Join us as we present a compilation of segments on expected returns and the dynamics that shape investment outcomes. We deep dive into the world of financial predictions and gain a comprehensive understanding of how expected returns influence your financial decision-making. We then go back to the episode with Dr. Brian Portnoy where we delved into his book, The Geometry of Wealth. Finally, joining our conversation is our colleague Matt Gour who discusses The Power of Moments by Chip and Dan Heath. We discuss how extraordinary moments have the power to shape our lives and the pivotal importance of crafting unforgettable experiences. Tune in now!
Key Points From This Episode:
What Pressor Fama had to say about expected returns. (0:03:35)
Looking at returns through a historical lens with Professor Goetzmann. (0:08:23)
Professor Cederburg explains the usefulness of historical data. (0:11:38)
Hear Professor Cochrane’s perspective on expected returns. (0:15:19)
Professor Cornell shares his contrasting view on historical returns. (0:23:41)
We recap our discussion with Professor French about uncertainty. (0:34:23)
Breaking down the conventional viewpoint of uncertainty with Professor Pastor. (0:38:34)
A brief overview of our approach to estimating expected returns. (0:44:03)
Highlights from our conversation with Dr. Brian Portnoy about his book. (0:47:56)
Matt Gour joins us for our weekly book review of The Power of Moments. (0:51:15)
He shares an impactful moment from his childhood. (0:54:04)
We unpack a main takeaway from the book: the peak-end rule. (0:56:23)
The four elements needed to create a defining moment. (0:57:51)
Learn about the different types of defining moments. (1:01:02)
How to be deliberate about creating powerful moments. (1:01:02)
Main takeaways from the book. (1:04:55)
The aftershow, planned meetups, upcoming projects, and more. (1:07:15)
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 259. Ben, I love episodes like this. I love compilation episodes. I think it's so cool when you go back through past shows and assemble pieces from various guests. That's what we kick off today. You do a deep dive on expected returns. Then we’ll do a quick recap of episode 102 with Dr. Brian Portnoy and his excellent book, The Geometry of Wealth, and then we're joined by our colleague, long-time colleague Matt Gour, who's going to review the book, The Power of Moments by Chip and Dan Heath. Then, of course, we have the aftershow. Any other insights you want to give, Ben?
Ben Felix: Not at this time. But let's go ahead to the episode where there will be more.
Cameron Passmore: All right, let's get going here, Ben. Why don't you dive into your compilation of expected returns?
Ben Felix: Something that we have asked many guests about is expected returns. How would they approach estimating expected returns for financial planning purposes? We revisit a handful of those conversations and you'll see that the answers range from anything between maybe 5% to more complex approaches that include using valuations, to measure expected returns based on market prices and possible combinations of those approaches. Expected returns are, of course, one of the most important concepts in both the study of finance and in personal financial planning.
One of our past guests explained that expected returns are like the speed of light, or Planck's constant in physics, except that expected returns are not constant and we don't know what value to assign to them. Just as important, but, yeah, they're not actually constants, which makes it a lot harder. That's one of the reasons finance is hard and personal finance is even harder. I mean, that's the Bill Sharpe quote about retirement planning being the hardest, nastiest problem in finance, something like that. But that a lot of that ties back to uncertainty and expected returns, uncertainty and life expectancy, all these areas of uncertainty.
Anyway, expected returns are a big source of uncertainty for people engaging in personal financial planning. We've spent, because that's like, that is what we do. We help people think about the future through the lens of their finances. We've spent a lot of time trying to figure out the most reasonable, and we recognize fully that we can't predict the future, but we want to figure out the most reasonable approach to estimating expected returns for financial planning purposes, well, being fully aware to reiterate that this is not and cannot possibly be an exact science.
We have an approach and it'll be interesting to go through these clips and hear what the leading experts in financial economics have to say about expected returns and end at the very end, I'll do a very brief overview of our methodology. I think people will see that the way we do it ties together with all of these people.
Now, there's of course, selection bias in these clips and in the people that we asked and our methodologies align with them for a reason, so it's not just by chance. Anyway, so we'll go ahead to our first clip with Professor Eugene Fama from Episode 200.
Ben Felix: What do you think makes sense to use as an estimate for expected stock returns, just market returns?
Eugene Fama: Okay. That's a very good question because I don't know what to use except for the historical average return. The problem is historical average return is the number whose deviation from the true expected value has a big variance. You just don't get a lot of information, even with a huge sample of data about what the true expected market return is. I think the market return from back to 26 to now, return in access for rate has been in the neighbourhood of maybe 4% or 5%. But the uncertainty on that numbers means that two standard deviations away could be much closer to zero, or much, much higher. Even though you have now almost 100 years of data on this, you still don't get a very precise estimate of the expected value. That's a fact of life in investing that there's just no way to get around to that, to handle it in any better way. We just don't know the expected premium of stocks over bills, for example.
Cameron Passmore: What about the expected factor premiums?
Eugene Fama:Same thing. Because as long as you have stock returns in there, the variance that’s associated with them is going to be very high. The expected values of any premiums that you put in are always very uncertain, no matter how much data you have. Or another way to think about it is you'll never get enough data to know that for certain, you'll get a positive, expected, premium. Even if I tell you the expected value of the premium, you don't know that in any finite simple, you will get that because the variance is so high.
Ben Felix: Yeah. And we don't know the expected value, so it's a –
Eugene Fama: So, it's a double premium. Right.
Ben Felix: We touched on randomness earlier in an efficient market. Do you think long-term investors should think about returns as random, or as predictable? Long-term investors.
Eugene Fama: Predictable in the sense that I think stocks have higher expected returns than bills, predictable in that sense. It's not predictable in the sense that I know for sure that stocks will do better than bills over any length of time. It becomes more likely the longer the period, but it still never said. I don't know if that answers your question or not though.
Ben Felix: I'm thinking, John Cochrane, for example, talks about long-term predictability and that in the very long run stocks are a little bit less risky than you'd expect if they were completely IID.
Eugene Fama: Yeah. Oh, okay. Right. There's some negative autocorrelations built in there that lowers the variability long-term relative to short-term. Those numbers themselves, the autocorrelation numbers themselves are estimated with a lot of uncertainty. You can't really get a precise hook on that either, but he's right on that.
Ben Felix: Interesting. If you're thinking about long-term returns, it's really, IID and use historical as the –
Eugene Fama: Yeah. What it looks like, the reason it's not IID, at least him and I wrote a paper on this too, and John did, too. It's not the same paper. But the paper we wrote basically said, if expected returns vary through time, but they're mean reverting, in other words, they don't go off to infinity, plus or minus, they tend to come back to a constant mean, then you're going to get overwhelmed, if I look at long periods, I'm going to observe some negative autocorrelation generated by this variation in the underlying mean.
The way the empirical work, this goes back to the early '90s I think, the way the empirical turned out, that seemed to be a good story for the behaviour of stock returns. There was never anything in that, that was a message for investors. Because you're talking about variation and the underlying expected value that's really not so big relative to variation around the expected value, and with a ton of uncertainty about estimating the process that generates that time-varying expected value.
Ben Felix: Okay, so from Fama's comments, the historical return is probably useful, but there's a ton of uncertainty about what the actual expected return is based on the historical realized return. Lots of challenges in there. Stock returns may be a little bit mean-reverting, but that process is also full of uncertainty.
Now, it's always going to be imprecise based on what Professor Fama told us, but collecting more historical data might be informative. Interestingly, it does seem to tell a consistent story going back hundreds of years. We talked to Will Goetzmann about that in episode 248.
Ben Felix: Okay. We are going to get into bubbles and innovations later. But before we progress on this, how informative do you think data from hundreds of years ago are about expected returns today?
Will Goetzmann: Well, you're asking a real financial question, expected returns, which means what kind of growth, or benefits do I expect from owning a share of stock, or a part of the stock index today, on average, over months and years? That is a puzzle for many people, and the reason for that is that the returns you get from investing are not stable. They vary quite a bit. With that volatility, that volatility creates uncertainty. It could take you 20, 30, or 40 years to really understand what the expected return, or what the average historical return is. But we'd like to think that once you've discovered something that makes money, it's going to keep on going before you can really put any kind of boundary on it at all.
As financial historians, and financial economists, were plagued by that uncertainty about what the expected return is. But history helps you, because what I found in my research is that, well, over very long stretches of time, the stock market returns some amount in a relatively narrow band once you can control for things like inflation.
Ben Felix: What's the furthest back in time that you've looked at equity returns?
Will Goetzmann: Well, equity returns are the returns of owning companies, or investing as a shareholder. I've looked at some data with my co-authors for very early companies that were created in France, in the 1300s and that's fascinating. Nobody knows that companies existed that far back. Or that, what's even more miraculous is that somehow in the city of Toulouse, people saved the documents of these ancient firms. That was fantastic. We have good measurements of the returns to shareholders from about the middle of the 1500s, early 1500s. Those things, for at least one of the companies, goes all the way up into the 1940s. That was very exciting to see.
Ben Felix: That's fascinating. The returns going back that far are still in that sort of narrow band that we see in more modern times?
Will Goetzmann: Okay, so we've studied one company that stretched the whole time period. It was about 5% real returns, between 4% and 5%, on top of inflation. That's not too far different than what the US has experienced over the last couple of 100 years.
Now, sometimes the stock markets go up faster than that, 5% or 6% per year, inflation-adjusted. And then, sometimes you run into periods like a whole decade, where there's no return at all, on average. That's the variation. But the 5% real return for an equity investment is surprisingly modern, even though it comes from looking at this ancient company that lasted over centuries.
Ben Felix: We also talked to Scott Cederburg. That was a very memorable episode, that's been discussed a ton afterwards. We talked to Scott Cederburg about the usefulness and relevance of very long-term historical data for thinking about the future back in episode 224.
Ben Felix: Why do you think having data like yours that corrects for the easy data bias and the survivor bias, why do you think that's important for financial decision-making?
