I model the probability of not meeting desired spending.

So, when I respond, “yeah, you’re probably good”, I add, “. . . and assuming your Monte Carlo simulation used a reasonable model.”

3. Spending shocks are difficult to model, so they seldom are.

Spending shocks can decimate a retirement plan but they are difficult to model. Shocks typically have a low probability of occurring but potentially huge risk magnitude. These risks are usually better mitigated by insurance when affordable insurance is available than by relying on a low-probability of their occurrence. Even if we model them, insurance (Social Security benefits, annuities and pensions) will usually be the answer.

4. Simulations probably won’t generate rare but potentially catastrophic scenarios.

Monte Carlo simulation works by generating many of the most probable scenarios and fewer and fewer of less-probable scenarios. They won’t thoroughly analyze very low-probability market returns (tail risk), for example, because they are unlikely to generate more than a few such scenarios.


A normal distribution “tails off” at both ends. The “skinny tails” show that the probability of outcomes far from the mean are highly unlikely, which means they are equally unlikely to be included in a Monte Carlo simulation. We refer to this as “tail risk.” You can see the skinny tails of a normal distribution in the diagram above.

Outcomes in the tails are improbable but, as I recently read somewhere, the left tail should be labeled “There be dragons.”

Unlikely outcomes to the right of the mean (the right tail) aren’t a problem; those outcomes are improbably good. It’s the left tail risk that’s a problem because the distribution tells us that outcomes there are improbable but it doesn’t tell us they’re magnitude.

The reality is that we can’t estimate tail risk for the market because we don’t know the distribution of market returns. We guess that it is “normal-ish” tail risk but we know that market crashes occur far more often than a normal distribution would predict. Monte Carlo simulation isn’t helpful in predicting very unlikely but catastrophic events but then, nothing is.

In Antifragile[7], Nassim Taleb says, "[Antifragility] provides a solution to what I have called the Black Swan problem — the impossibility (emphasis mine) of calculating the risks of consequential rare events and predicting their occurrence."

5. Complex scenarios are difficult to model, so they seldom are.

Complex scenarios are difficult to conceive, let alone model. Elder bankruptcy research by Deborah Thorne[6] showed that most of the worst-case retirement finance outcomes (those that end in bankruptcy) are not caused by a single factor, like spending too much on credit cards, but by a complex self-reinforcing cycle of interdependent risks. These numerous complex combinations of risk are unlikely to be modeled.

Here’s an example that would be difficult to anticipate and therefore difficult to generate with a simulation model.

A retiree borrows a reverse mortgage, feeling secure in the fact that it is non-recourse. He knows that his loan can’t be foreclosed unless he moves out of the home, which he doesn’t plan to do. His wife becomes ill and runs up huge medical bills. They spend home equity to pay bills, then run up credit card debt and eventually file for bankruptcy. They can no longer afford to live in the home and when they leave, repayment of the reverse mortgage will be triggered.

Monte Carlo simulation can generate hundreds of thousands of possible future scenarios but they won’t include complex, interdependent risks like this one. On the other hand, Monte Carlo simulations may surprise you by showing scenarios, for example, in which purchasing an annuity actually results in a greater legacy.

7. Simulation can’t predict your future.

I recently wrote about a blog post that suggested that Monte Carlo simulation has no value because a retiree can’t know which of the thousands of possible future paths her future will track. That is absolutely true — your individual path is unknowable — but the argument is irrelevant. That argument is based on the false premise that we run simulations in order to find that path. We run simulations to collect information on the range of many paths.

A retiree shouldn’t look at simulation results, regardless of the number of scenarios simulated, and assume his or her future is in there somewhere. More often than not it will be but a good retirement plan doesn’t rely on that. A good retirement plan should also consider what happens when really bad, improbable things happen.

8. Many Monte Carlo models underestimate risk.

Many, and probably most, Monte Carlo models calculate risk of ruin simply by counting the percent of scenarios that end in ruin. Some scenarios that are counted as successes, however, may have been exposed to significantly greater risk than others. That 95% probability of success is probably best case.

At this point, you may be asking yourself why I recommend a tool with so many shortcomings. One answer is that it has fewer shortcomings than the alternatives. It considers more factors and generates more information. We look at simulation results to get an overall view of the most probable outcomes and the perspective we gain is, like weather forecasts, imperfect but highly useful.

Understanding what will probably happen and what might happen in most scenarios is a great place to start.

The important takeaways are these. Monte Carlo simulation can be a powerful tool for retirement planning because it provides more information than other approaches. Ultimately, however, we must realize that, as Yogi is credited with saying, predictions are really hard — especially about the future. The results are more of a distribution of a ballpark estimate than a single answer but it's more useful to estimate a 40% chance of rain tomorrow than to maintain that we can't know for sure so it isn't worth considering. Monte Carlo simulation will not predict or protect your retirement from "consequential rare events."

The results are also better used to compare the relative risk of one strategy to another than to measure their absolute risk. If simulation tells you that 3% spending is half as risky as 5% spending, then you can be more confident that one is safer than the other than you can be that there is actually a 3% risk that the former will result in ruin.

If this is all a little too confusing, bear with me. You can learn to use the information provided by simulations without a complete understanding of Monte Carlo models. You probably couldn't build a GPS device, either, but you're probably confident using one. Perhaps, you just need to find a planner that will run one for you. Maybe you have a perfectly fine plan built with a different type of model or no model at all and you just need simulation to improve your confidence.

Next time I’ll discuss the relationship between Spending Rules and Simulation.



REFERENCES

[1] The Retirement Café: Why Retirees Go Broke.


[2] Where is the Market Going? Uncertain Facts and Novel Theories, John H Cochrane.


[3] The Retirement Café: Three Degrees of Bad.


[4] The Retirement Café: Time to Retire the Probability of Ruin?.


[5] Financial Analysts Journal: It’s Time to Retire Ruin (Probabilities) | CFA Institute Publications, Moshe Milevsky.


[6] The (Interconnected) Reasons Elder Americans File Consumer Bankruptcy, Deborah Thorne.


[7] Antifragile: Things That Gain from Disorder (Incerto), Nassim Taleb.





