David Blanchett, PhD, CFA, CFP®, is Managing Director and Head of Retirement Research for PGIM DC Solutions. PGIM is the global investment management business of Prudential Financial, Inc. He is also currently an Adjunct Professor of Wealth Management at The American College of Financial Services and Research Fellow for the Alliance for Lifetime Income. David has published over 100 papers in a variety of industry and academic journals. When David isn’t working, he’s probably out for a jog, playing with his four kids, or rooting for the Kentucky Wildcats.
There are many different objective functions you can use when building optimal portfolios. The majority of these approaches define risk from the perspective of variability or bad outcomes, but positive returns could be viewed as “risky” for those that don’t experience them, which is another way of saying that people experience regret (or FOMO, for our trendier listeners). Today, we are joined by David Blanchett, a return guest and the Managing Director and Head of Retirement Research for PGIM DC Solutions, the global investment management arm of Prudential Financial. He is also an Adjunct Professor of Wealth Management at The American College of Financial Services and a Research Fellow for the Alliance for Lifetime Income. David returns to the podcast for an articulate discussion about regret in portfolio construction, what drives it, and how financial advisors can cater to it. We then delve into how David is redefining optimal retirement income strategies, looking at retirement tools, retirement planning, compensation models in the industry, risk exposures, and portfolios. We also get a high-level overview of some of the fascinating work that David has done on home-country bias, plus so much more. For highly technical content presented in an accessible and practical way by one of the brightest minds in retirement planning, be sure to tune in today!
Key Points From This Episode:
Differences between risk aversion and regret aversion. (0:03:57)
The distinctly human element that drives “investment FOMO.” (0:06:34)
Insight into how David models regret in his research. (0:09:06)
The asset pricing implications of approaching portfolio optimization this way. (0:12:11)
Tips for deciding on what the regret benchmark should be. (0:13:19)
How a portfolio optimization routine based on regret affects asset allocation. (0:14:08)
Ways that the effect of optimizing over regret changes depending on risk aversion. (0:16:55)
Other asset characteristics that might drive optimal allocation to regret assets. (0:18:04)
Why moving away from self-direction is the best thing to happen to 401(k) plans. (0:20:53)
How financial advisors should cater to investors interested in speculative assets. (0:24:00)
Unpacking some of the social and story-driven sources of regret. (0:29:03)
Downsides to modelling retirement liability as a static inflation-adjusted amount. (0:32:00)
Why it’s important to understand the composition of retiree spending and saving. (0:33:57)
David’s research into dynamic spending rules for retirement planning. (0:42:06)
Some of the key pitfalls of existing financial planning tools and solutions. (0:44:38)
Ways that safe withdrawal rates change when you incorporate dynamic spending. (0:51:10)
How advisor channel affects passive fund choice and how clients should respond. (0:57:56)
Insight into David’s research on foreign revenue and home-country bias. (1:02:27)
Read The Transcript:
Ben Felix: This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from two Canadians. We are hosted by me, Benjamin Felix, and Cameron Passmore, Portfolio Managers at PWL Capital.
Cameron Passmore: Welcome to Episode 254, and we have a returning guest this week. David Blanchett joining us, Ben, and what a conversation. It was varied. You pored over, what? At least four big topics in preparation for this. The big part of the conversation was on regret in portfolio construction, which is super fascinating. Then, we went on to retirement tools, retirement planning, compensation models in the industry, risk exposures, and portfolios, and the fascinating work he's done on home country bias. What a round trip.
Ben Felix: Yes. We covered a lot of ground. I basically just went and read all of the research that he's published since the last time he was on and he's done a lot. The first two big topics on regret and portfolio construction, which is fascinating, he basically built a portfolio optimization model that includes a term for regret. So, given that somebody is concerned about regretting missing out, FOMO, basically. It's basically a FOMO portfolio model, which is kind of funny to think about.
But as a thought experiment, it's fascinating. Even, it doesn't necessarily inform, like it's not a normative model. It's not going to tell you, you should invest in this regret asset optimally. But it's kind of descriptive of how would we explain why people want to invest in regret assets? And if they wanted to do that, what's the optimal way to approach it? So, that's, I think, kind of how I would explain his model there. But that part of the discussion was fascinating. But his stuff on optimal retirement income is also incredible. So, we spent a lot of time there as well.
The last few topics were shorter, because it was just kind of quick questions on a couple of papers, but fascinating empirical findings on foreign revenues and how they explain foreign revenues as opposed to domicile and how that explains returns. And then how advisor channel influences the advice that they give to their clients. That's a lot of ground to cover in approximately an hour of conversation. But David was on it.
Cameron Passmore: He was on it. He showed up. He brought his game. So, David is currently Head of Retirement Research for PGIM, which is formerly Prudential Investment Management, which is the asset management arm of Prudential Financial. He's in the DC Solutions Group, where he develops research and solutions to help improve retirement outcomes. When he was with us last time on Episode 137, couple of years ago, he was the Head of Retirement Research for Morningstar. He is currently an Adjunct Professor of Wealth Management at the American College of Financial Services and was formerly a member of the executive committee for the Defined Contribution Institutional Investment Association and the Employee Retirement Income Security Act Advisory Council. Published over 100 papers and all sorts of incredible journals. He has a BS in Finance and Economics from the University of Kansas and an MS in Financial Services from the American College of Financial Services, an MBA from the University of Chicago Booth School, and a Ph.D. in Personal Financial Planning from Texas Tech University.
Ben Felix: Incredible background.
Cameron Passmore: Incredible background, incredible energy, very articulate, fantastic episode. Anything else to add, Ben?
Ben Felix: Nope. It's a nice, wide-ranging discussion with technical content but I think also very accessible and practical content, which is that's something that David came back to a few times in this conversation, like, how do you make this type of modelling more practical for how people actually are and what's actually useful to people? So yeah, great conversation. Let's go ahead to the episode.
Cameron Passmore: All right. Here's our conversation with PGIM’s David Blanchett.
***
David Blanchett, welcome back to the Rational Reminder Podcast.
Great to be back.
All right, I want to start with your new paper on regret, which is just a fascinating way to think about portfolio optimization. Can you talk about the difference between risk aversion and regret aversion?
So, risk in a traditional portfolio optimization routine, just standard deviation or downside risk. It's volatility or losing money. I think we can all kind of agree that that's pretty uniform. People don't like losing money. Now, people have different perspectives on what losing money would do to them. You might be really conservative and I might be really aggressive. I'm okay with having a more aggressive portfolio.
What that totally ignores though is how you might feel about certain assets doing really well. Risk is focused on losing money. Regret (or FOMO would be a fun word to use) is focused on the notion that how you experience an outcome could really affect you. Maybe you didn't lose money, but maybe not making money really negatively affects you and it creates all this emotional pain. It's obviously a different type of pain than losing money. But the thing about risk as a continuum, maybe I would have been willing to have a little bit more risk in my portfolio if it would reduce regret at some point down the line. So, there are behavioural things here too, like we've seen these investors abandon diversified portfolios during speculative bubbles because they're missing out on this next wave. Could allocating into assets, even in small portions, actually increase their wealth because it keeps them diversified over longer time periods because you're less prone to investing speculatively?
That's crazy man. It's kind of like the Robert Merton intertemporal asset pricing where people care about standard deviation, but they also care about covariance with other stuff. You're saying they care about standard deviation, but they also care about regret minimization.
Well, so what's interesting is that I think people internalize. Risk is, I think, pretty standard. I think that most or all investors experience risk. Okay? I think regret is very different, and that a lot of folks won't experience regret. I don't experience regret almost at all, ever. I just don't care. I make good choices then I move on. Even if you're going to experience regret, it'll be for different assets to different degrees. Right? What really got me thinking about this is cryptocurrencies. From my perspective, there are different beliefs out there. It doesn't make sense as an investment. But could it actually make sense to still own it? I'm like, “How could you define the decision to own this asset as being rational?” Well, you could if not owning it would cause you a lot of emotional distress, similar to risk.
So, I think, the key difference between risk and regret, is that risk is pretty consistent across all investors. Regret is very investor specific, in terms of like, what they have regret for, how much it bothers them, just everything else.
What is driving that regret in investing?
This is going to shock your listeners, but people aren't utility-maximizing robots across all time periods at all times. We’re people, right? I mean, we go back to the tulip mania, you look at real estate bubbles, you look at – people are prone to greed, right? When things start doing well, I think investors respond differently to having missed out. Could this have changed my life? Oh, my gosh, I could have bought Bitcoin at a dollar, and now, it's worth, I don't know, 25,000, whatever it is.
I think that the emotional response that's triggered when we see other things do well that we don't know, it's very personal, very emotional. But I even make the point in the research that I would say even institutional asset managers, to some extent, could suffer from regret. Right? You could see this, for example, in the performance of the US stock market, if you’re a hunter. You might hate large-cap stocks as a tactical asset manager. Okay. But if you don't own them, and they do really well, that can be really bad for you from a benchmarking perspective.
Even if it's little bit less efficient, based upon your expectations, it could actually make sense to still own it, to the extent it allows your clients to realize the value of your process, do a full cycle, right? So, to me, the key here is not just saying that “okay, you could have less wealth.” You have to acknowledge that individuals bail out over certain time periods, and that's where they really get burned. So, trying to do things to keep them engaged over a longer timeframe, acknowledging regret, and acknowledging FOMO, could actually help them create more wealth over the long term.
Interesting. So, is that kind of the main idea with the research is to suggest how much of a regret asset you should have in a portfolio to avoid bad behaviour? Is that the general idea?
Yes. I mean, so like, I have this super formal objective function where you can actually do optimization routines, and there's been some other research out there on regret previously. I would say, two issues of the existing approaches is that usually you only focus on one asset. You could include one regret benchmark in your analysis in that. You could care about 80 different things. But I think that's what's even more important is assumptions around normality, right?
Previously, researchers, for example, adjusted a covariance matrix. That's cool. But, what if you want to be like lotteries? Are things that are really not normal payoffs, you can't really include those if you use traditional covariance. The actual approach that I came up with, it allows you to kind of do anything you want. It's effectively – you can do a scenario, you can use historical returns, but it would allow someone who really actually wants to model this to figure out, well, how much should I allocate to an asset, given return expectations, whatever else, along with the rest of my portfolio, given kind of coefficients and aversion factors for different things?
How have you modelled regret in your research?
So, more formally, so think about the return distribution. Risk, as we think about it traditionally would just be like the left part of the distribution. It’s the portfolio going down. That’s the deviation. You can just click a… return, and that's your risk target. Okay? Regret, though, there are actually lots of ways you could do it. But I think, how I did it in the piece and the optimization so far is you have some combination of individual risk assets. So, you can just call it a volatile asset, and an efficient asset, cryptocurrencies, and you compare the performance of your portfolio to that asset. Okay? You can do it at certain thresholds, like only if the performance asset exceeds 50%. There are lots of ways you can do it but the key is looking at your return distribution, and how it does versus something else.
So, think about the way this works then is, even if I'm like somewhat risk averse, but I just have a massive amount of regret, just absolutely a ton of regret, you could see moving the entire portfolio, or most of the portfolio into the asset that I would feel regret about.
Now, that would result in an inefficient portfolio. But the key is, as you acknowledged, hey, there are other things that drive this definition of efficiency, it moves the weights towards those assets. There are some really interesting kind of ideas here. One is that, as you increase the volatility of an asset, you actually increase its weight on average when you incorporate regret, right? That is the exact opposite of traditional mean-variance optimization. Because if you make something riskier, it makes it less attractive. Well, if it becomes riskier, you can still lose everything, but you can get 3 or 5 or 10X if it does well.
The assumption is you use your model – I think what it does is it gives individuals a reason to think about owning things that you wouldn't ever say you should do if you use traditional portfolio routines, just because people are humans, and I think advisors have to manage it. I'm sure that you will have to manage this with your clients. You have to have these conversations with clients that want to own, again, be it Bitcoin or other things. How do you all deal with those conversations when you have clients that really want to own something that you don't think is efficient, but they're going to do it no matter what?
Yes, well, we do it through a conversation. We've never had a utility function. We've never had a way to model it. But basically, what you've done, I think, conversationally, where you tell them, ask the client, think about in the outcome or the good outcome you're imagining, how great are you going to feel if it goes 1,000x or whatever? But on the other hand, if it goes to zero, how are you going to feel? And then make a decision based on the range of emotional outcomes. But I think you've kind of taken that and quantified it, which is pretty cool.
Yes, I don't know that too many folks are actually going to perform the portfolio optimization routine that I outlined in the paper. But I think to me, what I was just trying to figure out is, how do you rationalize owning speculative volatile assets? Well, this does that. This suggests that, if you're someone that really cares about what something would do, I don't know, NFTs or just whatever, carve out a small part of the portfolio and do that to satiate you from cashing out everything, and going all in into that if you miss out too much.
What are the asset pricing implications if people do think about portfolio optimization this way?
I don't know. I mean, one, if you think about it, there are other interesting frameworks that exist. There’s behavioural portfolio theory, there's the popularity stuff. I mean, if you even look at people's expectations, they're radically different even on more traditional assets, like large-cap stocks and bonds. They’re even more different on more esoteric assets. I think it's the esoteric ones that are most prone to regret, the most speculative assets. So, right, you already have massive differences in expectations around cryptocurrencies and everything else.
I don't think it's much, because it’s not like we're talking about like mega-cap stocks here. We're talking about things that have very small market caps. And I think that it won't even necessarily change the total portion of wealth that goes into these assets. Because I think, from my perspective, you'd have a lot of investors owning a little bit than maybe a few investors owning a lot. So, I don't know that there's much there beyond existing frameworks and acknowledging that people are behavioural, irrational creatures to varying degrees.
Interesting. Okay. Now, how do you decide what the regret benchmark should be?
Earlier to your point, it takes a conversation, right? So, to me, the hard part here is that everyone is so different, right? The things that they think they might respond to aren't going to be the things that they do. You almost could create a regret portfolio. You could literally look at Google Trends searches, and be like, “Hey, these are like the 10 things that are persistently interesting” – but the idea I think… for a long time. You let a client open up a Robinhood account, and they can day trade their heart's content with a fraction of their portfolio, because it gives them that kind of high, that gambling high, but it doesn't imperil them accomplishing their financial goals.
This is just kind of saying, “Hey, if you believe this Blanchett guy, this actually gives you justification for doing that because of the emotional response you could have to certain things doing well that you don't own.”
Okay, Blanchett guy, how does this portfolio optimization routine around regret affect the asset allocation of the portfolio?
So, it depends, like the best answer ever. It depends. I think the one thing – I mean a few effects. One is if you have two assets and one is marginally more inefficient than the other, right? If you do any kind of resampling, you'll still have a higher weight the one that is more efficient. But let's just say that the one that is a little bit less efficient, and right now like that's like large-cap stocks, just for example. So, large-cap stocks, okay? Let's say that you have capital market assumptions, CMAs, and everything's fantastic for small-cap, and emerging markets, international, and large cap looks terrible.
Okay, well, large cap is the thing that people focus on the most. People still quote the Dow Jones. It's the weirdest index ever, right? There's the S&P, there's Russell. So, by not owning large cap, you kind of create this potential for regret. Where if it does well, well, why didn't you do well? But if it does poorly, like, no one really cares. So, to me, it's acknowledging one, like, what are the differences in expectations around commonly used assets? That's the first one. And the second one is, maybe before you were investing the full million dollars in your diversified portfolio, now, it's only 950 or 900. I don't know the right number. And they have 100, or some number to do with whatever they want, that they're going to invest speculatively.
In theory, that portfolio won't do as well, that isn't necessarily true, right? I mean, I've been hating on Bitcoin for a long time. If you bought Bitcoin one time, you'd have tons of money. So, while I might not think it's efficient, no one knows what's going to happen. It's not money that's going to get lit on fire. It’s just money that's going to be very volatile. In theory, if you can own multiple volatile assets that have some diversification qualities, it isn't necessarily bad for the portfolio to begin with, but it is by definition, again, assuming your capital returns are reasonable and correct, making the portfolio a little bit more inefficient versus a well-diversified multi-asset portfolio.
That's one of the other things I thought about reading your stuff on this is that it's hard enough to do a mean-variance optimization because we can't predict the future. And this would be even harder, I can only imagine, to truly optimize...
Well, it is. So, I think this requires a bit more resampling. Running multiple iterations of an outcome and seeing how things compare. That's why it is more complicated. Again, I don't expect a lot of advisors to build tools that can do this. Because again, what do you assume is the return of this expensive asset? What is the volatility? No one knows. Come on. How do you even pick numbers here?
Inevitably, what you'll likely have with here are assets that have – it doesn't matter what the return is, they're going to have this astronomical vol. Right? And so, a relatively low geometric return, so you probably wouldn't work well in a more traditional setting, but it does, you're going to say, “Hey, let's acknowledge the fact you're not a robot and think about how you might feel this does well.”
How does the effect of optimizing over regret change depending on risk aversion?
So, it has different effects. So again, there's this thing, well, what is the regret asset? What are you not owning? So, in theory, it could be a really safe asset, or really aggressive. But people don't regret not owning cash. I don't picture that being like the thing that, “Oh, I could have bought cash. I could have made 5%.” It's like, “Oh, I could have bought like Bitcoin or whatever and it went up 10 times.”
So, I think, when I think about this in real life, you would have bought or will buy assets that are really, really aggressive. They have high volatility. If you're a really conservative investor, it could actually increase your expected return based upon your assumptions around the regret assets that increase your risk. If you're a really aggressive investor, it could reduce your return a little bit just based upon the return assumptions, but also increase the risk.
By definition, risk is going to increase, because you're allocating more of your wealth to assets that have high volatility, but the return expectation should be that it's going to go down, but it can be like a bimodal distribution, right? Where in most instances it’s zero, and in some instances, you hold it long enough, it makes you tons of money.
Are there other asset characteristics that might drive optimal allocation to regret assets?
Probably. So, I think the one thing that I didn't really dig into is just all the different ways you can think about when someone regrets not owning something, right? Again, I made this point earlier, but it's like, is it when it goes up 20%, 30%, 40%? Does it go up more than another asset? So, do I only really care about it if it's up more than the S&P?
I think that there are lots of ways to go down this path. What's really important, though, is acknowledging the non-normality aspect of this. Lotteries are a really good example. Academics hate lotteries like it's just this terrible payoff. But I mean, it's kind of interesting if you just buy a small ticket, because if you're just a normal person, how else are you going to buy a yacht one of these days? Well, if you win the lottery, you can buy a yacht.
Again, like I'm not suggesting people go out and buy lottery tickets, but I think what we have to acknowledge when we're kind of managing someone's wealth is that there are lots of different ways to think about outcomes. Yes, they're trying to accomplish a financial goal. But if you invest them in this really efficient and incredibly boring portfolio, does it negatively affect their desire to save? Saving in 401(k) in the US is so boring, right? “Oh, God, I'm going to save 10% a year.” Well, hey, do you wanna invest in Bitcoin? Yes. Are you willing to kind of set some money aside in an account to start out? Yes.
So, I think that there are actually ways that, if you talk about this stuff, you could increase expected wealth on average. Could you play more into the exciting aspect of investing versus just kind of super dull, professionally-managed portfolios that invest in 15 ETFs or whatever else.
So interesting. Instead of the single asset, super boring portfolio being good because it controls behaviour, in this framework, it's not good because it allows for regret, which may lead to bad future behaviour.
One example of an implication that I've seen firsthand is participant behaviours in 401(k) plans during periods of market volatility. So, you'd have door A and door B. You're defaulted into a target date fund where you hold this like black box thing. And then, door B is you’re defaulted in, let’s say, a multi-asset portfolio that you can see, you hold like 15 funds. Without a doubt, individuals are more likely to kind of pull the ripcord, pull the parachute when they're in this single multi-asset fund because they don't understand what they actually own in their portfolio. Right?
So, I think that to the extent that you can demonstrate to someone, that they have a diversified portfolio, there's no additional cost, it can actually kind of encourage better decision-making over time, because people don't understand how diversification works, what a global market portfolio is, and having those individual slices, I think, actually, there are pretty clear behavioural benefits there because it just better, let someone to understand that, “Hey, I don't own one thing. I own thousands of things.”
Wow. Yes, that's counterintuitive. That was a paper you did on the 401(k) behaviour?
Yes. So, looking at how people responded to market volatility. And just to be clear, for the most part, people don't – I think one of the best things that's happened to 401(k) plans, DC plans, is moving away from self-direction. So, you're getting people into target date funds. I mean, by definition, they're not perfect investments, you can't have everyone in a five-year age band at the same portfolio. But if we go back to where we were, 100 million Americans voting portfolios, that's a terrible idea. That is the worst idea ever.
But I think that moving people to the structures that do it for them is really good. But there are ways that I think to kind of tweak it on the margin, to help them make better choices over time.
Could you solve that through disaggregated reporting of the underlying assets instead of actually splitting them up?
So, there are services that build portfolios using core menus. There are actually plans that have what are called custom targeted funds, where they're using the same funds on the core menu to build targeted funds with. You can look at different ways. But like across the board, what you see is what someone has defaulted. So, defaulting is by definition, passive choice. You're not actively engaging. They're the ones who are the least likely to make a trade regardless because they just don't do anything. But the more holdings they have in their portfolio, the less likely they are to make a change when things go wrong when you control for being defaulted, demographics, and all that.
You got a paper on that too, right? Where you've looked at – what was it? So, people didn't make a positive change if they've been defaulted in or something like that?
Okay. So yes, I've got all this fun stuff. It's the unique role that defaults have on a person’s decision-making. One thing that's interesting is how things like the employer matching level and the default level interact, right? If you have a plan that has an employer match, and you have default contributions, what does that do for behaviours? Which one matters more? If you know behavioural finance, the result is not shocking. What really matters is the default, right?
Whatever the default is, people just do that. There’s really interesting effects around things like, if you have a low default rate and a high employer savings rate in the plan, that's actually like a tax on poor people because they're not very sophisticated. They don't understand that you need to save more to get the match. So, they’re just going to go with the default. What you actually see is having higher defaults, but without a doubt, benefits individuals who earn less, who are less sophisticated on average, because they're more prone to just do whatever the default is.
Other cool things too, where like, as you have higher default savings rates, you have higher acceptance of target date funds, and that's because you're not asking someone to do something that they wouldn't do otherwise. Because if the default is like 3%, you’re going to be like, “No, I've heard I’ve got to save 10%. So, if I can't trust the default savings rate, I can't trust the default investment.” When you have higher default savings rates, you actually encourage more individuals to just go with target date funds.
There's tons of evidence now. The problem, though, to be clear, this was an old dataset, but like most plans weren't going over 6%. And 6%, in my opinion, is still pretty low. What I hope to do, at some point it could take five years, is to do a refresh of the data, only have a lot more plans doing 8%, 10%, 12%, as default investment savings rates in 401(k) plans.
So, it's pretty clear, like three versus six, six is a no-brainer. But we already kind of knew that. I think the next step is when we move beyond 6 to 8, 10, and 12, how at some point, things could drop off or change.
Absolutely fascinating. So, it's well known that investors chase attention-grabbing assets. So, what should financial advisors do – should we be catering to or moderating in some way the risk of regret?
I think my opinion on this has probably changed over time. I feel like a decade ago, it would have been like, “Quiet you.” No. You’re not allowed to do that, right? Because I can be like, we know it's an – but I think that the what that doesn't acknowledge is how people will respond, and what it can mean for that relationship if that asset does well. Let's call it a coin flip. Let's call it less than a coin flip. There's like a 30% chance or 20% chance it does well. And then, the entire time the person's like, “Why did I listen to that advice? That was terrible advice.”
So, I think, to me, it's just acknowledging these behavioural aspects of investing. I mean, if I were a client, I would be like, “I don't care about crypto. I just want to have a good portfolio.” I think that's how a lot of people are. Other folks will be like, “I follow this stuff. I love reading about it.” So, I think having the conversation, engaging with them, and saying, “Hey, okay, this is important to you. Just to be clear, I think it belongs in a well-managed portfolio given the uncertainty, but I think no one knows it’s going to happen and it wouldn't kill you to allocate a portion of your assets to it. We have to acknowledge it could go to zero. But if that makes you more comfortable saving, investing, and doing things, I think it totally makes sense.”
I think that's a different perspective than I would even have had 10 years ago because I wouldn't have acknowledged the more behavioural aspect of investing, as I'm increasingly focused on.
Does it then make it harder for the investors to choose a financial advisor? Because then you're kind of doing some sort of regret selection mechanism for the advice you'll be given?
I mean, from my perspective, it's giving the investor permission to invest themselves in these things that they're passionate about. So, I think that there are still areas for advisors to add a lot of value, to understand these assets, understand if someone's going to buy them, where and how they should buy them, checking in with the investor. So, I think if anything, it gives the advisor a unique way to have a more meaningful conversation about investing. What we've seen usually happen here is these don't tend to go well. A lot of these speculative assets tend to do well for a while, and then they tend to crash. So, I think that you don't want someone to fail. But having had that conversation with an investor, setting expectations, limiting their overall allocation to it, and then if the person experiences that eventual decline, that's created kind of a really good way for them to have that relationship.
Maybe it does well. Maybe it takes off. And you can even say, “Hey, I never would have thought this would have happened. But this is why you hold a little bit up.” I wouldn't necessarily recommend allocating more, but I think what it does is it gives a way to kind of have a more meaningful conversation about investing than just like, “Hey, this is the market portfolio. It’s mean and variant efficient, all that.”
Yes, that's really interesting. We've had a lot of conversations like that over the last 10 or so years, where we've explained, “Listen, this is a highly speculative asset. The rational thing to do would be to not allocate it.” The mean-variance approach or similar. But then we've given the explanation of the range of regret outcomes if this thing does go to which, the moon or if it goes to zero, and we've seen people make decisions on that basis with that framework. I think overall, it's been a pretty good decision-making outcome, even if the financial outcome was, the speculative asset did tank. I think people going into it with their eyes open, kind of like the way you've explained your framework is pretty successful. Do you agree, Cameron? You've, you've observed the same kind of thing as me?
For sure. Absolutely.
Instead of just saying, “No, don't invest in this. It doesn't make sense.” It’s like, “Here's what a rational model would predict. Or here's what a normative model would predict. Here's why you might not do that in real life.”
But it also depends on who's driving the choice of that asset. Are people looking for the advisor to help them choose the regret asset or not? They're choosing on their own because they have a passion about crypto or a particular stock or something else. But you're saying, David, to go and do it on their own. Come with that choice and acknowledge the regret decision around that asset choice. As opposed to saying, “Ben, give me a long-shot investment.”
That's why I wanted to ask David, which we did. How do you choose the regret benchmark? Because I don't think we can define it. I think we can go to clients and say, “You might regret not holding Ethereum” –
No. I wouldn't recommend walking in, “Hey, there's like 20 things you could own. Which of these do you want to” – I think it is more self-awareness of the investor, like, which things – I mean, investing in diversified multi-asset portfolios is super, super fun. But are there other things that you're passionate about that you think have potential that maybe we're not going to own?
I mean, yes, if it's individual stocks, we're going to own those, but a small portion. Maybe they think that biotech is the next greatest thing. So then, post to crypto, it's biotech stocks, or it's something else. I think that it takes their preferences to know that. I mean, what you obviously don't get blamed for not owning whatever it does well, but as long as you've kind of checked that box, “Hey, do you have any things that you're really passionate about that you think could do well, that you want to trade more frequently in? And if so, then this is how you do it.”
Again, to me, it's just versus just saying, “No, we don't do that. We don't recommend it. Own this portfolio and just leave me alone.”
Do you think the source of a lot of that regret is kind of story-driven? My friend was invested in this or heard about this at a certain event or geographically perhaps? If you're from a part of the country that might be more oil-and-gas-dominated, or tech-dominated, or crypto-dominated, or whatever it might be?
I mean, hindsight is 20/20. I mean, people don't talk about losing money and things, right? It's only the good stocks they bought, or that they got in early on crypto, or all these things. I think that that's just the nature of people, right? I mean, people don't tend to talk of their failures. They talk about their successes.
You see this when you have assets that have done well, like when Bitcoin, the Super Bowl, a year and two, three months, that was the peak. The floating QR code. I mean, you have this awareness in the media, I think, and that's where it becomes a lot more salient. I don't know that there's always one thing when this happens, I think, it's just certain circles. To your point, you can live in an area that's got a lot of folks that do oil and gas and so, that’s the thing. There could be rental properties. It could be lots of different things.
Obviously, some are easier to own than others. I mean, rental properties, that is a whole different ballgame. I think that's not what I'm thinking about in this. It really is things that are kind of marketable type securities or investments that are easier to buy and sell and transact.
Yes, just on having people around you doing something that might increase regret. The closeness, the closeness to a counterfactual is one of the biggest drivers of feelings of regret. So, instead of thinking about an asset that you might buy, if you're thinking about an asset, like employer stock that you already own, and you're making the decision to sell it, as opposed to how much to sell, as opposed to the decision to buy. That's like, as close as it gets to having owned that asset. Yes. And for that regret framework, that's even more interesting.
I don't have as much as I used to, but I have tons of people that asked me about cryptocurrencies and they bought them, and they made all this money. There's all this social media stuff now. So, I think, the closest in connectivity is a lot more real than it used to be. If in the past, you go back decades, you'd only really hear about people making tons of money in the newspaper or at a random party. That didn't seem very real.
But when it's your connections, your circle, that's talking about their winners, all their winners, and you didn't get it, it just becomes – I think it's becoming more of an issue because it's so much easier for individuals to communicate what they're doing to their closest friends instantly. We didn't have this as easily, decades ago. We do now and it's likely going to get worse. I think, that we're going to become more connected, and so, you just need to be more aware of – I mean, FOMO is a thing, right? This is related to FOMO. This is just one aspect of FOMO where we're investing, not just other social experiences.
Crazy. FOMO is a thing and one of the other big ones is social comparison. That's another big behavioural driver or happiness driver. All your friends get wealthy buying Bitcoin or whatever, then you might feel terrible.
Okay, that discussion of regret was fascinating. Can we move on to your other recent stuff on optimal retirement income strategies?
Sure.
Excellent. What are the downsides of modelling the retirement liability as a single constant inflation-adjusted amount?
So, I'm going to get geeky here again.
Do it. Love it.
I'm going to write a piece soon about “the 1990s want their key assumptions back.” Okay. The point is, is like, so all the early research in retirement was like the 1990s. …was ‘92, or ’94, and more stuff. But if you look at the tools advisors are using in the assumptions, they're mostly identical. I don't know if everyone knows this, but we've gotten a bit more powerful computers out there now than we used to have 30 years ago. But the key assumptions in our financial plans are mostly the same, which to me is a bit disappointing.
So, for example, most research in the vast majority of planning tools assume that the retirement income goal is effectively a static number that increases every year by inflation, right? It's a single value. That's nuts, right? I mean, in reality, like people's expenditures have different levels of elasticity or flexibility, I'm going to make changes as the portfolio evolves, and incorporating these rules into a projection can really affect the outcome. I've been talking about this for, I don’t know, a decade. The guys always say, “Well, David, that's what I do. I go in, and I work with clients every year to tell them what they can afford to spend.” And I'm like, “Well, that's spectacular. But here's the thing: if you account for a dynamic process in a model, that changes your advice today than just doing it over time.”
So, if you can model the fact that you're going to make changes as changes are warranted, it actually changes what you should have done 10 years ago. To me, the goal behind the research, which was just in the Financial Analysts Journal, is to kind of lay out a framework that I think better addresses reality in any kind of financial plan. I totally acknowledge is like a hot mess of assumptions of like 50 years and all this stuff. But you can get radically different outputs, I think, using just more realistic assumptions around things like outcomes metrics, around like spending and stuff like that.
Why is it important to understand the composition of retiree spending, as opposed to having that single spending number?
Utility is how economists quantify preferences. the thing about utility, so Monte Carlo is a model that incorporates randomness, right? That's how most advisors today when they do a financial plan, that's what it is. So, the utility function in a Monte Carlo analysis that uses static projections and success rates, it's binary. It's ones and zeros. So, did I accomplish my goal? I get a one or I get a zero. I get a one, I get a zero. So, the problem with that is that $1 short is a zero. There's no notion there of “if I fail, how did I fail,” right?
When in reality, and this is where things get a bit more complicated, is that if I don't achieve my “goal,” let's call it $100,000, what I can't do is going to have a huge effect on how I feel, right? If I can't pay for my house, my healthcare, my food, I'm going to be really, really angry. If I have to wait a year to buy a new car, I'm upset, but I'm not really angry. So, I think understanding the composition of the spending goal, and then, if you don't accomplish it, where you are is important because, let's say, all of your essential expenditures are covered by guaranteed income. You've got a defined benefit plan, you've got a public pension, whatever. Well, then a shortfall might not be that big of a deal. I can just adjust if I need to.
But let's say that you have very little of your needs are essential expenses covered with guaranteed income, then all of a sudden, a shortfall is more painful. I think, if you don't really understand what you want to spend money on, what the flexibility is, and you do a traditional projection, you're going to get an output that might not reflect how you would actually feel across the different outcomes.
When you look, empirically, what portion of retiree expenditure is elastic versus inelastic?
Seventy-ish is the average, but there's like massive differences. You can look at this using expenditure data. I've done a bunch of surveys. One of the surveys, I asked all these people, like the main expenditure groups in the consumer price index in the US, it's like a consumption stuff, like food at home, food away from home, transportation. An individual's willingness to cut back on those expenditures, right? No one wants to cut back on healthcare for the most part. But some people will cut back on healthcare, but will not cut back on leisure activities, like vacations. That is so important to them, right?
To me, the key with this is that yes, there are clear relationships where, on average, individuals who spend more, tend to spend more and more on things that aren't essential or necessary, there's more choice there. But everyone is different. To me, you can generalize, and I can say 70%. But what I would say more as it takes kind of understanding what you spend money on, what you derive utility satisfaction from, and then figuring out how to do that in a financial way.
Can you talk a little bit more about the district? What drives the differences empirically? Like you mentioned, higher expenses tend to be more variable, what else is there in there?
Again, this is so hard to measure, and I've done it like two ways. One is just to observe expenditures. You can do this in – there's this health and retirement study. You can look at how individual expenditures… not only like what they are, but then how they evolve over time. You can ask them questions about what they perceive to be inflexible or flexible. I think, to me here, just like the number one key is just moving away from a single static number to anything that somehow incorporates this notion that, okay, half of what I'm spending money on, I would not want to change. The other half, I'm willing to, and then seeing how that maps out over time.
Because the biggest thing here is that a lot of Americans, a lot of retirees, have a lot of their needs covered from guaranteed income. So, it dramatically changes what you should be doing in terms of investing their portfolio, and funding retirement, because it's the ones or the more flexible expenses that the portfolio is funding and that's just not how we model retirement. A lot of the models that people use for retirement are from the pension space, like LDI. LDI is built in this framework of a hard liability. Pension plans, they have to make that payment every month, every year, hard stop. That is not going to change. People, though, are very different, right?
So, when I think about building portfolios for retirees, it's more like liability-aware investing. You know the liability is there, you have to acknowledge the flexibility. The moment you introduce flexibility into the process, it just really changes anyone's perspective on what are the right decisions around retirement age, spending, saving all that.
Yes. I got to give a shout-out to your paper on that topic, on liability-driven investing for individual investors. Fantastic paper. Such a good way to think about, well, basically what you just said, trying to model liability matching for households is, it's kind of crazy.
I think it's a useful exercise to think about, right? It's useful. No one saves for their 401(k) because it's fun. I'm like, “Oh, I'm going to sock away 20% a year because it's fun to not spend money today.” You do it to fund a goal, right? So, I think the aspects of that goal should fundamentally drive the portfolio, especially as you get closer to that goal, right? The problem is, is like a lot of famous economists have these models that say, “Oh, retirees should invest all of their money in inflation-adjusted annuities.” Well, you can’t even buy those right? Or you should buy tips. I assume that retirement liability is totally fixed to inflation. Well, it's not.
So, you're assuming that someone would never invest in equities, because they're just super conservative. Well, there's a benefit to investing in equities over the long term. You have a higher return. So, most investors don't own all bonds, because they say, “Hey, there's a compromise here, I'm willing to accept some risk for a higher expected return.” In retirement, I'm willing to accept some flexibility for not having to put all of my money in cash.
So, I think, that acknowledging the trade-off people make in real life, which you can’t make in a household, you can't make in a pension, can lead to, I guess, a very different perspective on again, that kind of optimal portfolio definition.
The perfect hedge with tips is such a good example. And it's not just the discretionary expenses like we've been talking about. But you've got to work also on how expenditure changes relative to inflation over time, so you don't necessarily need perfect CPI adjustments for your income.
Right. So, all these models, most financial plans today, like they assume the return liability increases every year by inflation. Well, on average, and this is somewhat country-specific because it seems like healthcare kind of wrecked the model. Most people as they get older, they don't tend to increase their spending by inflation, they just tend to slow down.
In the US, there's this interesting effect where I talk about the spending smile. Well, like the latter part of the smile is, are these few households that have these like massive healthcare expenditures? If you run a regression on anything, outliers can kind of really affect. The average and the median can differ significantly. that's what happens later on in life, where the average gets pulled back up because you have a few folks that have these big expenditures. But for most people, there's just kind of constant decline in today's dollars versus inflation.
So, let's say that inflation is 3%, and at least one and a half percent more per year. Well, here's the thing. If your public pension benefit is indexed to inflation, which most of them are, it actually reduces the inflationary needs of your portfolio. So, the efficacy of things like tips or inflation-back bonds changes when you kind of acknowledge this structure liability and how it evolves during retirement.
I know we've got one listener that does think this, so I want to ask you the question. Do you think any of that smile is driven by people running out of money, and not being able to spend as much?
Half, yes. I don't think we have a retirement crisis. We have a retirement savings crisis. Developed countries have, for the most part, a really good public pension system. Old folks aren't living on cat food. Things are pretty good. But even if you look at some of the research, I've done this, multiple times, what you find is that, yes, some people are cutting back because they have to. You can put them into groups. You can say, “Okay, this group, these people have like, tons of money. They have too much money.” How does their spending evolve, versus say, the folks that don't have any money? People that have no money, they cut theirs a lot faster. But even the people who have tons of money, they still tend to cut, right? Especially as you move past like 70, 75.
I mean, I would say that anecdotally, I see this with myself and my grandparents. I mean, sure, there are going to be some folks that want to go out and stay active. But I think a lot of people just don't want to do as much as they age. So, I think that's what you're seeing here, which is just that people don't tend to increase their full-on spending by inflation every year.
How did you set up your dynamic spending rule in your recent work on this stuff?
So, I spent about maybe 10 or 15 years looking at dynamic spending rules. Here's the thing, so the vast majority of research out there, great research, it would never actually work in a financial planning software and there's two key reasons here. One, there's like dynamic programming, which is like really cool. It like solves every possible state and tells you the answer. That stuff can take five minutes to do a financial plan. And let me tell you, in my experience, nothing angers a client more than you pressing a button, and you say, “Oh, just wait five minutes,” and then you’re like, “I got a bad answer.” And you’re like, “I want to change this assumption. We're going to wait five more minutes.” That's not going to work. You need to have like, to me, it's like five seconds or less.
That's why, I think, like the most robust way won't work today. It might, when we get to quantum computing. But right now, none a viable solution. There are lots of rules that exist. The problem with the rules is they’re usually based on a portfolio that exists with no uneven cash flows. So, what happens if you retire at 60, you claim your public pension at 65, your wife retires at 70, you have a deferred income annuity that kicks in at 85. That'll break the vast majority of existing dynamic rules to figure out safe controls.
So, what you have to do, to actually have this work in financial planning software, is to have a line of sight into all assets and liabilities. All income coming in, and all outflows going out across the entire length of retirement. How you can do that, is a metric called the funded ratio. Okay? It's really common in pension plans. It's just the assets like your portfolio, net present value of other inflows, like public pension benefits, whatever, overall your spending goal. The idea is that you estimate that within like a Monte Carlo projection every year of every run, and based upon that value is how you would adjust the previous year's spending goals.
For example, in the first year of retirement, the goal is based upon the individual, the retiree, but then how that changes in the model over time would depend on how that funding ratio evolves as you move through retirement. So, if the funding ratio is high, or increases, you can spend more. If it goes down, you'd spend less, and I totally acknowledge that life comes at you fast and what's going to happen? But I think the goal here is just to say, “Hey, you're probably going to make changes over time based upon how things go. This is a way to model that, and then give you context around the possible distributions of outcomes.”
So, a static model, you have all your gold and you fail, it just waterfalls off to nothing. This is like a tulip, where you show a distribution of income levels over time, which is, I think, a better conversation than just assuming that “Oh, you're not going to make a change if your portfolio is going to zero.”
I love that. Well, why do you think we haven't seen more dynamic spending rules in – I mean, you touched on it just now. It's hard to do. But I mean, there are smart people working on these softwares. Why do you think we don't see it?
I don't know. We have, in my experience, seen that a large pivot towards advisors using Monte Carlo-type tools. I would argue there's like deterministic tools where you just have like a single run, a single assumed growth rate. That's probably, when I do surveys, less than 20% of advisors. I would argue probably, those are like the tiny advisors like the big advisors. They're doing like with bigger clients. A lot of them are doing some kind of like Monte Carlo stochastic analysis.
So, I think that these companies are in the business of building better tools, but this isn't something that advisors have ever been demanding. They don't know how this works. I mean, they want to talk about their 78% success rate. I think that that's absurd. You shouldn't tell a client your success rate. Why? That doesn't help them make better choices. But advisors want to quantify this stuff. So, I'm going to be on the soapbox yelling for the next few years. But it's the people that build these tools. They need to build better tools. Advisors are not going to be built – like software engineers, some are. More props to you. But I think what we need is just a greater awareness of some of the key pitfalls in the existing tools and solutions, and then have the giants in this business build these.
I know that some are I know that some are. I know that some are already doing this, and I think the good news, hopefully, is those that do it early, get market share, and then results in other tools that exist to acknowledge, this is important, and figure out how to do it. There’s nothing like top secret if you read the paper, I've literally walked through, step by step, exactly how you can do it in a way that I know for certain can be done very quickly in a Monte Carlo projection, and it can give you useful outputs.
So, I think what we’re previously, well, how would you do this? How do you actually figure out how to make the adjustments that work in the context of production? There are questions there. I'm sure there are other ways to do it. I am certain that if you use the process I lay out, you can do it using existing tools.
The demand side is huge, though. There are a lot of advisors that are still not using, in Canada, at least, that are still not using Monte Carlo even.
Conferences are very bias, right? People who go to conferences like the best. Even when we do like – we've done surveys within PGIM where I work, and we get about 80% of advisors that answer the surveys consistently using Monte Carlo. So, I think it really has kind of caught on as the framework to do financial plans. I just did a piece that came out recently in Advisor Perspectives. Some advisors get all bent out of shape about Monte Carlo, because they're like, “Oh, that requires normal return distributions or uses as a storefront.” I'm like, “No.” There's actually nothing inherent in Monte Carlo like whatsoever. It literally just means you have something that's random in your projection. The rest of it is totally up to you.
So, I think what I want to – what I try to like correct people on that kind of, throw, shade on the idea is like, your tool might be crappy, you might have a crappy calculator. That doesn't mean that all calculators are bad. But what you need is a better calculator. Right? I think that advisors don't understand the fact that yes, we built all the models in a similar way. There are actually infinite ways to do them. I think the goal here is that we just have tools that offer a more robust modelling environment than exists right now.
You talked earlier when he started this segment, about the binary outcome that Monte Carlo gives you, that it's like success or fail. How do you describe the utility metric that you use in this paper to evaluate retirement alternatives?
Again, Monte Carlo, it doesn't have to be binary. Success rates are binary. Success is either you do or you don’t. Ones and zeros. Academics who do research in retirement, the good ones, don't use success rates as their outcomes metric. They think about the full continuum of what it means to accomplish a goal. It’s not a one or a zero. It's like a .9 or .7, or .6 or .5 or 1.3. Simply, as opposed to saying, did I accomplish my goal, one or zero? I can say, well, what percentage of my goal that I accomplish? And that would be between, let's just say, zero and one. Let's say you can't ever find a goal.
So, I got 90% of my goal. All of a sudden, that's a full curve, it goes to zero to one. It's not just ones and zeros. On top of that, you could further adjust the numbers. You can say, “Well, if it's .9, I'm okay with that. But if it's a .3, I'm going to get really, really angry, so I’m just going to make that a .1.” Okay, and then the key is how you aggregate them. So, I talk about this and the guys are like, “David, this is so complicated. I don’t want to show them this.” I don't think they should. I don't think that as an industry, we should be showing clients numbers about outcomes, and 50-year projections, right? All you're trying to tell someone is are you in really bad shape? Are you in bad shape? Are you in pretty good shape or really good shape? I'm not going to name the company, but a company with 100,000 Monte Carlo simulations. I'm like, “What are you doing?” Maybe it sounds cool. But you're not helping anyone with that kind of model. They're even using historical returns. I'm like, “This is absurd. You're doing 100,000 runs with purely historical long-term averages. What's the point of that?”
I think the key should be relaying information in a way that individuals can understand it. So, I like complicated models behind the scenes that do dynamic withdrawals, but I like, I don't know if it's like bunnies, or like a thermometer gauge, or whatever else it is. But you're in terrible shape, you're in great shape, and that's really about all we can tell you.
So, I think, what's really important here is that yes, this stuff sounds complex, and I'm a fan of building things that I think better reflect reality. But how you communicate that to clients or advisors can be very different than the math behind the scenes.
Funny planning. There's a business plan for it.
There's like, you do cloud. So, the group, I give them my input and ignore me. We're thinking about how you do that. My key is, it's not a number. I don't think telling someone that there's a 90% success rate really helps them make better choices, because in reality, they're in really good shape. If you have a 90% success rate. That means in this model, assuming good assumptions, you never have to make a change to your goal once. And then when you fail, you probably only fail by a tiny bit. But then, because it's only 90, do they get nervous? Well, oh, my God. What happens if I fail? Failures in Monte Carlo are not plane crashes. Certain individuals who will remain nameless, have been like, “You can't trust financial planning because you don't want to get on an airplane, it's going to fail 10% of the time.” That's absurd. That's not what a failure in Monte Carlo means. The clients don't understand that.
That's why I worry. To some advisers, it's like a badge of honour. “My clients have 90% success rates.” I'm like, “That's ridiculous. Your clients aren't enjoying their lives because you're targeting a crazy high success rate.” I think that if you take the numbers out of it, or at least out of the outcome, I think that could help advisors and retirees, and households make better choices.
Nobody wants to see a bunny failure.
That's right. A bunny on a plane crash, now, that would just be terrible, right?
Terrible. So, how do first-year safe withdrawal rates change when you incorporate needs and wants and dynamic spending, and utility as opposed to static spending?
Again, unequivocally like they go up. So, think about like a static goal with success rates, ones and zeros. I think we're going to get into trouble, and why now is more important is there has been a greater awareness among advisors that you have to plan for retirements that last 30 plus years, 30 to 35 years, okay? And when you do static projections, and you assume retirement lasts 35 years, when the person fails, it's like in the 34th year of retirement, when they're like 99, and they fail by this much. Capturing the fact that, “Oh, okay, maybe they're going to fail eventually but only by this much.” What it tends to do pretty unequivocally is give someone to be able will to spend more today, right? You're taking the handcuffs off of like, “Oh, it's just ones and zeros.” Ones and zeros, just like ones and .99s, right?
So, you tend to see more aggressive portfolios than you would get using traditional LDI. You tend to see higher withdrawal rates. What kind of interesting is there is actually some ambiguity around allocations to guaranteed income like annuities. What you tend to see in these models is that it's really valuable to fund their essential expenditures. But beyond that, it's a lot more dealer's choice, right? So, people out there are like, retirees, only more annuities. Well, how are they going to feel about a shortfall? What is their capacity to adjust? I think having the essential expenditures covered is really important. Beyond that, that's more of a, how do you feel about creative income and everything else?
That's kind of crazy. So, you can have a model specified to output a large annuity allocation, is kind of what you're saying? Where if you modelled preferences a certain way?
So, let's just say that like a more traditional immediate income annuity. Nominal, you give money to the insurance company, they pay you $7,000 a year for life. The problem with that in a Monte Carlo projection is that it tends to lead to like a – it's like a tipping point, where based upon your assumptions, it makes it look really good or really bad. So, if you have conservative CMAs, and long retirement, like, “Oh, it dominates. I should own all of this.” I think the key is, annuities, they can improve outcomes. But it's understanding – the most important thing is, what is the goal? The goal is to have income for life. One, do you need it? What are your existing sources of guaranteed income?
The problem with success rates, you can have a 0% success rate, and be on track to replace 98% of your goal. You can have all of your needs, and almost all your wants covered, because your portfolio, that tiny piece, that's all success rates measure is what is your portfolio doing versus your goal. So, I think what that gives us this wrong context about like, “Oh, successful, unsuccessful.” No, it's like you think about how you're doing more holistically, again, like static withdrawals, success rates, I don't think it gives advisors that correct picture.
Okay to come back to Monte Carlo or traditional Monte Carlo, the way that it's generally used by financial advisors, how would a plan, a financial plan optimized for utility as we've been talking about, with split out expenses for elastic and inelastic? If we optimize a plan in that framework, how would it look if we went back and evaluated it with a traditional typical framework?
Yes. So again, like what you would tend to see, so if you're doing like a solver, you said, “Okay, well, like How do things look?” You'll typically get higher or much higher safe withdrawal rates if you incorporate flexibility and utility. You tend to get a little more aggressive portfolios, right? Because again, it's about trade-offs, right? Life is all about trade-offs. That's what it is. So, I think that a lot of the more traditional LDI-focused models are all about conservatism and you got to – you want to have strong guaranteed annual returns. Well, you want to invest in equities if it means that there's a chance I can go on more vacations if I'm going to roll the dice there.
But then also, it's to me, the biggest thing is the role of guaranteed income and do people need more. If you use static assumptions in a base utility model, which is actually really common in the research. It just says everyone needs more annuities. That is like the takeaway that you hear all the time. Academics, “Oh, more annuities.” I like guaranteed lifetime income, just to be clear. And the problem with that is it's doing that whole static failure thing. It's like, “Oh, you're going to go from all your goal to none of it. But if you glide down slowly, it really changes how efficient an outcome is.” So, when you evolve a plan from static to dynamic, and you overlay utility, you get very different results than if you can just assume those static withdrawals.
Okay, that's super interesting. So, we know empirically, like you talked about earlier, that people do spend dynamically or they do have flexibility in their spending. Could that help explain the so-called annuity puzzle?
I think it explains part of it. I think that annuities are sold, not bought. Some are complicated. Some make a lot of sense. A lot of them have high commissions, high fees are opaque. There are all these problems. I think that if you take a step back, and we can all agree, retirement is incredibly complicated. The shift towards idiosyncratic longevity risk is not good for retirees. You have to manage it. So, I think that there are lots of reasons that people talk about why individuals don't allocate more to annuities. I think that we're seeing products that offer revocability, that offer cash refund provisions. We're kind of slowly moving away from these things that individuals clearly desire. But I think there's this larger question of, what am I guaranteeing? If I have a super strong preference for going golfing every day forever and doing all these different things, then by definition, I should value an annuity if I don't have that already.
But people already have a lot of public pension benefits, right? They already have Social Security. They might have other forms of guaranteed income. So, I think to your point, it does suggest part of the reason why individuals don't annuitize more is because they like the liquidity, the freedom, and the flexibility of having a portfolio to fund those more flexible expenses, especially once they have those essential expenses covered for life.
Wow, where does this research go next?
Really, well, I just hope people build more tools. I mean, we're working on a tool that kind of does this within PGIM. There are other companies that do this, that I think – to me, like, the most important thing here is a more realistic framework to give people advice and guidance. And again, Monte Carlo, 50 years, hot mess of stuff is going to go wrong. But assuming that someone's going to make a change, if they have to, you're not going to be giving them good advice out of the gate.
So, to me, I think that a lot of this is, like the earlier regret. It's helping individuals achieve better financial outcomes across a variety of definitions of what it means to achieve a goal. It's not just variance. It's regret and variance. With respect to like this research around static, that it goes, it's just a more realistic financial plan. And in reality, what it should do, hopefully, we can communicate outcomes better to clients, so we can actually make them more comfortable depleting their assets and using their portfolio to fund spending earlier in retirement.
Super interesting. Okay, we got a couple more papers we want to ask you about total change of topic, but they're just so, so good, I didn't want to leave them out. You did some survey-based research on how an advisor channel affects passive fund choice. Can you talk about that research?
I have a few things that are related to this topic of how advisors are registered, how they're compensated, and to the extent that it might affect decisions that they make with respect to clients. At the end of the day, I don't know that I have like super strong theoretical preferences as to how an advisor gets paid, fee commission, whatever. As long as it's fully disclosed and transparent.
Where it becomes an issue, though, is when there's research that suggests that advisors that are paid one way or do things another way, perhaps create better outcomes on average for their clients, where there's more kind of, “Okay, yes, you're going to get paid, but it doesn’t affect your decision making.”
So, you can look at the selection of funds. I have another piece that's under review at a journal right now, looking at how equity allocations vary over time. Based upon Commission Code. So, there's A, B, C, D Commission Code. Do advisors who get paid more upfront, do they exhibit more time very risk averse? And they do. I think, to me, what this larger body of research is saying is that again, theoretically, people get paid different ways, like, okay. But there is growing evidence that how they're paid, might affect their decisions, and not always in the best interest of their clients. That, to me, is the key behind this is that, in theory, it shouldn't matter. But in reality, it does appear to matter.
How do you think clients should use this information?
So, the problem is, is that I don't know that clients can really figure out if an advisor is doing a good or bad job, right? It's so hard to know. There's a fancy term that I'm forgetting about the type of good that advice is, where you can't – you don't know even afterwards if they did a good job. I think that you look for the positive signals, like are they a Certified Financial Planner? Are they transparent in their fees?
But even then, I mean, just to be honest, if I were a crook, I would want to get a CFP because it would make me seem like I'm less of a crook. I mean, we can't just say that, “Oh, CFPs are all great,” because I would have an incentive to literally get one because it creates a halo effect. But by definition, if you have a CFP, you have taken some tests that are difficult, you have minimum education requirements, and you have relatively a clean regulatory history. I think that there are things that households should be doing, that are kind of filtering out all advisors into those that at least appear to be more professional than just you meet someone at a cocktail party and they're your guy. I wouldn't recommend that. I think you need to do due diligence and understand, what are the person's qualifications. Things like that.
Yes. We just did an episode on what are the measurable benefits of financial advice, and we talked a lot about that. That's why I had the Cretan’s good word in my head…
There you go. So, you got it.
Yes. There's a bunch of literature, like you're talking about, on how commission-based advice tends to be really not so good. So, I think that compensation piece seems to be all the education stuff, totally agree. But that compensation piece seems to be a pretty, pretty clear filter, at least as a baseline.
To me, that like the one nuance there is, I'm not convinced that conditions themselves are the problem. It's the individuals who tend to sell things that are commission based. I mean, it's a nuance there were like, because fees, if you do AUM, any model that you can create, there's going to be negative incentives. But I think that at least structurally, the quality of advisors that are paid based upon commission are lower quality, on average, than those that are paid based upon assets under management, right?
Yes, you could say, “Well, then we should be in commissions.” Well, then if it's the same advisors, they'll just find a new way to do things that aren't as good with AUM. To me, there's this question of: is there a signalling thing there where it's really not just the fact that how they're paid, it's because they're just not as good? CFP versus non-CFP. So, I think that this is all really difficult to figure out until after the fact. Do they actually do a good job? But I think that our profession has evolved a lot. I did internships in this business 20 years ago. “Oh, you’re a stockbroker?” I mean, I guess. That's what you do. You just buy and sell stocks, right? So, we're evolving, there are higher standards, and so I think that it's all good. But there are still a lot of folks in this industry that don't do things that I think are always in the client's best interest.
Yes. One more big pivot in terms of topics, you had another paper on foreign revenue. How important is the country that equities derive their revenue from as opposed to their country of domicile and explaining returns?
It depends on the quality of the defence. I think what sparked this different piece of research was actually a new data point and when you start direct. This is actually when I was Morningstar. That’s where we’re working on this. That provides information on the percentage of revenue from a given index or fund from different countries, right? Because I mean, domicile is binary, right? You assign a company to a country, and how that is determined. It could be totally for tax reasons or something else. It's not like you wait for companies across different countries. You usually put them in a single domicile.
I think there's this question of well, does that accurately capture the true global risks of a company? And the answer is obviously no, right? I mean, usually, smaller companies have most revenue domestically, but as you get larger, you're going to have a larger and larger share that's International. So, I think there have been other folks that have kind of analyzed this, but I think, do we need to, as our society becomes increasingly global, think about different ways to construct indexes or portfolios, given the vastly different revenue profiles that exist across countries that are in these indices, and across countries.
I think, to me, that was the point, is just that there clears to be a huge effect, possibly larger than domicile, in terms of what drives the returns of a given index, based upon location, right? I forget some of the stats in the piece. But certain countries have most of the revenue from their largest companies come from globally. Well, if we go way back to LDI for individual portfolios, what you would kind of want is, if I live in the UK, I would probably want to own stocks to kind of track the UK market pretty well. If inflation takes off, and prices go higher, they do well. Well, if all the revenue from the companies in the UK comes from Europe, in China, or just wherever else, and that doesn't help me, isn't it?
So, I think that there are ways you could think about building portfolios of securities, whatever else that helps better kind of track what you're trying to do with a given strategy that you would not capture necessarily at all in domicile.
That's super interesting. That's one of the home country bias arguments that you did. It can be sensible for the reason you just said, to hedge local consumption, but you're saying you can't just do that with a local index, you have to do it with the revenues from local companies, which could be totally different from the local index, right?
I mean, it tends to kind of all washout, right? You tend to see some are very local, some are global. But if you really wanted to do that, you could. I mean, I think MSCI like walked down this path a decade ago. I don't think they did anything with it. But like you really could create locally focused indices that would give, I think, especially like retirees a better exposure – to the equity market, their local equity, right?
There are two pieces, right? There's the discount rate side and the cash flow side. So, for long-term investors, you might be affected by foreign discount rates, if you own foreign companies that derive most of their revenue from the UK in that example. You're affected the foreign discount rates, but in the long run, the cash flow side is more driven by the local UK stuff, which is maybe what you care more about, at least, in the example if someone wanting to hedge local consumption. Super interesting.
Does this finding dramatically change people's home country bias? If you look around the world, do you know?
Not really, I mean, so like small-cap companies are really still mostly domestic,, the US especially right? And I think this is, and it has been a larger issue for smaller countries that aren't – they don't have as large of a global footprint as the US. But that's just always been how it is. So then, I tried to build a diversified portfolio doing that, and it's kind of tough, because in certain industries, everyone in the industry is global.
So, I think that, to me, there's just this question, like, again, as we move forward in the future, and we have this increasingly connected global economy. In theory, domicile just becomes more and more meaningless as a metric, considering other metrics could yield a very different perspective on the global risks, for example, of an index. Even if you're not doing any kind of … decomposition, you're not doing RBSA and all that. You might just say, “Oh, well, this is a US large-cap fund.” Well, yes, all the companies are domiciled in the US. But this fund, in particular, has 60% of the revenues or 80% of the revenues coming from other countries. So, it really is an international exposure with domestic domicile.
Okay, now that is often used as a reason, particularly by US investors to not need international diversification. Do you think that this negates the need for international diversification?
To some extent it does. Again, I forget the numbers. But if you own Coca-Cola, that isn't like they're just selling Coke here in the US. All these really large, really, really large Apple, they are truly global companies. So, I think that it does negate the need for owning… because there is significant revenue for most of these companies that is.
Cool. Well, that's the last of our questions, David. This has been fantastic, as usual. Thanks a lot for coming back on the podcast.
Yes. Thanks, David. Amazing.
Sure. Thanks for having me.
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'Regret and Optimal Portfolio Allocations' — https://www.pm-research.com/content/iijpormgmt/49/4/143.full.pdf
'Redefining the Optimal Retirement Income Strategy' — https://www.tandfonline.com/doi/full/10.1080/0015198X.2022.2129947
'Does Advisor Channel Influence Passive Fund Choice?' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4068853
'Foreign Revenue: A New World of Risk Exposures' — https://www.pm-research.com/content/iijpormgmt/47/6/175
'Keep Keeping Your Distance: An Updated Look at 401(k) Participant Behaviors During the COVID-19 Crisis' — https://www.morningstar.com/articles/1032011/keep-keeping-your-distance-an-updated-look-at-401k-participant-behaviors-during-the-covid-19-crisis
'Save more with less: The impact of employer defaults and match rates on retirement saving' — https://onlinelibrary.wiley.com/doi/abs/10.1002/cfp2.1152
'The Problems with Monte Carlo are in Your Mind' — https://www.advisorperspectives.com/articles/2023/04/24/the-problems-with-monte-carlo-are-in-your-mind
'Foreign Revenue: A New World of Risk Exposures' — https://www.pm-research.com/content/iijpormgmt/47/6/175