Scott Cederburg: Yeah, I think it's really important for any forward-looking thing. I mean, in one sense, we're obviously looking backwards and we're looking at all these historical periods. When I'm thinking about this stuff, I'm always trying to think about, the reason that we got into this in the first place is very practical. It’s like, what could happen to my investments over the next 30 years? The focus that we've been doing so far, is distributions of returns at a long horizon, like a 30-year horizon. If I'm sitting here in 2022, and I'm thinking about what's going to happen to me over the next 30 years, we've seen just a lot of paths that countries and markets have taken, historically, that I don't think would have been anticipated at the beginning of those periods. I think, just trying to get as much of an ex-ante view of the world as possible is helpful.
Cameron Passmore: My last question on this section for you, Scott, it's got to do with, you've done all this work over so many years, going back a 100 and plus years, right? I can hear listeners wondering, with all the change in market structure, technology, competitiveness, information, does that change the applicability of this information? How do you think about that?
Scott Cederburg: That's a great point. We've certainly thought about that a lot. There's a couple of aspects. One, if you look back at return days, it doesn't look that different in the early part than the later part. You think about the massive changes in the way that everything's traded, and just all the economic developments that have been and technological developments, but it's still some people coming together and trading some stocks that are reflecting some macro-economic conditions and all this stuff.
The other thing that we've done is at least post-war, we can just basically chop off everything World War II and prior. We had pretty similar estimates on loss probabilities. In our earlier paper in the JFE that we just looked at stocks, we had one specification there. We did every starting period from 1841 to 2000 in that one. The loss probability, just using post-2000 data, we were estimating was 19%. It doesn't seem like the more recent data is indicative that there's just no more tail risk.
Cameron Passmore: Wow.
Scott Cederburg: Like Japan, starting in 1980, is another example, where it just sometimes things can happen. Japan and the US were by far the two largest stock markets in the world at that time. It's not even just small markets, and it's not just worse. There are some risks.
Ben Felix: That one's crazy because I think Japan at one point was much bigger than the US, right?
Scott Cederburg: Yeah, it is. The last 30 years of our sample are perfectly timed on that particular thing, just by happenstance. Because I think, even in 1989, prices are still running up, and then it was 1990 and beyond were pretty awful.
Ben Felix: Some great insight there from Scott on both the usefulness of historical data, but also the relevance. I found that part really interesting, how long-term historical data, even though we might think, “Oh, the world's changed or whatever,” but no, it's still highly relevant to today.
Next, let's hear from Professor John Cochrane from back in episode 169 on how he thinks about expected returns.
Ben Felix: What should you use for an expected return for financial planning purposes? Should it be related to valuation ratios, or should it be the long-run average?
John Cochrane: You should use risk management. I think there is a tendency to survey the expected return forecast and say, "Aha, the expected return forecast is 4.23%. So, we will plan on for the next 50 years, we'll lock in. We can spend 4.23% of our portfolio.” That's probably not such a wise idea. This is a number that is subject to great uncertainty. The historical average is pretty darn good. Now it depends when you take your beginning and end of sample, but your numbers in the 5%, 6%, 7%, 8%. Now, one way I like to think about this is did your grandfather, or great-grandfather know in 1945, that stocks were going to earn on average 8% more than bonds, and he put it all into bonds, which is what my grandfather did even though he was a stockbroker, wonderful man.
Cameron Passmore: Wow.
John Cochrane: I have to work for a living for a reason. No, nobody knew this was going to happen, right? In 1945, all the worthy economists were saying, “Secular stagnation.” The idea that we would have 50 years of the greatest economic growth ever seen, with zeros in front of it, is arguably a surprise. And with it, the stock market returns. Valuation ratios were much lower than, and it kind of do seem to be permanently higher down. A lot of the observed return, this is a great Gene Fama and Ken French paper. A lot of the observed return from 1945 until now comes with the price-to-earning ratio rising. If that price-to-earning ratio rises permanently, which is good reasons to think it is a permanently higher price is relative to earnings. Back in 1945, to own stocks, you had to clip, you had to actually have physical shares and put them in a safe deposit box. Normal people didn't own stocks.
Now we have 401(k) plans and index funds, so stock ownership is much more wide. Why history is not a – well, the future may not be like the past. Our economic growth is now kind of stuck in sclerosis and everything out of Washington seems to tell me, we're going to be having the next 50 years are not going to see the 3.5%, 4% growth that the last 50, 60 years do, unless these guys wake up and just recognize that economic growth is the challenge, not all the other stuff they're looking at.
So, you got to kind of take your best guess. Most academics now are saying, maybe in the four percent-ish range, but that's as much of a guess in an echo chamber as anything else is. There is this equity premium puzzle. It's been very hard for a long time to come up with economic models that justify 5%, 6%, and 7% stock premium over bonds. After you've tossed a puzzle, now, economists are pretty good about this stuff. It’s a puzzle, our models don't work. This is the Mehra Prescott equity premium puzzle. You spend 30 years trying to make better models and say, "Oh, the world's right, but our models are wrong." Economists are pretty good about that.
Well, here we are 30, 40 years later, and the models still don't generate 5%, 6%, 7% regular premium of stocks or bonds. The risk is just not that big in stocks. There is risk in stocks, but this looks too good to be true. Well, maybe the models were right after all and going forwards were more in the 3%, 4% that the model's constrained to get. That's what we know about it, which is not much. And that's why I always say, number one, don't pay taxes. You don't have to. Number two, risk managements, it might be good, might be bad. Number three, my best guess is in the 3% or 4% range, but I don't know anymore than anybody else
Cameron Passmore: I take away from that, John, that your grandfather didn't appreciate the return that was on the horizon. Am I overstating that from you? I understand that people today might be underappreciating the risk that they're looking at?
John Cochrane: Yeah. I don't want to say – my grandfather's a wonderful guy. With typical family skill at market timing. He started out as a stockbroker in the summer of 1929. The subsequent years were a searing, very difficult time for him and everybody else around. That he personally was not willing to jump in 1945, I think is understandable. That was the consensus as economic opinion. We're right back to the Great Depression, which is what all of the good Keynesians and Worthies were saying in 1945.
Going forward, yes, risks are – long-run risks, I think are more than people think, which is it's got to be – if you want to justify even if bonds are paying 1.6% and you want to justify stocks paying anything more than 1.7%, you need some sense of long-run risk. Those risks do add up over the long run. The primary part of the long-run risk is not the valuation risk, I think. Price dividend ratios can vary. That's kind of the short – if you want to call a decade a short-run risk, you might have to sell at a time that prices are really low, like in the middle of another Great Depression, relative to dividends.
But the big question is what is dividend growth going to be like for the next 30, 40, or 50 years for the return? Because the return is dividend growth plus change in the price-dividend ratio, roughly. Well, leaving the change in the price dividend ratio alone, which is kind of the speculation, the valuation risk, the dividend growth risk is there. Do you think economic growth is baked in at 2% a year, which is already, that's two percentage points down from the post-World War II era. That's bad for returns. How much risk do you think there is in those long-run growth rates?
I think there is actually more risk in those long-run growth rates than people say. The end of Pax Americana, the decline of America is not going to be good for economic growth and for the stock market, if that happens. And certainly, risk means things that we aren't expecting to happen, but that could happen. And so, the risks of our government falling apart, our political system falling apart, climate change is nothing compared to, I would think that kind of risk. Historically, worse have been bad. So now, we're back on valuation risk, but if China invades Taiwan and we do nothing about it, I would look for a decline in the stock market. Yeah, there has to be risk out there and it's less longer horizons than shorter horizons. Risk is better borne by people with long-horizon strategies, but you don't get that return in return for nothing.
You get that return for bearing risk. You also get returns for thinking. It is true that if you can think about things better than the other person, you're going to make money. Markets reward people who are better to outthink everybody else. If you got a better idea on the long-run future of the American, or world economy than I do, a better understanding of the sources of risk premium than I do, you're going to make money. Markets reward you for taking risks and for processing information. When we say markets are efficient, it just means that it's a very competitive market for processing information, but the people who do it better than other people, even though it's only half of them, as well as people who get lucky, can make a tremendous amount of money. That's what we're here for.
Ben Felix: All right, so similar to Fama, Professor Cochrane gave us a lot about uncertainty, which is always going to be a theme when we're thinking about the future from the perspective of financial markets. We need to know about future growth and future valuation changes, both of which are big unknowns, even if we take the historical average, it's sensitive to the start date. The advice to use risk management, or basically, just make sure the plan is resilient to lower realized returns, that seems like pretty darn good advice.
Now we have Fama, Goetzmann, Cederburg, and Cochrane, who all talked about looking at historical returns as a guide post, I also want to hear from Professor Brad Cornell, who gave us a different insight in episode 151.
Ben Felix: It actually leads into the last set of questions that we want to ask you just on the expected equity risk premium. Because like you say, looking at histories can be problematic. How do you think investors and financial planners should think about estimating the expected equity risk premium?
Brad Cornell: Well, I think the equity risk premium, I call it the most important number in finance. It's like the speed of light or Planck's constant in physics. The only trouble is that the speed of light and Planck's constant, we know what they are and their constants. The equity risk premium, we have no idea what it is, but it's not constant. I'm working on a popular paper on this right now. And I think the key things that investors have to know is that let's take the current level, the fact that I've just done these calculations, let's take the current level of the S&P 500. It was about 41.50. I don't know where it is at this instance, but let's use 41.50.
There's a lot of hand-wringing over whether that's too high, whether the market's overpriced, and whether I should get out and so forth. Well, it's critically dependent on the equity risk premium. If you take the 41.50 and you go to Aswath, Damodaran site, he has an applied equity risk premium calculation there, you can compute what 41.50 implies for stock returns going forward. And it's about 4% over treasuries. That gives you an expected stock return of 5.5 for the market.
If you're willing to accept that, that's fine. The market's properly priced and all. But you can't play the game as saying, the market's properly priced and I expect to get the same sort of returns I got at Starkly, because again, that's not consistent with the equilibrium. You could even say, the market's going to go up from here, suppose the equity risk premium drops to 3%. It was 3% the implied premium that Damodaran calculates in the '60s.
If it drops to 3%, the market goes to about 5,600 on the S&P. Amazing. But if it did that, you would be looking at stocks only earning 3% over long-term treasury bonds, not much better than corporate bonds. On the other hand, if it goes back to a 6% equity risk premium, which is kind of the recent historical average and what most investors talk about, pension funds tend to use that approximately in their planning. Then the market goes back to about 2,600. The behaviour of the equity risk premium is the fundamental issue that I think investors should be looking at.
Cameron Passmore: How would you take that message to overseas markets? What do you think about global views on equity risk premium?
Brad Cornell: Aswath is putting together a new paper on that, where he presents all that data. I haven't looked at it yet, but overseas you will see higher equity risk premiums. This run-up in stock prices has been focused on the United States and particularly United States tech companies and big tech companies. That's why our equity risk premium is so low. You can rationalize Tesla's price with our projections, Porsche's margins and Toyotas sales, as long as you're willing to accept about a 1.5% equity risk premium.
Ben Felix: Geez. Wow.
Brad Cornell: You'd be bearing all the risk and earning 3.5%.
Ben Felix: Wow. You talked about that in another paper. This is a total divergence from the line of questions that we're thinking about right now, but somewhat related. You talked about how valuable that is to Tesla. The extremely low cost of capital that it has right now and how dangerous that is for other automakers.
Brad Cornell: No question. I mean, if you just reverse engineer it and you compute the effective cost of capital, Tesla, given reasonable projections, then you have this minuscule discount rate. I think that's, Musk has been a genius. People want to invest with Elon Musk and he's able to raise money a lot more cheaply, and he's taken advantage of that recently. He's been issuing stock and so forth. That makes perfect sense. See where GameStop finally found the light. Too bad they couldn't have sold them at 400 for them.
Ben Felix: Yeah. You mentioned with Aswath's site being able to calculate the current implied equity risk premium based on price levels, which implies, I think, predictability in returns. I want to ask a little bit about that. What does the evidence say about stock – the equity risk premium being predictable from measures like that?
Brad Cornell: Well, really, what you mean is the future average return.
Ben Felix: Right. Yes.
Brad Cornell: You compute the implied equity risk premium now and what does it tell you about the future average return? It works as well as any projection in finance, that when prices are very high and the analog that is the implied equity risk premium very low, the next 10-year returns tend to be low. In my view, the next 10 years returns on stocks for that reason are going to be low. I just don't know if they're going to be low because we're going to see 10 years of sideways motion, or we're going to see a sharp drop, which then when you average it in, leads to a low average return.
Cameron Passmore: When you say low, are you saying broad market? Or are you also, for example, looking at your DCF model, or a value model, or perhaps a size-tilted model or some other factor?
Brad Cornell: I was talking there about the overall market. But you can do it on a case-by-case basis. The problem is on a case-by-case basis, you get all these arguments about what the future revenues and profits are going to be. For the market as a whole, those are quite predictable, so you can get a much more accurate measure of the implied equity risk premium.
Ben Felix: In one of your papers, you talked about the fact that it looks like there's statistical evidence of predictability, kind of like what we just talked about with, well, what we just talked about a second ago. But you also talked about how important it is to look at the historical context behind that data to interpret what looks like predictability. Can you talk a little bit about that?
Brad Cornell: Yeah. And this goes back to my early days. My first professorship was at the University of Arizona, and my colleague there was Vernon Smith, who later went on to win the Nobel Prize for his experimental work in financial markets. What Vernon said, and this has always been my beef with behavioural finance is what seems to happen in his experiments is you get the, again a physics analogy is, even empty space can suddenly pop energy into existence because of quantum fluctuations. He said that's the way his experiments would work. Suddenly, the market would kind of go haywire.
It wasn't like the behaviour is said that everyone was always under-reacting, or overreacting, or anchoring, it was suddenly something happened and it went bonkers. That in my view is what the alternative to the efficient market theory is. It's not there's some behavioural deficiency. It's that periodically people do really weird things, but they're virtually entirely unpredictable.
Do you know anyone who predicted the GameStop phenomenon? I mean, that to me was just – and it's exactly what Vernon says can happen, and why and how, even ex-post, it's hard to know. The late Steve Ross, who was one of the giants of financial economics said, “In his view, the biggest failing of our profession wasn't that we couldn't forecast the future” because that depends on getting new news and new news is always random. His problem was, we can't explain the past. Even looking back at these weird things, like the Tesla run-up. Why did Tesla run up 10 times last year? I've studied the company for years. I really don't have a clue.
Ben Felix: Yeah. Again, this is another divergence, but you talked in one of your – the big market delusion paper. You talked about how those phenomena of seemingly crazy, but unpredictable behaviour leading to what we might call ‘expose the bubble.’ That shouldn't be something that we worry about, it's just kind of part of how markets work and it's arguably even important to market function. I thought that was a fascinating point.
Brad Cornell: Yeah. I think Bob Schiller has made this point on numerous occasions, that that's just the way that markets work. These narratives take off, they become viral and they infect people and they then filter through the market. But you just don't know what causes them, or when they're going to stop.
Cameron Passmore: What do you say to someone, professor, who wants the higher expect returns of equities is worried about volatility and high prices, and there is all this randomness? What do you tell people to get them to stay in their seat and kind of chill about the whole thing?
Brad Cornell: I just did a little video for Cornell Capital on this. I’m telling you, you got to know the present value relationship and you got three things there, you've got the price, you've got your forecast of cash flows and you've got the discount rate. Other than saying, “Well, I'm going to be able to sell this stock to a bigger fool and that's how I'm going to make money.” If you believe in the present value relationship, then you're stuck. In this environment, you have to accept lower expected returns on equity. If you're not, if you're not planning for that, you're not being rational. You're praying for a miracle.
Cameron Passmore: Basically, learn to love, or learn to accept volatility and get as much data as you can around the cash flow.
Brad Cornell: Yeah. I think that's the best you can do.
Ben Felix: You mentioned 6% is what some institutions’ pension funds might use as a projected expected equity risk premium. What do you think investors should be using if they're sitting down to do their personal financial plan, thinking about how much they need to save and stuff like that? What do you think people should be using for the equity risk premium today?
Brad Cornell: They should be using Damodaran's implied equity risk premium, or something very close to it. I mean, you don't have to buy into exactly the way that he operationalizes it, but it doesn't make much difference if you tweak it a little bit. We're looking right now at 41.50 at about 4% for equities over the long run going forward.
Ben Felix: For US stocks, right?
Brad Cornell: Yeah. And you'd have to plan. If I'm running a pension fund, uh-oh, I got 4% over equities, I mean, over the T-bond, it’s 5.5. So, 5.5 on equities. High-grade corporate bonds, what? Three? I'm looking at four and a half percent on my portfolio. If I'm using a 7% rate of return, I'm either smoking something or I'm thinking that I can find some sort of alternative assets that are going to give me those returns.
Ben Felix: Okay. From Professor Cornell's suggestion, we would be looking at relying much more heavily on current market prices, rather than using history as a guidepost in estimating expected returns. No matter what we decide to use as an assumption, I don't think that we can underestimate the effects of uncertainty on the realized future outcome. We've already heard about that from multiple people throughout these conversations, but I want to hear from Professor Ken French, who had some really insightful comments on uncertainty back in episode 100.
Cameron Passmore: Such a great episode, too.
Ben Felix: You mentioned earlier that when you're buying stocks, you're buying the rights to future cash flows, or earnings and buying them at a discount based on some level of risk. I guess, the investor would then expect to collect the risk premium. How confident should investors be over the long-term, say, 20, 30 years? How confident should investors be that they're going to collect a positive equity risk premium?
Ken French: Your question's a great one. I work with a guy named Gene Fama. Gene and I have a paper on exactly this question. The experiment we did is, I think it's really interesting. What we did is we took all of the past returns from 1963, in this case, we stopped in 2016, because we wrote the paper in 2017. We have data from 1963 to 2016. We took all of the monthly returns. We just said, okay, if I think about pulling each of the returns for a sample of, let's say I'm working on 20 years. The question I'm trying to answer is over the next 20 years, what's the probability of getting a positive equity premium? And we just say, okay, let's sample from all of the past equity premiums, every – what do I have? 240 months, I'm going to draw 240 of the prior months.
I pull a ball out of this bucket that has all the months in it, look at it and say, "Oh, okay, that's the equity premium for the first month." I put that ball back in, I pull out another one and say, "Oh, there's my equity premium for the second month." I do that 240 times. What's wonderful, I know exactly the distribution of balls in my bucket. I know exactly what the average premium was, and I know what the volatility is, and what the randomness in that bucket is. So, we do that a 100,000 times, we do 20-year samples drawing balls out of the bucket, 240 of them. Calculate the equity premium, and then a 100,000 of those experiments. I get to look at 100,000 of the equity premiums. From a true distribution, I'm absolutely certain of. It's the one we experienced from 1963 to 2016.
It turns out if I'm looking at a 20-year horizon, I get – again, I can't remember the numbers here. Just about 8% of my 100,000 samples produce a negative equity premium. What that says is, I go to my financial advisor, my financial advisor tells me, “You know, there's this positive equity premium.” What that means is the expectation, if you played this game enough, on average you'd have a higher expected return, or a higher average return if you buy equity instead of T-bills. That's what we mean by a positive equity premium. If have enough observations, you have a positive expected return on stocks relative to T-bills.
What Fama and I show is almost 8% of the time, 8% of the universes if we have a 100,000 parallel universes, if we look over the next 20 years, you will not get a positive equity premium. People will look at that and say, "Aha, there is no positive expected equity premium." In fact, there is, but the realization can be quite different from the expectation. The realized return, that's the expected return, plus the unexpected return. The trouble with equity is the unexpected return, as we're living through the coronavirus right now, the unexpected return can totally dominate the expected return. Almost your complete performance over any reasonable short-run period is going to be determined by the unexpected, not the expected return. Even 20 years, 8% of the time you won't get a positive equity premium if the world looks exactly like it did from ’63 to 2016.
Ben Felix: Okay. Finally, to really drive this point of uncertainty home, I want to hear from Professor Lubos Pastor from episode 124 with some more really brilliant and insightful comments on uncertainty.
Ben Felix: Your 2012 paper, are stocks really less volatile in the long run? Now just for some context, our podcast listeners, we talked about leverage a while ago, maybe a year we talked about it for the first time and talked about the Ayres and Nalebuff research on time diversification and how young investors, it’s rational for them to use leverage, because it actually decreases over the long run, your 2012 paper, I think, and I want to ask about that specifically, too, but it throws a wrench in that whole idea of stocks being less risky over longer horizons. How in the paper, how did you arrive at this conclusion that stocks are not really less volatile in the long run, like the conventional wisdom exodus?
Lubos Pastor: Yeah. So again, we have an hour, right? As you mentioned, there's this conventional wisdom that stocks are less volatile at longer investment horizons on a per-year basis. This wisdom is based on historical data. Historically stock volatility at the one-year horizon has been about 17% per year. The 30-year horizon has been more like 12% per year. Historically, indeed, long-horizon investors have faced less volatility per year than short-horizon investors. But this result is based on historical estimates of volatility. What we argue in this paper is that investors making portfolio decisions should be looking into the future. They should care about forward-looking, not backward-looking measures of volatility. Okay, so, that's the key point.
We take the perspective of a forward-looking investor, rather than a backward-looking historian, if you will. A forward-looking investor cares not only about the historical estimates but also about the uncertainty associated with those estimates. That's key. Because that uncertainty drives a wedge between historical estimates based on which conventional wisdom is based on and these forward-looking estimates that we believe matter to investors. Because this uncertainty about parameter estimates is growing with the investment horizon.
In fact, we show that our forward-looking measure of volatility, which matters to investors has two components. First, historical volatility, which conventional wisdom is based on. And second, this uncertainty about the parameters, especially about the mean of the return process, about the trend around which stock prices fluctuate. That second component is increasing with the investment horizon. The first component is decreasing. That's the conventional wisdom. The second component is increasing. When you add them up, you actually get an increasing pattern in forward-looking volatility. We do get long-horizon investors facing more volatility than short-horizon investors.
The intuition is that why is this uncertainty increasing with the investment horizon? Because just think about uncertainty about the mean, okay? If I compute historical volatilities, I'm computing volatility around a known mean. I know that the historical average was let's say, 7% real, I know exactly what I'm computing fluctuations around. But the forward-looking investor is computing fluctuations around an unknown mean, okay. That uncertainty is compounding over time. Think about it this way, if you compound at 4% a year and I compound at 5% a year, there's been a little difference one year out, but there's more and more difference as we go further out. And you see how, if we go 20 years out, 30 years out, there's going to be a gigantic difference.
That's why this uncertainty about the parameters matters, especially at the long horizon. As an investor looking to buy whole stocks over a long period of time, I actually face more uncertainty than I had thought based on these historical estimates.
Cameron Passmore: What are the implications then for someone managing their retirement account that has a long-term horizon? What then this means for their asset allocation?
Lubos Pastor: What I've learned from this as an investor is that I should slightly reduce my stock allocation. Stocks are simply more risky in the long run than I had thought before I wrote this paper. It doesn't mean that I should, for example, the target date funds are incorrect. It just means that stocks are riskier in the long run than we had thought.
Take target date funds, because they are so popular nowadays, right? Young people have more invested in stocks than old people. There are two popular justifications for target date funds. One is based on human capital. We can talk about that. The other is based on mean reversion in returns. It's the idea that over the long run, stocks are less volatile than over the short term. I like the human capital argument. I don't like the mean reversion argument. I think that mean reversion evidence is swamped by the uncertainty evidence that we document in our paper. I still think it makes sense for the young to invest heavily in stocks. I think that makes perfect sense, but they should do it for the human capital reason, not for the mean reversion reason that is often put forth as well.
Ben Felix: All right, so those were some incredible clips from some of the brightest minds in financial economics, helping us think about, how to think about expected returns, how to think about the future through the lens of finance. We don't have the answer for uncertainty, which is, by definition, very difficult to account for. It is uncertain. We do have a methodology that blends together historical data, the effects of valuation changes on historical data, and the information current market prices to estimate expected returns.
We have a fairly new document up on our website. We can link to that in the show notes that detail our methodology. We had this thing where we kept iterating our methodology, just small improvements each time we released a new version of our expected returns document, which we update twice a year. We decided to consolidate all of those small methodology changes into a single methodology document, which will be updated going forward, and then the expected returns updates just have the data. Anyway, so that document is now available on our website.
As a very brief overview, our methodology has two components. We've got the equilibrium cost of capital, as we call it, and we've got the market-based expected return. The equilibrium cost of capital, we use the DMS World Index from 1900 through to the most recent years, so currently 2022. We don't just take that historical average, though. We take the historical average less the portion of the historical return explained by evaluation changes. We're penalizing the historical return for the portion that is explained by rising valuations over the full period. It's like, world valuations have increased a bit from 1900 to 2022. We don't count on that valuation change happening again. We remove that from the historical portion of the return.
Then for the market-based portion, we use the expected return implied by the Shiller CAPE for stocks and the current yield for bonds. we weigh those components differently for stocks and bonds based on how well the market-based metrics predict future returns. We did regressions to look at that. The actual predictive power gets pretty fuzzy, depending on the time period in the country, and even the way statistical significance is defined. Since we're predicting the future anyway, we're not too fast on specifics. Based on the regression work that we had done, we basically found that without even giving a point estimate on the numbers that future bond returns are much more sensitive to the current yield to maturity than future stock returns are to the current Shiller CAPE, which is what we use for stock valuations.
Based on that, and again, recognizing that this part gets super fuzzy, we weight the market-based return in our estimate at 75% for bonds, so 75% of the expected return is based on the current yield to maturity, 25% is based on historical return, and then for stocks, it's 25% based on the current earnings yield and 75% based on the valuation-adjusted historical return.
Again, we don't think that's super scientific. I mean, as much as we could be to come up with a reasonable number, but you heard some of the comments from the past guests that a lot of this is pretty fuzzy. Maybe 4%, 5%. We even recognize the fact that people have poked fun at me for this before, that we have our expected return figure to two decimal places. That's probably not necessary either. We could round to the nearest percentage probably, but I don't know. We have a methodology, so we update it. It's all quantitative, and we get our number out, and we use that number, and we update it twice a year.
Anyway, hopefully between those comments and my brief explanation of our methodology and for further reading the actual methodology document, that gives people a lot to think about for expected returns.
Cameron Passmore: Love it. Well done. Nice and clear. I think this will be a frequently shared segment. Cool. All right. Let's go on to a quick recap of a past episode. This time we're going to look at episode 102 with Dr. Brian Portnoy. A bit of a backstory, which I seem to be doing more and more now. I went to the, as listeners might remember, I went to the WealthStack Conference back in 2019 in Scottsdale, Arizona, and Brian was one of the presenters. I thought he was great.
At dinner that night, I happened to meet him briefly. He was at a table near our table. Someone at our table knew Brian. I very, very briefly met him. Shortly after, I just reached out, because that's what I do. Since then, Brian has become a friend of ours, has been on the podcast a couple of times, as well as a pretty close advisor to the team here. Brian's a good guy and a special guy, and we appreciate getting to know him. Let's get going.
Brian Portnoy joined us for episode 102 back in June of 2020. Brian authored the book, The Geometry of Wealth: How to Shape a Life of Money and Meaning. This is a book about having a healthy relationship with money, with the objective of funded contentment. Here, it tickles that there are three components of funding contentment, which is what is our purpose, what are our priorities and goals, and what are our money decisions in areas of saving, spending, ensuring and giving? In summary, purpose, priorities and decisions.
Brian also discussed the shape of the financial industry today, which in his opinion is still too much. How do I beat the markets and not enough? Did I reach my goals? He also talked about the impact of recent crises, such as the 08 financial crisis and COVID, and how even though the world has been through many events in history, each one of them is a first for each of us, and this is a challenge for humans as we strive for a sound economic future.
Lastly, we talked about his experience analyzing hedge funds for a living and whether it's reasonable to expect market-beating returns from hedge funds, or actively manage mutual funds. I think you know what his answer is, and that was Brian Portnoy, episode 102. Okay, let's go to our book review this week, and we're joined by our colleague, Matt Gour.
Ben Felix: I got to say before we go to – it's hard to overstate the impact that Brian ended up having on us. It's just funny to think back to your backstory, you had this chance meeting through a conference, and that led to how many podcast episodes on money and happiness and all that stuff, and that whole redirection of our content to cover that stuff, and then we've done a ton of work with Brian with our team, and that ‘Finding and Funding a Good Life’ paper that was downloaded however many thousands of times off of our website, that was largely a reflection of work that we did with Brian, at least as a kicking off point for it.
Cameron Passmore: I hadn't thought about that. He really was, I guess, the gateway to all of this.
Ben Felix: It was a pivotal moment when we had him on our podcast, and when we started talking to Brian offline about all of the work that he'd done on these topics.
Cameron Passmore: In hindsight, that reach-out was when he was establishing his company in this consulting space. I think we were one of his first clients, which is cool. As he said, he was creating the product. He used the analogy that we were at his kitchen table watching him create this product in real-time. He was testing out different recipes on us and be like, “Yes, do you like that?” It was all really fascinating. Yeah, Brian's a very good guy. That's a good point. All right. Let's head over to Matt on the book review.
Cameron Passmore: For this week's book review, I reached out to our team to see if anyone had a book they'd recommend, then join us to talk about it. This week we're joined by our long-time colleague, Matt Gour. Matt, it's good to have you on the podcast.
Matt Gour: Glad to be here.
Cameron Passmore: How many years we've all worked together now?
Matt Gour: Coming up on eight years this November.
Cameron Passmore: Unbelievable. Ben, you're 11, 10?
Ben Felix: No. Coming up on 10.
Cameron Passmore: Coming up on 10. It's crazy. Matt advises many of our clients that have some of the more complicated financial situations. I think it's fair to say, