Originally Aired: March 16, 2011
Topic: Safe Withdrawal Rates with Special Guest, Geoff Considine
The Lange Money Hour: Where Smart Money Talks
James Lange, CPA/Attorney
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- Introduction of Geoff Considine, Asset Management Analyst
- Safe Withdraws Depend on Probability of Running Out of Money
- Factor in the Possibility of Another Market Downturn
- Volatility of Investments Drives the 4 Percent Withdrawal Rule
- One Snapshot in History Can’t Show the Range of All Possibilities
- Longevity Risk Is the Real Challenge to Safe Withdrawal Rate
- Monte Carlo Simulations Cover More Market Possibilities
- Equity Risk Premium: Volatile Investments Should Bring Higher Returns
- Lower Equity Risk Premium Can Threaten Retirement Portfolio
- Monte Carlo Allows More Specific Asset Allocation Than Historical Data
- 80% Probability of Having Enough Money Might Be as Good as It Gets
Welcome to The Lange Money Hour: Where Smart Money Talks with expert advice from Jim Lange, Pittsburgh-based CPA, attorney, and retirement and estate planning expert. Jim is also the author of Retire Secure! Pay Taxes Later. To find out more about his book, his practice, Lange Financial Group, and how to secure Jim as a speaker for your next event, visit his website at paytaxeslater.com. Now get ready to talk smart money.
Nicole DeMartino: Hello and welcome to The Lange Money Hour. We are talking smart money tonight with retirement and estate planning expert Jim Lange, who’s also the author of two editions of Retire Secure! and The Roth Revolution. Tonight, he’s joined by Dr. Geoff Considine. Geoff, are you on the line?
Geoff Considine: I am.
Nicole DeMartino: Wonderful, welcome. Geoff joins us from Colorado tonight where he is the president and founder of Quantext and the author of The Survival Guide for a Post-Pension World. Geoff is an expert in asset management analytics and research, so he is the perfect guest to join us tonight as we talk about safe withdrawal rates when planning for your retirement.
Jim Lange: And I’d like to start with something that I’ve actually never done before, which is actually having a correction or addition from a prior show. The last show, we had a guy named Sandy Botkin on, and he did a very nice job talking about — he’s actually a former IRS agent and a CPA and an attorney, and he talked a lot about the different tax-saving tips and I thought he was a very good guest, and he’s also a big fan of people — he likes for people to start their own little side business and eventually even have their side business be their main business, and that’s fine. You know, the world of authors, which is, frankly, usually the type of people I get as guests because they’re experts and they have something to say, but some of them are a little bit outrageous, and Sandy said something that really was outrageous and I didn’t call him on it. By the way, it happens a lot when I think later on, “Oh gee, I should’ve said this, I should’ve said that,” but he said something that I really should not have let go, but I did. Again, he wants everybody to develop their own business, and he said something like, “Well, if you have your job, spend as little time as possible, just do whatever you can just to get by while you’re developing your side business, and just do just enough to not get fired,” and then I made a joke, “Well, that doesn’t apply to my employees.”
And that’s all well and good, but really, what I should’ve said is, “No, Sandy. There’s a lot of people … in fact, I would say the majority of the listeners who, they might have put in 20, 30 years, or they’re still working, and they take a lot of pride in what they do, and they do a good job and they do something useful for society,” which is, frankly, most of my friends, acquaintances, clients and the vast majority of people I run into, and there are people like me who are self-employed. Some people would say that we’re self-employed because we’re unemployable, but, in either case, I shouldn’t have let him get away with that, and I’m going to have a rare correction or an addition where I can really say, “Well, no, I disagree.” If you have a job and let’s even say that you drink Sandy’s Kool-Aid and you think, “Oh, someday I ought to go out on my own and figure out my own business.” Well, that’s fine, but in the meantime, while you have your job, do a good job, and then, at some point, if you go out on your own, give your employer sufficient notice and then go out on your own. If you’re going to stay with your employer, then you owe it to him, frankly yourself, and your own clients and people that you run into through your work to do the best job. So, anyway, I wanted to get that out of the way because that bothered me.
All right, anyway, back to Geoff. Geoff, are you still here?
Geoff Considine: I sure am.
Jim Lange: OK. Geoff, this show was advertised as a safe withdrawal show, and I know that you have other areas of expertise, and in fact, in your book, safe withdrawals were only one section. On the other hand, when you type in “safe withdrawal rates” in Google, you’re all over the place, and you have articles and you’ve obviously been writing about it, and I think that that is a component of your software, so could you start with let’s just say the basics on what do people mean, or what do advisors mean when they talk about the safe withdrawal rate and is that your definition, whatever you think the standard definition is, is that your definition also? So, what is the safe withdrawal rate?
Geoff Considine: OK, that’s a great place to start, and, by the way, thanks for having me on. The whole debate about safe withdrawal rates is really a consequence of the move from traditional pensions to defined contribution pensions, where you’re going to be living on what you’ve managed to save and invest over your lifetime, and where the challenge comes in is you’ve spent your whole life working and saving and investing and you come upon retirement and you have a portfolio of assets, and people need to try to figure out how much money they can safely plan on drawing each year to be able to sustain a long-term income in retirement. And so, that’s really the definition of the safe withdrawal rate is basically just how much money you can plan on drawing based upon the size of your portfolio for the balance of your life with an acceptable probability of running out of money.
Jim Lange: All right. Now, one question that I get about safe withdrawal rates, and whether we use 4 percent or 5 percent and we’ll get into that later, people say, “Well, does that mean that if I spend 4 percent,” and let’s just use a million dollars because it’s a nice round number. So, you have a million-dollar portfolio and somebody says, “Well, does that mean that if I take out $40,000 per year, that I’m going to die with a million dollars, or does that mean that I’m going to be able to spend $40,000 a year — and I should include inflation in that — and then when I die, there’s nothing left?”
Geoff Considine: OK. Good question and your later clarification was crucial. Where the 4 percent rule comes from, which is what you happened to refer to as, based on the idea that if I retire with a million dollars, the 4 percent rule says, well, I can draw $40,000 my first year in retirement, and then escalate that amount by 3 percent, to keep up with inflation, for the rest of my life, and I will have a high probability of being able to sustain that income for the balance of my life. But no, you should not plan on retiring with a million. It requires that you have the possibility of spending the million. Not that you will, or not that you will on average, but you have a good chance of spending down the entire balance.
Jim Lange: All right, so the safe withdrawal rate is not really a rate designed to pass money onto your heirs. It’s really just to make sure that you will have sufficient money to live during your lifetime. Is that correct?
Geoff Considine: Well, let me clarify though because this is a really important point: On average, if you follow the 4 percent rule, if you draw that amount, you will have a fairly substantial estate at your death. The 4 percent rule though is based on the worst-case scenario or the worst cases. So, the idea is that, on average, you have money and a pretty substantial estate left, but you need to plan for the bad scenarios. And so, there is a meaningful probability that you will draw down your entire portfolio, but no, you should expect to leave a substantial bequest, and substantial is as a fraction of what you were trying to live.
Jim Lange: OK, now let’s say, for discussion’s sake, that we had somebody that retired in 2008 with his million dollars, and then, all of a sudden, boom! He loses a substantial amount in the market, and he’s probably, if he’s going to, let’s say, stay with that 4 percent rate, he’s probably not going to leave a substantial amount of money. In fact, does he even have a problem doing the 4 percent?
Geoff Considine: OK, very good question. So, you have someone who retires before the crash and let’s say they retire with a million dollars, they’re planning on pulling that $40,000 a year, inflation-adjusted, for the rest of their lives. After 2008, if they just continue to draw that amount, they have a very high probability of failure, of not being able to fund their long-term retirement.
Jim Lange: All right, but the 4 percent withdrawal rate does anticipate the possibility that we’re going to have another 2008, we’re going to have another, in effect, crash, and that that presumably is built into those numbers because, on average, the investments have certainly done better than 4 percent over time, and, in addition, if that was true, if people got the average rate, if you will, and it was more than 4 percent and they just drew their 4 percent, then they would end up dying with their million dollars and more. But what you’re saying is, the safe withdrawal rate is 4 percent because you have to take into account the fact that you’re going to have at least the possibility of those down years.
Geoff Considine: Right, and that’s a really important point. There’s an awful lot of calculators floating around, including on the web, that ignores investment risk. So, they treat your portfolio as though if you think your portfolio’s going to make 7 percent a year, make sure your portfolio will earn 7 percent every year. And so, of course, you can draw more than 4 percent in that situation. The problem is that returns for any portfolio that’s a mix of fixed income and equities are somewhat volatile, and so there will be situations where you will be drawing a higher fraction of your portfolio relative to its current value. So, your $40,000 is 4 percent of what you retired with, but if your portfolio’s down 20 percent and you draw $40,000, you’re obviously drawing a proportionately higher fraction of your portfolio, which is then not there to enjoy the recovery. And so, no, it is the volatility of investments that really drives the 4 percent rule. If you ignore volatility, life is much easier, but the fact is you simply can’t get equity-like returns without that volatility.
Jim Lange: OK, and by the way, I do want to get to your software solution, which I think is both unique and the next step, but before we get to that, if we could do a real quick history of the analysis, because even without your software, maybe you can’t say that, maybe because it’s just such an integral part of the way you think and who you are, but if we could do a quick history of that analysis, and to see whether you agreed with that 4 percent rule, let’s say before you add your analysis. And I know that your analysis, it’s not just changing the 4 percent number. It’s actually something done proactively regarding investments. But if we could just do a real quick history because the other thing is, as I mentioned to you earlier, that Bill Bengen, who I think was one of the pioneers in this area, and I think he wrote very articulately, and he was actually on the show, and I figured he was kind of like, well, he’s kind of like the classic safe withdrawal guy, and I kind of consider you the more modern safe withdrawal guy. I don’t know if that’s fair or not. But if we could do a real quick history and then get to where you’ve taken it.
Geoff Considine: OK. So, right, Bill Bengen was really the pioneer in this area, and I think he did some of the, if not the first, he’s certainly known as being the first person to really take the volatility of the market into account in terms of calculating safe withdrawal rates, and basically his work, and there’s also a study called the Trinity Study that used historical market data to go through and say you essentially take real sequences in market returns and say if I retired in this year and started to draw a certain amount, how much could I safely draw, and looked at every year in history for which we have market data and then looked at how successful you could be with the given draw rate, and basically, what the early studies showed was that the 4 percent draw rate was sufficiently low and you would never run out of money through all the market histories for which we had data where there was just an exceedingly low probability that we would run out of money.
Jim Lange: OK, I don’t mean to correct you, but this is something that I always kind of wonder about. A lot of the people that I work with are conservative by nature, and things like “exceedingly low” might not quite do it for them. Are you talking about 70 percent, 90 percent, 99 percent?
Geoff Considine: Right, OK.
Jim Lange: And I hate to be this exact, but frankly, these are some issues that people are concerned about because sometimes, when I’ve even read some of the material, even some of your material, it says, “Well, if you take out this much, you have a 70 percent chance,” and then I’m thinking, “Oh, that means you have a 30 percent chance of running out of money,” which is obviously what we’re trying to avoid. So, if you could be a little bit more specific about that, I’d appreciate it.
Geoff Considine: Let me be very specific.
Jim Lange: All right, good, I like that. By the way, I love this because, you know, it’s the difference between getting a Ph.D. who’s studied this for years and years and knows what they’re doing rather than getting some joker who is just kind of making it up as he goes, or he read something and he’s trying to spit it back out, but I love when you say, “Yes, I’m going to be very specific.”
Geoff Considine: OK. Now, again, you may have to have a correction on this because I don’t remember exactly. My recollection is that in Bengen’s original study, he found that a 4 percent withdrawal rate was absolutely safe for the historical period that he looked at, like, you would never go broke with the 4 percent rule over that period.
Jim Lange: OK.