Friday, March 30, 2018

The “Future” of Retirement Planning

When we decide how much money we can spend in the present year of retirement we need to know not only how much spendable wealth we have today but our best guess of how much we will have in the future. Likewise, on the expense side of the ledger, we need to know not only what our expenses were last year but also our best guess of what our expenses will be in the future. We can spend less this year, for example, if we know there is a big expense looming in the future and more if we’re pretty sure we’ll have more money in the future, say a sizable inheritance.

In short, we need a model of our retirement future to properly plan for it and even to determine a safe amount to spend this year.

Of the four inputs to this model I just mentioned, only one, our current wealth, is fairly certain.

If our entire future income will come from annuities, pensions and Social Security retirement benefits then it's relatively predictable, too. To the extent that future income will come from investments, that income is fairly unpredictable.

Expenses are unpredictable, as well. All we know for sure is how much we spent over the past few years. We can’t even be certain of the coming year’s expenses, so they too are uncertain. Retirement spending studies have shown that spending tends to decline as we age [2,3] but it doesn’t for everyone so we can’t assume that ours will. According to David Blanchett, whether or not it declines, annual spending volatility is relatively high (unpredictable from one year to the next).

When we take spending shocks into consideration, the future spending becomes even less certain. I spent $15,000 in the past year for two HVAC systems that I expected would last at least five more years. That has a much greater impact than my cable bill going up 5%.

The primary determinant of retirement cost is longevity. A five-year retirement will be far cheaper than one of 35 years. Our individual life expectancy is completely unpredictable assuming we are healthy.

As researcher Larry Frank keeps telling me, everything in an individual household’s retirement funding is stochastic, i.e., unpredictable.

Following is a graph of 200 randomly-selected portfolio value paths from a simulation of 10,000 scenarios for a retiree with a $1M portfolio from which she plans to spend $45,000 a year. All calculations are in real dollars and life expectancies are randomized using actuarial tables. It assumes a real 5.25% expected market return with a standard deviation of 12%.


Notice that most terminal portfolio values end up lower than the initial $1M portfolio value in real dollars. In this simulation, the median terminal portfolio value was about $860,000. About 75% of the scenarios ended with smaller portfolio values than the $1M they started with. This is typical of simulation results, though spending less would shift the bulk of those blue lines upward and spending more would do the opposite. The central mass of those blue lines would rotate around the starting point like clock hands, farther clockwise with more spending.

I read a comment on a retirement blog this week from a reader who said, “Retirement is uncertain so planning is useless.”

That’s like saying we shouldn’t plan outdoor activities because we can’t know future weather conditions with certainty. It’s like saying that companies shouldn’t bother developing business plans because they can’t know future economic conditions for sure. Of course you can plan where outcomes are uncertain and the best way to do that is with probabilities.

We develop retirement plans using models of the future but some models are much better than others. Nor is the model a plan. If we schedule a picnic for tomorrow and the weather models predict a 20% chance of rain, calculating the 20% is not the plan. The plan is deciding to take an umbrella or planning a backup activity. As in retirement planning, we use the model results to help create the plan.

Another blog suggested that Monte Carlo simulations can generate hundreds of thousands of future scenarios but that using them for planning is a mistake because a retiree can’t know which one she will experience. The first part of that statement is true. Your retirement's future finances might follow one of the blue lines in the chart above — assuming we ignore spending shocks — but it is impossible to know which one is yours.

There is a small chance that yours will follow a better path than any of these and a small chance that it will follow one worse and we can't ignore the latter's risk. (The former would just be sweet – we're OK with things turning out much better than we expected.)

Though it is true that we can't foresee our future path, it is also irrelevant — the purpose of the Monte Carlo model isn’t to predict an individual retiree’s path through the future (that’s impossible) but to explore a broad range of possible scenarios and develop some estimate of the probability of each actually being realized. Simulation is essentially a gigantic "what-if" analysis.

The weather forecasting model is likewise imperfect but the probabilities it provides are extremely useful. If there is a 5% chance of rain tomorrow perhaps we forego the umbrella. With a 95% probability or rain, we might cancel the event altogether. We don’t say, “No use planning based on the weather probabilities because we can’t know for sure.”


Determining how much you can safely spend this year requires a good model of the future.
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The alternative the blogger suggested was simply to build a spreadsheet for a near-worst-case life expectancy using an expected market return and ignoring stock return variance. Ignoring variance, of course, ignores sequence of returns risk. This is the model of the future you get using a spreadsheet that assumes the same expected market return every year. It's the kind of analysis we did before Bengen. It's the kind of thinking that led Peter Lynch to suggest 7% annual spending from a stock and bond portfolio would be safe.

(When I say "spreadsheet" in this post, I'm referring to any model that assumes zero portfolio volatility and a fixed life expectancy. Actually, you can use a Monte Carlo simulator and set the portfolio volatility to zero and get the same results. On the other hand, you can build a Monte Carlo simulator with market volatility in an Excel spreadsheet – I have the scars to prove it. You can download the Mother of All Monte Carlo Spreadsheets at the Retire Early Home Page[1].)

The path to the median outcome is also in that jumble of blue lines above, so the first question we should ask the blogger is, "If you can't know which of those blue paths to choose, why did you go ahead and pick one (the one with the mean annual return), anyway?"

The following chart shows all those blue paths again with the "spreadsheet" prediction of the future superimposed (red) assuming a fixed 30-year retirement and zero market return variance. That’s effectively what a spreadsheet model produces.


Why is the spreadsheet future a nice, smooth upward curve while all the simulated blue lines are jagged and head off in all directions including ruin? 

The answer is sequence of returns risk. The spreadsheet ignores market volatility and consequently, it ignores sequence risk. The model in the simulation is much more realistic.

And why does the spreadsheet portfolio end up so large compared to most of the blue lines?

The answer is sequence risk plus longevity. Note that life expectancies are simulated to generate the blue lines (they end at different years of retirement), while the spreadsheet model assumes a fixed-length retirement of 30 years. Real-life portfolios and retirees don't often last 30 years so their portfolios most often have less time to grow.

Of all the paths on this chart, the red spreadsheet path is by far the least likely for you to experience. Twenty consecutive years of identical positive portfolio returns is unimaginable.

With 10,000 simulated scenarios, fifteen survive 20 years and end up within 1% of the spreadsheet path value at 20 years. These are fifteen possible paths to reach the spreadsheet value at 20 years and they don't get there in a straight line, as you can see on the following chart. So, the spreadsheet path is in there, but why one would choose it as the representative outcome remains a mystery.


The path that reaches the median terminal portfolio value, among the 10,000 simulated scenarios, is shown on the graph above in orange. It ends at year 17, which is roughly the median life expectancy for this 65-year old. The spreadsheet path presumably uses average historical market returns, so why is its outcome at 20 years ($1.2M) so much higher than that of the median simulated outcome of $860,000?

The chart shows that using the average market return every year in a spreadsheet (the red line) doesn't produce the average outcome (the orange line). You're probably tired of hearing me say "sequence risk and stochastic life expectancies are the difference" but simulations model them and spreadsheets don't.

The spreadsheet path is quite optimistic. If you insist on a spreadsheet model, you should at least reduce the expected return to compensate for sequence risk. In this comparison, you would need to reduce the expected portfolio return in the spreadsheet model from 5.25% to 3.5% to obtain results similar to the simulation's median outcome at 20 years.

Lastly, let's look at a density histogram of all portfolios that survived at least 20 years.


The blue bars show the portfolio values after 20 years for those 956 portfolios and retirees who survived at least that long. It's a probability density histogram, so the total area of the blue bars equals 1.

The orange curve shows the continuous density. As you can see, the distribution is right-skewed and not a symmetrical normal distribution. The median is less than the mean due to all those huge but highly improbable outcomes along the right tail.

We're more interested in the median ($645,000), the value at which half of the portfolios are larger and half smaller. About 57% of the outcomes after 20 years are less than the mean ($702,000) compared to the 50% of outcomes that are less than the median. The median is the more representative statistic with this skewed distribution.

Finally, the red vertical line represents the spreadsheet model's portfolio value after 20 years, $1.17M. At the 20-year mark, that red portfolio value is larger than 88% of the simulated portfolios that survived that long. $645,000 is a much more representative expectation after 20 years than the spreadsheet prediction.

It's true that you can't predict which of those 10,000 blue paths your future will mimic but the spreadsheet outcome is one of those. Pick it and you simply decided to pick a path from the 10,000 choices after saying you couldn't. And, then you picked a very unlikely and optimistic one. The spreadsheet predicts portfolio values in the absence of sequence and longevity risk and tells you nothing about the probability of realizing them.

Furthermore, the purpose of simulation isn't to predict your future but to explore the possibilities, so you aren't intended to choose one.

We need a model of the future to plan retirement. We need it to even calculate the safe amount to spend this year. Simulation is a good starting point.

The takeaway, for now, is that if you have planned your retirement with a spreadsheet model, you should take another look, especially if your plan shows a single straight path to doubling (or more) your initial portfolio. It could happen; it just isn't likely and if it does happen it certainly won't be a smooth path.

If you're using an online calculator, make sure it incorporates simulation. There's a Monte Carlo version of E$Planner, for example, and there are free simulators online.

But simulations have issues, too, so they're only a starting point. I'll discuss the Limts of Simulation next time before describing how to make sense of that jumble of blue lines.



REFERENCES

[1] Download The Retire Early Home Page spreadsheet.


[2] Expenditure Patterns of Older Americans, 2001‒2009, Sudipto Banerjee, Employee Benefit Research Institute. (Download PDF.)


[3] Estimating the True Cost of Retirement, David Blanchett. (Download PDF.)




Thursday, March 15, 2018

The Pros and Cons of Bucket Strategies

Continuing recent posts updating my past descriptions of retirement strategies, let's look again at time-segmentation (TS) or "bucket" strategies.

The basic implementation of time segmentation strategies sets aside enough cash and short-term bonds to cover the next few years of retirement expenses, let’s say five, then covers the following few (let's say years six through ten) years' expenses with intermediate bonds, and finally allocates any remaining assets to stocks.

Note that this is a markedly different way of allocating assets than is typically used by other strategies that base equity allocation on the largest loss a retiree can stomach in a market downturn and the optimal asset allocation to avoid prematurely depleting a savings portfolio.

Many retirees will find that setting aside five or six years of expenses in a cash fund will be a significant portion of their investable assets so this might be a dramatically different allocation.

Here's an example. A retiree wants to spend $40,000 annually from a $1M portfolio. She invests a little less than $200,000 in cash and short-term bonds (the discount rate is low, especially in today's capital markets, so we can roughly just multiply annual spending by 5) to cover expenses for the next five years. She invests a little less than $200,000 (less because they yield a little more) in intermediate bonds and roughly $600,000 in stocks. It is her estimated future spending that determines her asset allocation of 20% cash, 20% bonds and 60% stocks.

TS strategies don't typically recommend an annual safe spending amount like the $40,000 in this example but this can be estimated by any of the (preferably variable) spending strategies.

This part of the TS strategy is based on matching asset duration[1] to the duration of expenses and is financially sound.

Asset duration, in simplest terms, refers to the recovery period typically needed after a market downturn or interest rate increase. The duration of an expense is essentially the number of years until it is due but expected inflation must be considered, too.

Matching a near-term liability with a long-duration asset like stocks would provide a greater expected return but less confidence that the money would actually be available when needed if stock prices declined. Matching a long-term expense with an intermediate bond would have greater certainty but a lower expected return. "Liability matching" provides the greatest asset return for which the expense can be reliably met and is a key component of TS strategies.

Short-term bonds may have a duration in the neighborhood of three years, intermediate bonds 5-10 years, and stock market duration is measured in decades. This simply means that we can be pretty sure of the value of a 3-year bond in three years but not less, the value of cash next year, and that we probably need to invest in stocks for 7-10 years to be pretty sure our investment won't be looking at a loss.

Planners often recommend that the bonds are set up as a ladder held to maturity to mitigate interest rate risk but many planners simply use bond funds of short and intermediate durations assuming that the results will be "close enough" to those of bond ladders.

The expressed goals of TS strategies are to match expense durations to asset durations, to help retirees better understand the purpose of their different assets, and to weather bear markets without the need to sell stocks at depressed prices and thereby avoid “panic selling” in a market downturn.

Liability-matching is a sound financial policy, while the latter two are primarily psychological benefits. In fact, from a financial perspective, to quote Wade Pfau:
... it must be emphasized that on a theoretical level, income bucketing cannot be a superior investing approach relative to total returns investing.[2]
The reason is that bucketing typically requires a much larger cash and short-term bond allocation than other (total return) strategies. The difference between the returns available from these two assets and what their value might have earned in the stock market is referred to as "cash drag." You simply earn less money if a larger portion of your portfolio is held in cash instead of invested in stocks.

In a paper entitled, “Sustainable Withdrawal Rates: The Historical Evidence on Buffer Zone Strategies[3], authors Walter Woerheide and David Nanigan showed that the drag on portfolio returns from holding large amounts of cash can be significant.

In other words, the comfort of a large cash bucket can come with a heavy cost. According to the authors, the performance drag imposed by a large cash bucket actually leaves the typical portfolio less sustainable. That suggests that TS strategies increase the security of income for the next ten years but do so at the cost of less security of income in the years beyond.

Said differently, the goal of TS strategies is to reduce sequence risk, i.e., to reduce the probability of outliving one's savings, by encouraging the investor to avoid selling stocks at low prices. Woerheide and Nanigan, however, show that this strategy's cash drag is typically greater than the benefit of avoiding selling low and often achieves the opposite, a less sustainable portfolio.



Are bucket strategies easier for retirees to understand or is their explanation simply easier to get away with?
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The goal of building a cash bucket to weather bear markets conflicts with the goal of maximizing portfolio returns (and thereby increasing portfolio sustainability) and can backfire. The longer the cash bucket the greater the cash drag. The shorter the cash bucket the less likely it is to outlast a bear market.

It has also been argued that TS strategies reduce sequence of returns risk and they probably do when they work, meaning when they outlast the bear. But, Moshe Milevsky showed in “Can Buckets Bail Out a Poor Sequence of Investment Returns?” that this strategy cannot always avoid sequence risk. When a retiree spends all his cash in a market downturn he can be left with an extremely risky all-equity portfolio, possibly before the bear market ends, with the postponed selling having had the unhappy effect of waiting to sell stocks until near the market's bottom.

Technically, bucket strategies are not “floor and upside” strategies but, as I have noted in previous posts, most Americans are eligible for Social Security retirement benefits. Consequently, most Americans have a floor, no matter which strategy they prefer, though it may not be what a retiree would consider an adequate floor — living off Social Security benefits alone isn't pretty.

While floor-and-upside strategies are meant to provide confidence that the retiree will never fall below a certain level of income for a lifetime, bucket strategies attempt to inspire that confidence (not always justified, as Milevsky explained) for only the length of the bond ladder.

I often think of the floor issue by imagining that my upside portfolio has been completely depleted. This is an unlikely scenario to be sure unless one is spending from that portfolio, but it forces me to imagine my circumstances in a potential failure scenario. Using a bucket strategy, I would have no stocks from which to replenish the longest rungs of the bond ladder in that event, so my income beyond this "rolling ladder" is clearly dependent upon equity performance and is not secure.

The stock allocation will decline with age as the short- and intermediate-term buckets slowly come to dominate the portfolio. At some age, the portfolio will contain mostly bonds and cash.

TS strategies recommend spending first from cash, then from bonds, then from equities, but as the Michael Kitces explains[4], that is pretty much what happens when we rebalance a SWR portfolio. Rebalancing results in selling assets that have recently experienced the highest growth. If stock prices have fallen, rebalancing ensures that it is other asset classes that will be sold. With rebalancing, stocks are sold after their prices go up.

Lastly, how many retirees — or planners, for that matter — understand these risks?

It's simple enough to explain to a retiree where the funds are coming from to pay bills for the next several years. But, unless she also understands that buckets can fail, that increasing the cash bucket to avoid failure dilutes her expected portfolio returns, and that income for future years funded by the stock market is still at risk, then this benefit of bucket strategies is not a true understanding but simply a psychological salve.

If that's the case, are bucket strategies easier for retirees to understand or is their explanation simply easier to get away with? The arguments for bucket strategies are not that the strategy itself is easier to understand but simply that it is easier to understand the purpose of their asset allocations.

Planners report that bucket strategies improve the bear-market behavior of their clients and their planners find that quite valuable. There's nothing wrong with that if the retiree understands the cost of this behavior management — the long-term sub-performance of an overly-conservative TS portfolio is likely outweighed by the losses they avoid by not selling low.

It's hard to evaluate that comparison because it is largely dependent upon the retiree's self-control but it seems a steep price to pay for this guardrail, especially compounded over a long retirement.

A strong urge to sell in bear markets could just be a sign of an overly aggressive asset allocation. Finding a more tolerable asset allocation between that and a 20% cash allocation might be a better answer.

No retirement funding strategy is perfect and I think a sub-optimal strategy is better than no strategy. Or, as my friend, Peter is fond of saying, bad breath is better than no breath at all.

Ultimately, I firmly believe that the best retirement plan is the one that lets you sleep at night.



REFERENCES

[1] Efficient Frontier, William Bernstein.

[2] The Yin and Yang of Retirement Income Philosophies, Wade D. Pfau, Jeremy Cooper.

[3] Journal Sustainable Withdrawal Rates: The Historical Evidence on Buffer Zone Strategies, Walter Woerheide and David Nanigan.

[4] Is A Retirement Cash Reserve Bucket Unnecessary?, Michael Kitces.

Friday, February 23, 2018

Unraveling Retirement Strategies: Variable Spending from a Volatile Portfolio

 In Unraveling Retirement Strategies: Constant-Dollar Spending (4% Rule), I described retirement funding strategies like the “4% Rule” that base portfolio spending on a calculation made at the beginning of retirement that remains unchanged in real dollars regardless of how the household’s finances unfold over time.

Constant-dollar spending is like the Stephen Colbert joke about a man whose beliefs are constant. He believes the same thing on Thursday that he believed on Tuesday ... no matter what happened on Wednesday.

That doesn't work well for retirement planning, either.

Variable-spending strategies are similar to constant-dollar strategies in that they spend periodically from an investment portfolio but differ in that they spend a periodically updated amount based on portfolio performance – they spend more in good markets and less in bad markets.

This is a huge difference. We have two basic choices in portfolio-drawdown strategies: spend a predictable amount annually and risk depleting our portfolio or spend an unpredictable, possibly painful, amount annually to avoid portfolio depletion.

Spending strategies, including these two, explore ways to draw down a portfolio without outliving it but they do so without considering the expense side of the equation.

Regardless of which of these strategies you choose, you will spend the amount you need to spend after retiring. If you need a kidney operation or a new roof or a check for the IRS, you will pay for those things regardless of what your spending strategy recommends. That will increase your chances of outliving your savings but that risk isn't considered by these "income-side" strategies.

There are many variable spending strategies. I recently attended a webinar in which Wade Pfau identified a half dozen of the better known and in Making Sense Out of Variable Spending Strategies for Retirees[1] he compares several more.

Joe Tomlinson, Steve Vernon and Wade Pfau recently recommended using the spending percentage for Required Minimum Distributions (RMDs) from qualified retirement accounts[2]. Vernon provides a summary of the study in "How to Pensionize Any IRA or 401(k)."[6]

RMD is based on the assumption of a retiree and a spouse 10 years younger. Retirees closer in age to their spouse can perhaps use the Modified RMD strategy and spend 10% more. Your investment company will calculate RMDs for your qualified retirement accounts when the time comes or you can find a calculator online.[3] You are required by tax law to use these calculations on tax-deferred retirement accounts but you can, of course, use them on all types accounts if you choose.

Another strategy is to spend a fixed percentage, say the same 4%, of the new portfolio balance each year, though the safe spending rate actually increases as life expectancy decreases. It makes more sense to spend that gradually-increasing percentage of one’s current portfolio balance each year than to always spend a fixed percentage of a changing portfolio balance. It approaches 10% late in retirement but grows slowly at first.

Most Americans are eligible for Social Security benefits so most have a floor. It may not be an adequate floor in the event that your portfolio is depleted, but it is a floor. The variable spending strategies and the constant-dollar strategies, therefore, technically manage the upside portfolio of a floor-and-upside strategy and will rarely be a standalone strategy.

I recommend, once again, reviewing this strategy in Pfau and Jeremy Cooper’s The Yin and Yang of Retirement Income Philosophies[4]. I particularly recommend the introduction to the work of Blanchett, Mitchell and Frank[6] on dynamic spending at the end of the variable spending strategies review. Their strategy periodically updates the critical assumptions of a retirement plan. (Frankly, I don’t see a rational alternative.)

It effectively says, “When the road in front of you turns or ends, modify your car’s behavior accordingly.”

A light pole oddly stood in the middle of the Sears gravel parking lot in my hometown. Some wise person had painted two arrows on the pole curving away in opposite directions. Below the arrows were the words, “Turn. Go left or right.”

Sounds like sage advice.


Variable-spending strategies make a lot more sense.
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The challenge with the dynamic spending strategy is that it is mathematically complex and will be difficult for most retirees or even planners to implement. I suspect, however, that you would achieve similar results with any variable spending strategy if you updated your spending percentage annually to reflect decreasing life expectancy (strategies like RMD do this for you) and based the spending amount on your current portfolio balance. Blanchett, Frank and Mitchell point out that asset allocation plays a smaller role.

The Blanchett-Frank-Mitchell study shows that life expectancy plays a critical role in determining a safe spending amount. Life expectancy declines as we age. Some variable-spending strategies, like RMD and actuarial approaches, consider decreasing life expectancy in their calculations while others, like spending 4% of remaining portfolio balance, don't. I recommend you choose one that does — it's a key factor.

To implement a variable spending strategy, choose a variable spending rule that suits your fancy[1]. Which you choose probably has less impact on portfolio depletion risk than the act of recalculating it annually, so long as it incorporates changing life expectancy.

I personally prefer the dynamic strategy, Modified RMD for simplicity, Milevsky’s formula[4], and actuarial strategies[5].

I’ve written several posts on asset allocation and it has been thoroughly discussed in several threads, including Unraveling Retirement Strategies: Constant-Dollar Spending (4% Rule). You won’t go terribly wrong with an equity allocation between 40% and 60% and it’s difficult to prove that another will work better across a broad range of outcomes. The same rules apply to variable spending portfolios.

I recommend a floor to go along with an upside variable spending portfolio to make sure you can survive if the improbable happens.

Constant-dollar strategies tell you to spend the same amount every year and that you probably won't run out of savings over a fixed thirty-year retirement. They don't consider what happens if you do.

Variable spending strategies tell you to spend more when you have more money and spend less when you have less money. The better variable spending strategies also consider remaining life expectancy and tell you that you can spend a higher percentage of your remaining savings as you age. Annual spending isn't predictable but you are unlikely to outlive your savings.

Again, seems like sage advice. Variable-spending strategies are so much more rational that I personally dismiss constant-dollar spending strategies entirely.

Retirees who have a pension, Social Security benefits or have purchased an annuity, which covers practically all American retirees, will actually be building a floor-and-upside strategy and managing the upside portfolio with a variable-spending strategy. Floor-and-upside strategies, however, will focus more on the floor and will likely recommend one higher than Social Security benefits alone are likely to provide.



REFERENCES

[1] Making Sense Out of Variable Spending Strategies for Retirees, Pfau.



[2] Optimizing-Retirement-Income-Solutions-November-2017-SCL-Version.pdf, Pfau, Tomlinson, Vernon. (Very lengthy, consider [6], instead.)



[3] Estimate your required minimum distributions in retirement, Vanguard.



[4] The Yin and Yang of Retirement Income Philosophies, by Wade D. Pfau, Jeremy Cooper.



[5] How Much Can I Afford to Spend in Retirement?: Spreadsheets, Ken Steiner.



[6] How-to-pensionize-any-IRA-401k-final.pdf, Steve Vernon.



[7] An Age-Based, Three-Dimensional Distribution Model Incorporating Sequence and Longevity Risks, David Blanchett, Larry Frank, John Mitchell.






Monday, February 12, 2018

Unraveling Retirement Strategies: Constant-Dollar Spending (4% Rule)

Sustainable Withdrawal Rate (SWR) strategies are based on the work of William Bengen[1], whose research uncovered sequence of returns risk. The basis of the strategy is that there is a constant amount of spending from a stock and bond portfolio that would have been “safe” in 95% of historical 30-year periods of stock returns.

SWR had a colorful beginning. Peter Lynch of Magellan Fund fame posited that a retiree should be able to invest in stocks and spend about 7% of her portfolio forever. Scott Burns quickly showed that a 7% withdrawal rate was far riskier then Lynch imagined.[2]. (The culprit, as Bengen would show, is sequence of returns risk. The order of market losses is more important than the average return.)

Lynch’s response was, “OK, but surely there is some percentage that would work?”

Bengen found that the safe withdrawal percentage rate in the U.S. was historically 4% to 4.5% over rolling 30-year periods of market returns, hence the “4% rule."

Wade Pfau later showed that number only worked in the U.S. and a handful of other countries[5]. More recent work by Pfau suggests that the number at present is perhaps 3% to 3.5% — a sizable range. A range of 3% to 4.5% may sound small but it’s the difference between a safe spending amount of $30,000 and $45,000 a year per $1M of savings. Regardless, it’s well below Lynch’s 7% assertion.

The basic process for implementing this strategy is for a retiree to calculate 4% (or 3% or 4.5%, depending upon who you choose to believe — I'd go with Pfau) of her total investment portfolio value the day she retires and to spend that dollar amount (not percentage) for the rest of retirement, increasing it annually by inflation.

A retiree with a million dollar portfolio who agrees with Pfau's 3.5% could spend $35,000 the first year of retirement. If inflation ran 2% that year, he could spend $35,700 the following year.

This strategy will result in two possible outcomes when simulated, though actual retirees might not behave this way. The strategy will produce a constant, inflation-adjusted income amount from the portfolio until the retiree dies or the portfolio is depleted, whichever comes first. SWR practitioners try to minimize the latter outcome to “only 5% or 10%” of retirements, or 1-in-10 to 1-in-20.

With all due respect to Bengen, whose research exposed sequence risk — an important contribution — I consider this strategy irrational and believe that it probably makes sense only for households with so much savings that they don’t need it. The idea that we can spend an amount calculated at the beginning of retirement and continue spending it regardless of what happens to our financial situation over perhaps 30 years is not only risky but irrational.


Constant-dollar spending strategies are risky for households that aren't wealthy and unnecessary for those that are.
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As retirement progresses, our finances and life expectancy will change, our finances for better and for worse. Life expectancy constantly declines. Constant-dollar spending is a strategy to ignore any of this new information after the original spending amount is calculated.

Larry Frank, David Blanchett and John Mitchell published research[3] showing that our spending should be “dynamically” adjusted as our finances change over time but you probably don’t need to read the research to understand this.

Instead, have this conversation with your 75-year old wife. “How much can we spend this year, Walter?”

“$45,000.”

“Thanks, but how do you know that, Dear?”

“It’s the amount we could safely spend a decade ago based on our life expectancy and wealth back then.”

Let me know how that conversation works for you.

Wade Pfau and Jeremy Cooper wrote a great explanation of the strategy (and others) for Challenger Ltd[4]. Granted, mine is more cynical, but they’re decades from retirement and I’m a decade into it. I have more skin in the game.

Here are some considerations I have learned by running a gazillion retirement simulations that you probably won’t find elsewhere without a lot of digging.

SWR strategies are based on the assumption that future market returns will be similar to historical returns but there is a lot of reason to believe they will be lower in the future. Even if they are similar, we don’t know the expected market return, whether it changes over time or even the distribution of those returns. We pretend they are normally distributed, largely because it makes the math easier, but empirical evidence shows that there are far more extreme market events than a normal distribution would predict. That’s a lot of uncertainty on which to bet one’s retirement.

Many retirees who like this strategy believe that they are creating their own annuity without committing a large sum of money to an insurance company. There is a specious similarity to an annuity in that both provide constant income but SWR is like an annuity from an insurance company with a 5% to 10% chance of going out of business.

Further, annuities provide maximum lifetime consumption while SWR strategies are economically inefficient. It’s expensive to tie up 96% of your wealth so you can safely spend 4% of it[6].

Self-annuitizers may expect that have more liquidity with a SWR strategy than they actually have. In the same way I explained that the liquidity of TIPS ladders can be illusory, spending from an SWR portfolio to meet large, unanticipated expenses means spending income you were counting on for the future. Certainly TIPS ladders and investment portfolios are more liquid than annuities but there is a price to pay in the future for spending them early.

A high spending percentage increases the probability of outliving the portfolio and reduces the expected terminal portfolio value, which is often part of a planned bequest. At the other extreme, a low spending percentage decreases the odds of portfolio depletion but increases the expected terminal portfolio value. This has some interesting implications. The following charts show the relationship.



Retirees with limited wealth relative to their spending needs may need to spend a larger percentage and accept a greater portability of outliving their savings. They are less likely to accumulate a large terminal portfolio.

Retirees with adequate savings can play it safe with a low withdrawal rate but they are more likely to die with a large portfolio. This is a good thing for households with a strong bequest motive but not so good for those without. Without a bequest motive, a retiree who plays it safe with a low withdrawal rate may find late in retirement that she has an extra million bucks she could have spent to enhance her life.

This may be ideal for a household with so much wealth that they can easily afford their desired standard of living and still expect a large portfolio to leave to heirs but then one must ask why a household this wealthy needs a SWR strategy, at all.

As I explained in Retirement Income and Chaos Theory, constant-dollar spending strategies are probably chaotic when the portfolio is sufficiently stressed. It’s a bit like hanging around the event horizon of a black hole in that scenario where just a little bit of bad luck can nudge your strained household finances into an irreversible downward spiral.

In a post entitled, "Time to Retire the Probability of Ruin" back in April 2015, I wrote that we should stop basing retirement plans on this metric. A short time later, Moshe Milevsky wrote a better piece entitled, "It’s Time to Retire Ruin (Probabilities)"[7].

Constant-dollar spending strategies are quite unpopular among economists and most of the researchers I know. They are sometimes popular among planners who charge fees based on assets under management and retirees who see them as an annuity alternative.

I am none of those and not a proponent of constant-dollar spending strategies. I have many reasons, but the most basic are that it is irrational to ignore new information that comes available as retirement progresses and financially unsound to attempt to derive constant income from a volatile portfolio. The strategy is risky for retirees who are not wealthy and unnecessary for those who are.

Ultimately, it isn't possible to re-create an annuity with a one- or two-person risk pool. Rational strategies to spend from a volatile portfolio will suggest that we spend more when our portfolio grows in proportion to our spending and life expectancy and demand that we spend less when it shrinks. That requires a variable spending rule strategy, which I will address next.



REFERENCES

[1] Conserving Client Portfolios During Retirement, William Bengen.



[2] Dangerous Advice from Peter Lynch, Scott Burns.



[3] An Age-Based, Three-Dimensional Distribution Model Incorporating Sequence and Longevity Risks,  Frank, Mitchell, and Blanchett.



[4] The Yin and Yang of Retirement Income Philosophies, Pfau, Cooper.



[5] Journal The 4 Percent Rule Is Not Safe in a Low-Yield World, Wade Pfau.



[6] The 4% Rule - At What Price?, Scott, Sharpe, and Watson.



[7] It’s Time to Retire Ruin (Probabilities), Moshe Milevsky.






Tuesday, February 6, 2018

Will the Market Go Up or Down from Here?

The answer is yes. It will go up or down from here.

Whenever the market has a large setback (this one is 7% so far, but it happened quickly and may or may not be finished) many of us feel a responsibility to tell our readers not to panic.

So, here's my advice: don't panic. (I hope to provide more useful advice below.)

To the extent that history is a guide, the market will be higher sometime in the future but no one knows when that will be.

It could be Friday.

On the other hand, stocks took 25 years to recover from the Great Depression and 16 years to recover from multiple financial crises beginning in 1963[1]. It took only six years for the market to recover from the 2007 sub-prime mortgage crisis.

When you read how quickly the market recovers from big losses, it's important to note that a retiree's portfolio is not the market index. It probably took longer for a retiree to recover from those losses than it took the market because she was selling stocks to pay bills during that period. At the other extreme, someone in the accumulation phase might have recovered sooner than the market if they were not spending but instead contributing additional savings during those years.

Saving during your working career is like periodically throwing more money into your retirement boat. Spending from that portfolio during retirement is like owning a leaky boat.

Three more pieces of advice.

It is important to ignore the advice of those who say this is the beginning of a much larger market decline because they can't know; they're only guessing.

It is equally important to ignore the advice of those who say this is a great buying opportunity because they're guessing, too.


Ignore those telling you this is the beginning of a crash. They're only guessing. Also, ignore those saying it's a buying opportunity. They're guessing, too.
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You should pay more attention to experts who simply admit that they don't know. Unfortunately, no one is going to interview them because they're boring.

My wife received a text message from a friend last night. "Mary wants to know if they should buy or sell?" she asked from the other room.

Assuming Mary was really asking if the market will go up or down from this point, my initial answer was that they should go to a movie. After a little more thought, I admitted to myself that I know little about their finances and maybe there are good reasons for them to buy or sell, though short-term market volatility wouldn't be a good one.

"How much of their retirement savings have they invested?" I asked.

"She says all of it."

OK, so that gets my attention. That portfolio would have fallen over 50% during the Great Recession. I couldn't tolerate that but maybe they could. I usually recommend 40% to 60% equity for a portfolio from which a retiree is spending. If there are no known liabilities to match (future bills to pay) with that portfolio, I might go with 80%.

"She says they'll be fine — they survived the 9/11 market crash."

So, three important points. First, the market fell about 14% after 9/11. It rebounded 21% in three months. Hardly the Great Recession's 50% loss and not much of a test of one's risk tolerance.

Second, Mary and her husband were working back in 2001 and presumably saving for retirement. As I explained above, there is a world of difference in recovery time between the accumulation phase and the distribution phase.

Third, Mary is trying to time the market and research overwhelmingly shows that no one can time the market and that you will likely lose even more money if you try to.

I promised to provide some more useful advice, so here it is. After you refuse to panic per my previous instruction, reconsider your risk tolerance. It should be lower after retirement because you no longer have a safety net of new savings contributions and no job, for that matter. Retirement is riskier.

If this recent market crash made you feel a need to sell, then it has done you a favor — it's telling you that your equity allocation may be uncomfortably high. After you weather this market volatility, consider lowering your equity exposure.

I like William Bernstein's recommendation to limit your equity exposure in retirement to the maximum loss you could tolerate in a severe bear market. The following table was published before 2007 in The Four Pillars of Investing but I held 40% equity back then and my portfolio fell only 15%, as he predicted.


Be forewarned that if you held an uncomfortable equity allocation before the downturn and lower it before the recovery, that recovery will take longer. If your portfolio fell precipitously because you were holding 90% equities and you lower that to 60%, it won't climb as quickly as it fell.

Should that happen it will be the result of a previous error — overestimating your risk tolerance. That past mistake may cost something but you can fix it going forward.

Your risk tolerance changes over time and is generally much lower during a market decline than you expected it would be during the previous bull market.

So, don't panic. If you don't feel panicked, then your equity allocation may be just fine. If you do feel a bit anxious, wait until the smoke clears and then think about whether you have underestimated your risk tolerance. Adjust your equity exposure then.

The worst thing you can do is panic and sell at a market bottom, though that is exactly what many people do.

In the meantime, ignore the guessers.


REFERENCES

[1] The Dow’s tumultuous history, in one chart, MarketWatch.



Friday, February 2, 2018

What's a Floor?


After my last post, The Retirement Café: Unraveling Retirement Strategies: Floor-and-Upside (An Update), I received several comments and emails regarding floor portfolios that made me realize that the definition of a floor isn’t universally applied and that I need to communicate the definition that I use more clearly.

In "How retirement savers construct an income floor"[1], Stan Haithcock suggests the following:
"You need a solid income base to build on and to hopefully add to those guaranteed amounts. These income sources can include your Social Security, pensions (if so fortunate), income-producing real estate, dividends from stocks, bonds, and contractual annuity payments."
While I find that the column provides generally sound advice, I don't agree that all the assets in this list should be used to build a floor. Real estate income depends on real estate market performance, stocks have market risk so their dividends do, as well. Bond income has bond market risk unless laddered and held to maturity.

I received other comments from readers that considered potential floor assets to include a rolling 10-year TIPs ladder. Deplete your portfolio and how will you buy future rungs? There was even a suggestion that RMDs are floor income, although they totally depend on portfolio performance.

Some seem to define a floor portfolio as an income portfolio complementing the upside stock portfolio and believe that any investment that yields income is suitable for a floor. I don't view floors that way and I don't believe that Bodie, Merton and Samuelson[2] had that in mind when they envisioned lifecycle finance.

I found the following an excellent explanation from a Bogleheads thread[3]. "bobcat2" explains:
"The life-cycle approach ("floor" plus upside approach) is the general economics approach to financial planning including retirement planning. The older approach (called mean/variance or "probabilistic") is based on risk-return tradeoffs along the efficient frontier and is a special case of the life-cycle approach. In that special case, the floor goal is either non-existent or very low, and the aspirational goal is soft. ("I would like to have this much or more, but perhaps not realizing that the “or more” reduces the chances of meeting the goal.")

There is no pure life-cycle approach. You pick two goals. One goal is what you want [upside]. The other goal is a lower conservative goal that typically you want to hit with very high probability [the floor]. You are serious when you set or reset the goals and you employ investment strategies that are explicitly targeted to meet the goals. If you want to hit the lower goal with near certainty, you are going to have to hedge or insure, not diversify, the risk of reaching that goal. That means you need a matching strategy to reach that conservative goal both before and during retirement." 
We "insure" the "near certain" floor with annuities, Social Security benefits, pensions, and possibly a very long and expensive TIPs bond ladder or a shorter, non-rolling ladder supplemented with a deferred income annuity at its end[4] that's less expensive.

Dividends, bonds or bond funds other than laddered TIPs held to maturity, RMDs, real estate income and rolling ladders are not "near certain" and, therefore, not predictable.


What's a floor, anyway?
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I view a floor portfolio as a safety net of near-certain income in case factors beyond my control should leave me with nothing else.

My grandparents suffered the effects of hyperinflation that destroyed their finances. People used to refer to their predicament as “living on a fixed income” but what they meant was that they no longer received pay increases from an employer to offset inflation. The purchasing power of their pensions and savings accounts eroded quickly.

When I think of a floor portfolio as a safety net, I imagine that my client’s other assets are depleted and that they are forced to live only on income from the floor. I want to make sure that their floor income can withstand some pretty serious inflation, so I consider inflation protection a critical component of a floor portfolio.

A dear friend lost his entire $4M retirement portfolio during the Tech Crash just a few years before his planned retirement. When I think of a floor portfolio as a safety net, I imagine that my client’s investment portfolio is depleted and he is forced to live only on income from the floor portfolio. I consider mitigation of market risk critical in a floor portfolio. Market risk (any market) belongs in the upside portfolio.

For a decade now, retirees have been hurt by historically low interest rates that have left safe income sources like CDs and money market returns barely worth the effort, so I consider the mitigation of all capital market risk to be critical in a floor portfolio.

Growing up in a rural community, I had several relatives and friends of relatives who were trying to get by on Social Security benefits alone. It wasn’t pretty.[5]

They were mostly widows whose husbands, often deceased for a decade or two, likely hadn't been able to afford to delay Social Security benefits or didn't understand the value of delaying, which greatly reduced their spouse’s survivors benefits. When I think of a floor portfolio as a safety net, I imagine that my clients don’t want to end up living off Social Security alone in old age. I recommend they delay Social Security benefits as long as possible. I consider mitigating longevity risk to be a crucial component of a floor portfolio.

It is also worth considering building a floor with as many judgment-proof and bankruptcy-proof assets as you can.

Those three goals, mitigating inflation risk, mitigating capital market risk, and mitigating longevity risk are, in my personal view, essential to a floor portfolio’s design. Combined, they provide a pretty strong safety net of near-certain, real lifetime income.

Of course, not all risk can be mitigated. Spending shocks, for example, can destroy our finances even with an adequate floor. The floor defines the amount of safe income available but it has no sway over costs.

One last but critical consideration is the amount of floor income you target. Don't overdo it. Even small floors can be expensive. Design the rest of your plan such that having to live off floor income alone is very unlikely.

Sleeping on the floor is a more tolerable consideration if the chances of ending up there are small enough. At the other extreme, retirees who plan to spend 5% of their investment portfolio for thirty years in retirement probably want a cushier floor. If I had a 10% chance of losing my bed, I'd keep an air mattress nearby.

I don't get to define what constitutes a floor but it is important to understand the definition I have in mind when I use the term in posts.

It's fine if you or your retirement planner use a different definition as long as you agree and understand how it differs from the lifecycle economics definition. Just know that, with a different definition, some of your floor might not be there in certain scenarios when you need it.

It's challenging to build a perfect floor for several reasons. The cost of retirement is unpredictable and changes over time[6]. You may not claim Social Security the year you retire and filling the safe income gap until you do can be problematic. Pensions provide lifetime income but most aren't inflation-protected. An inflation-adjusted immediate annuity is in many ways the best answer but many retirees won't buy one. Flooring is very expensive in today's economy.

For these reasons, you are unlikely to find a perfect answer and will need to make concessions. But, it's important to begin the process with some basic goals in mind and to imagine the future scenarios in which you might have to live off floor income.

I begin with the goal of a floor portfolio that provides near-certain safety-net income and I try to fill it with assets that in combination mitigate inflation risk, capital market risk, and longevity risk to guarantee that I can survive improbable but worst-case outcomes. Because floors are expensive, I build mine as low as I think I could tolerate and then I structure the rest of my retirement plan to minimize my chances of rolling off the bed.


REFERENCES

[1] How retirement savers construct an income floor, MarketWatch.



[2] Videos - Robert C. Merton Finance Class at MIT



[3] Wade Pfau: Lifecycle Finance - Page 3 - Bogleheads.org.



[4] The TIPS plus DIA strategy is discussed in this column by Wade Pfau. It contains links to the original research. Safe Retirement Income with TIPS and a deferred annuity, Wade Pfau.



[5]9 Ways to Retire on Social Security Alone, AARP.



[6] Estimating the True Cost of Retirement, David Blanchett. >