Geoff Considine: Now, later work that attempted to incorporate more uncertainty, which is to say to account for the fact that given a certain sample of history, that’s not representative of everything that could possibly happen. That’s simply one snapshot of history. And so, later work that attempted to put more statistical analysis around the historical values, in other words, more uncertainty around it, came up with results that were more like an 80 percent probability of being able to fund a 30- to 40-year retirement, and the numbers do vary when you go from a single period in history, which we have absolute data for, but history never repeats itself. So, the challenge in going beyond that is to then say, “OK, what can we say?” So, for instance, saying that something that’s never happened before in a 50- or 60-year market history doesn’t mean it’ll never happen. It just means it didn’t happen in that period.
So, if people attempted to expand the probability to cover the range of things that appeared to be possible based on historical statistics, the probability of failure naturally rose. And so, it is more common today to see probabilities of a failure somewhere in the 80 percent to 90 percent range simply because we recognize that one snapshot in history is not sufficient to give the range of all possible things that could happen. And of course, the extreme case is what we refer to as “black swans,” you know, the fact that you’ve never seen a black swan doesn’t mean one doesn’t exist. But even without going to those really extreme events, simply looking at a given period in history doesn’t give you the range of all things possible. It simply gives you one snapshot of what is possible.
Jim Lange: So, for example, if you used a 30-year period, and I don’t know if Bill did that or not, but if you didn’t include the Depression, or, for example, most of his work was before 2008, and you didn’t include that downturn, then you would obviously have a higher percentage of success, even if it’s 100 percent, compared to taking into the possibility that well, something that didn’t happen during that period could happen and, therefore, it’s not as high.
Geoff Considine: Right, and what’s perhaps a little more worrisome is the fact that the market evolves. The market today is not the same market that it was. And so, there are people out there who believe, for instance, that even the way markets have evolved, especially with high-frequency traders and the increased influence of those kinds of players in the market, is that extreme events have actually become more probable because there are more giant leverage players out there. And so, right, I think the really big-picture view from my perspective is that looking at history is a great idea. I mean, it’s what we have. However, you should always assume that history is one snapshot of the possible, and in terms of building statistical models, you have to try to use history to give you a sense of going beyond simply what has happened to what might happen, and that actually leads very directly from the pure historical studies to more of the Monte Carlo studies, which is what I developed in my software and what a number of other companies have developed as well.
Jim Lange: All right, why don’t we get to …? Oh, you know something?
Nicole DeMartino: You know, I think this is a good point to take a break, and then when we come back, Geoff can talk about that. We are going to take a break. You’re listening to The Lange Money Hour. We are live. If you have any questions, (412) 333-9385. We’ll be right back.
Jim Lange: I do want to get to your Monte Carlo analysis, Geoff, in a minute, but there’s something that I think it would be premature to just say the classic solution is 4 percent, and one of the reasons why I don’t think that that’s even the classic answer is because we haven’t distinguished between how many years you need the money. So, let’s just take two people. One is maybe 60 years old and they have a million dollars and they’re in very good health and they might live 30 years or even longer, and compare that with somebody who is perhaps 90 or 95 years old and is not in good health. Obviously, just intuitively, the 95-year-old can take a much higher withdrawal rate than 4 percent and never run out of money, whereas the healthy 60-year old has to be a little bit more conservative because he’s going to live longer. If you can tell me some thoughts that you had, and then maybe we will also give the listeners some of the classic analysis that Bill Bengen did on that, and then we’ll get to your Monte Carlo, if that’s OK?
Geoff Considine: Sure, absolutely. Well, of course, you’re correct that the 4 percent rule is based on the idea of someone retiring today and how much they can draw as a fraction of their portfolio. The older you are, if you were to, say, be 70 and reset and say, “OK, I’m going to reevaluate my draw rate,” of course, you’ll be able to draw a higher fraction because you’re looking to sustain income for a smaller number of years. The real challenge to the survival rate is all about longevity risk, and obviously, the older you are, the less longevity risk you face. And in fact, one of the more important evolutions of what has become known as the 4 percent rule is the idea that you should do exactly that. So, you start out at, say, age 65 and you say, “I’m retiring and I’ve got a million dollars and so I’m going to draw $40,000 a year.” But the idea is to come and reevaluate and do that same kind of analysis as you get older. And so, basically, the idea is to take the amount that you have, say, three years later and look at your age and reevaluate what a new safe withdrawal rate is given your age, and you can do that using either historical data or software tools.
Jim Lange: Which we’ll get to in a minute. Now, the other thing that I would like to stress, though, is I don’t want to just base it on age. I actually want to base it on life expectancy, and I sometimes joke with people and say, “How long are you going to live?” And then they make a joke back, but then we actually get into some serious discussions of, “Well, my dad was 87 when he died,” or maybe “He was 60, but he smoked, so we don’t really know because I don’t smoke,” or “Well, I had this cancer,” or whatever it is, in that I don’t want to just strictly go with what somebody’s age is, I’d rather, and for a lack of better information, I just ask the client what they think their best guess is and I try to be conservative. So, let’s say, somebody is 60 and they say, “Well, maybe I’ll make it to 85,” rather than looking at the 25 years, I might want to look at 30 or 35 just on the chance that they will survive longer than they might think.
Geoff Considine: Absolutely. Now, longevity rate, longevity varies dramatically based upon your family history, how healthy you are, behavioral factors, and, of course, another important consideration is your bequest motive. If you really want to leave a substantial estate to your heirs, then your decisions will also be quite different than if you have less of a bequest motive.
Jim Lange: And the other factor is that, usually, assuming that we’re talking about a married couple, to me, I always must consider the longer of the two lives. So, let’s say, for discussion’s sake, I think it’s starting to change, but let’s say traditionally, the husband is either the same age or older and has a shorter life expectancy, then we might gear it towards the woman’s life expectancy because we have to provide for both spouses.
Geoff Considine: Certainly.
Jim Lange: All right. So, what I thought I would do before we get into, let’s say, your analysis with the Monte Carlo and what you’re bringing up to it, I thought I would just tell that to people because Bill Bengen actually did come up with safe withdrawal rates for different time horizons, and what I’m going to do is I’m actually going to take a minute to go over those, and the analysis that Bill had was actually before the downturn in 2008 and 2009, and I said, “Would you say that that still applies today?” and he hedged a little bit and he said, “Well, you know, I’m not sure that we can expect quite the returns that we did in the past, but at least nobody has redone them,” and I think that his implication was well, if they go down, they don’t go down by much.
But anyway, here they are because I think that this is relevant for our listeners. And again, this isn’t fixed in stone, and obviously, a lot of people, including, by the way, you, might very strongly disagree, and I’m also not going to be further talking about something that’s really important, which is to talk about the asset allocation, which I know is critical and it’s critical in your analysis, so I’m going to skip that part too. So, I’m really skipping something that’s very important. But I think rather than skipping it, I will just say what Bengen’s analysis was, which was with a 10-year life expectancy, he calculated a safe withdrawal rate of 8.9 percent. With a 15-year life expectancy, he calculated a safe withdrawal rate of 6.3 percent. With a 20-year life expectancy, he calculated 5.2 percent, with a 25-year life expectancy, 4.7 percent, with a 30-year life expectancy, 4.4 percent, with a 35-year life expectancy, 4.3 percent, a 40-year life expectancy of 4.2 percent and a 45-year life expectancy of 4.1 percent. So, he was even a tiny bit higher than 4 percent. But anyway, and again, you might have some disagreements with those numbers — I expect you would — but I just wanted to get the, let’s say, some of the classic analysis down.
Geoff Considine: Sure.
Jim Lange: Well, let me ask you this. Before we get into the issue of different ages, could you say, if you can, in layman’s terms, what you did to analyze it, how you think that what you’re doing is the next step, and then also perhaps tie that into your software? Because I know we have a lot of professional financial advisors and we have a lot of quantitative types that like to do some of this stuff themselves, and your software might be a great tool for both of those sets of people. So, can we start with maybe … maybe even just starting with what Monte Carlo is and then what you did with it?
Geoff Considine: Sure, OK. So, Bengen’s study and other historical studies take history and look at history and say, “OK, starting at various points in history, how would things have turned out?” And by the way, one thing that’s important that I don’t remember off the top of my head is in Bengen’s study, is he looking at a 60/40 portfolio, 60 percent equities, 40 percent bonds?
Jim Lange: Well, what he’s doing is, he’s actually changing the allocation as you age. So, I didn’t go through this, but for example, a 15-year portfolio, he had a 30 percent equity allocation, but for a 45-year life expectancy, he had a 65 percent allocation. So, he’s basically increasing the percentage of fixed income as somebody ages.
Geoff Considine: Got it, OK. So, in terms of looking at periods of history, you have two limitations. One is that what happened is simply one snapshot of what’s possible, and the other is we don’t have a really long time series of the diverse asset classes. In other words, there are asset classes for which simply weren’t traded and more for which we don’t believe we have very reliable index data going back. And so, the purpose of Monte Carlo simulation, as opposed to history, is to try to combine what we can get from historical data. We had statistical models to give a broader sense of what’s possible rather than simply what happened in one trip through history. So, the idea simply is to cover the broader range of what’s possible than you can with single market history.
The other thing that Monte Carlo usually incorporates is some way to adjust baseline estimates of the returns that we can expect going forward, and that’s one of the biggest criticisms of using pure historical data to look at survival rates is that we have gone through a period where which most researchers believe, particularly in the U.S., has delivered higher returns for equities than we should expect going forward, and there are a variety of reasons that the research shows that. One is compared to other economies, we seem to have gotten an unfairly high, or a fortunately high, equity risk premium over the last 50 years or so, which is to say we just got more return from equity than we should have expected, and then on the basis of fundamentals, there are fundamental models that predict the kinds of returns we should expect from equities versus less risky assets, and on that basis, we also expect that we’re going to get lower returns going forward, which is probably what Mr. Bengen was referring to in terms of the way we might revise returns downwards.
Jim Lange: And I hate to interrupt, but if you can just go back for one minute because I want to make sure that everybody’s with us. You used a term that I think a lot of financial advisors are familiar with, which is equity premium, but perhaps you could explain that to our listeners.
Geoff Considine: OK, thanks for calling me out on that. There is an idea that equities should return more to investors because they’re riskier, the idea being that risk and return go hand in hand, and so the investor should rationally expect to get higher long-term returns for taking on the risk of equities. And that is referred to as the equity risk premium, and it’s usually measured relative to a risk-free asset or some very, essentially a risk-free asset or very low-risk asset like T-bills.
Jim Lange: Which used to be risk-free.
Geoff Considine: Right! So, the idea of the equity risk premium is that additional return you get from risky assets like equities that rewards you taking on that risk. And again, in those terms, the feeling towards the results from a lot of research out there is that the equity risk premium will be lower going forward than we’ve seen in the market as a whole over the last 50 to 60 years.
Jim Lange: Do you have numbers for either historically or what you think is going to be the equity premium?
Geoff Considine: Now, that’s a very interesting question. Actually, just today, I was reviewing a new piece of research that comes out every year from Credit Suisse, and basically, there are these three academics named Elroy Dimson, Paul Marsh and Mike Staunton who go through and look at the global equity risk premiums and then estimate what they think we can expect going forward. They’ve actually revised their estimates down somewhat this year from last year, and they’re normally pretty conservative. Basically, as a rule of thumb, I think we should probably expect, in terms of average annual returns for equities, nominal, in other words, they are all in of, say, 8 to 8½ percent a year at the expected return. Realistically, there are probably some reasons why that might go a bit lower, but that is an arithmetic average annual return. The compound annual return will be lower than that and that’s because of volatility. But basically, for instance, in terms of my analysis, I assume a baseline of about 8 percent.
Jim Lange: And I know all the engineers are going, “Eight percent!? Are you kidding? Where can you get 8 percent?”
Geoff Considine: And again, that’s nominal, not real. But in terms of the after inflation, which is the real return, a 5 percent for equities, given their volatility and the history is pretty much where I see the research coming out, although it’s kind of hard to believe looking how we’ve been doing in the markets lately over the last five years, and it certainly could be lower, and I wrote an article years ago called “The 800-Pound Gorilla of Retirement Planning,” and there is no question that what you assume about the equity risk premium, the baseline return from equities has enormous impact on what comes out of these calculations. If you use historical data, things will look quite rosy. If you lower the equity risk premium, things can look a lot worse fast.
Jim Lange: OK, all right. Again, I didn’t mean to interrupt you.
Geoff Considine: No, no, no, it’s actually a really important question. It was definitely on the list of things that I wanted to make sure we got into the discussion as well.
Nicole DeMartino: Jim, before you move on, I think this is a good place for us to take another break. You’re listening to The Lange Money Hour, Where Smart Money Talks.
Jim Lange: So, we were talking about Monte Carlo simulations, and why don’t you finish that discussion, if you would, Geoff, and then I also want to get into some of the things that you wrote about in terms of how people can increase their safe withdrawal rate, but if you could talk about the Monte Carlo simulations and how your software ties in and what your software adds to the mix? I think our listeners would be most interested in.
Geoff Considine: OK, thanks. So, the key with Monte Carlo is that, as I mentioned, first, you can extend the range of possible outcomes, which is really important to protect against the really extreme downside events. You can adjust the equity risk premium, and again, the current equity risk premium, for instance, that we use in the software at the baseline is lower than the historical equity risk premium, which, again, most research suggests is both correct and it also tends to lead to more conservative plans. And finally, you can do asset allocation that is much more specific than you can do using the historical data because, as I mentioned, the asset classes that are available today in very low-cost index funds simply weren’t available to investors over the very long sample period, and even if you have proxy data in the form of indexes that you could use to represent those asset classes, they’re simply less meaningful because those were not actually traded that way back in those earlier decades. So, being able to experiment with much more sophisticated asset allocations is a really powerful tool.
Jim Lange: So, I guess in one way, you have to be more conservative taking into account other possibilities, but on the other hand, and I think one of the points of your research is if you are better diversified, that the additional safety from diversification will allow you to have a higher safe withdrawal rate. Is that fair?
Geoff Considine: That is a fair statement.
Jim Lange: All right. What does your software add to the analysis, and how might you, let’s say, disagree, and, you know, I kind of ran off some numbers that, in effect, Bill Bengen did. Do you have conclusions, or is it really too much of a case by case basis, and that’s one of the points of using your software, and then also if you can tell people where to get your software?
Geoff Considine: OK. Well, in general, what I’ve found, and actually is quite surprising, is the withdrawal rates on the order of 4 percent to 5 percent actually do seem to come out fairly consistently from the Monte Carlo tool consistent with the historical analysis, and the reasons are that, on the one hand, we do have lower expected returns than we’ve had over long periods of history, but the greater diversification effects that we can test for and build in because of the additional asset classes that are available allow you to boost your returns relative to the risk levels you’re taking on, and so those two tend to be sort of a natural offset. And so, actually, as a rule of thumb, a little over a 4 percent safe withdrawal rate as a rule of thumb is actually remarkably good.
Jim Lange: All right, now I was going to ask for how many years are we talking about if your baseline is 4 percent?
Geoff Considine: OK. A baseline of, say, 4 percent for a high probability of being able to fund a 30-year retirement, now that doesn’t mean you’re guaranteed to not run out of money. In fact, the probability, that’s for an 80 percent probability of not running out of money over a 30-year retirement. So, you still have a 1 in 5 chance of running out of money, which doesn’t sound terribly attractive. On the other hand, and this was an important point that was raised years ago by William Bernstein, who, I imagine, many of your listeners are familiar with. Bill Bernstein did some of the early Monte Carlo analysis to look at retirement planning, and he makes the case that essentially, we really can’t do much better than, say, an 80 percent confidence level, and to believe that we can have like a 100 percent confidence level of being able to fund our retirement is just unrealistic because even in the best situation, we simply can’t understand the range of possible future outcomes that well. So, his point is to plan for something like an 80 percent probability simply because we’d love to plan for a higher one, but there is simply always that risk of extreme events out there that you can’t plan for.
Jim Lange: All right, and let’s assume, for discussion’s sake, that we have a lot of conservative listeners out there who are fiscally conservative and say, “You know something? Eighty percent doesn’t sound bad, but that means there’s 20 percent of the time, I’m not going to make it.” Now, does that mean that they’re going to be starving and destitute and in the street? And could you talk about the concept of changing expectations after an event? So, for example, I have a lot of clients who were planning on retiring earlier, and then after the market downturn, they said, “Well, I’m not going to retire.” So, they actually changed their behavior rather than increase the risk of running out of money, and I guess the corresponding thing for somebody who is retired is that they could reconsider how much money they could spend. So, could you talk about them, let’s say, not necessarily static model of 4 percent or 5 percent, but what people actually do? And by the way, we’re starting to run out of time, and I know that I promised you that you could talk a little bit about your software. You’ve been really great doing pure information, but please do a quick description of your software and give people contact information for getting it.
Geoff Considine: OK, thanks. Well, I’ll address the substantive issue first. One of the things that I found in my research — and a number of other people have as well — is that the most powerful way to lead towards a more successfully funded retirement is to have flexibility in your plans. Rules like the 4 percent rule really are contingent upon the idea that you will draw a constant income regardless of what happens, and in real life, we certainly hope that people don’t do that, and in the book that I wrote called The Survival Guide for a Post-Pension World, I went through a series of sensitivity studies looking how changes in behavior, such as delaying retirement or changing your income or saving more, can really have a major impact on the probabilities of successfully funding retirement. And so, no, that will certainly improve things, and, in fact, that’s the most powerful tool that most people have at their disposal is changes in behavior, both before and in retirement. The staying power of the 4 percent rule is simply that it is a simple guideline and rule of thumb. Hopefully, people do more detailed and specific analysis, both before retirement and during retirement, and that’s a lot of what the tools I developed are for.
Jim Lange: All right, and why don’t you tell people, because we’re really going to run out of time soon, why don’t you just say, “OK, I’m going to quit giving people such excellent substance and I’m just going to talk a little bit about my software,” because I think that, frankly, it might be very interesting, particularly for some of the financial professionals and for some of the quantitative-type engineers and physicists and other quantitative types, and I know that we have a lot of them in our audience.
Geoff Considine: OK. All right, well, thank you. It’s an ample opportunity to give my plug.
Jim Lange: That’s it!
Geoff Considine: Quantext Portfolio Planner is the software that I’ve developed. You can learn about it at www.quantext.com. You can apply for and download a free trial and try out all the bells and whistles, and it helps you to build a portfolio out of real funds, ETFs and individual stocks, and it will do Monte Carlo simulations on your real portfolio, and then project risk and retirement survival rates given whether you’re pre- or post-retirement and given your savings rates and what your expected draw rates are in retirement.
Jim Lange: Again, can you give that contact information one more time?
Geoff Considine: Sure. It’s www.quantext.com.
Nicole DeMartino: Wonderful. Geoff, thank you so much for joining us. This was Dr. Geoff Considine. Again, his website: www.quantext.com.
Nicole DeMartino: We had a great show tonight. You can always reach us at the office, (412) 521-2732 and www.paytaxeslater.com.
Jim Lange: And I actually have one other quick note that if people are interested in the safe withdrawal rate and they wanted to hear what Bill Bengen said, that is actually in our archives. If you go to www.paytaxeslater.com and click on “Listen Now,” you can listen to, let’s call it, the classic safe withdrawal guy, which is Bill Bengen, and it’s basically an hour long show.
Nicole DeMartino: Yeah, absolutely. All of our shows are posted on www.paytaxeslater.com, all of our archives, and we also have the transcripts on there too. So, if you like to read better than listen, feel free to download those whenever you’d like. Again, thank you very much for listening to The Lange Money Hour. Have a great evening.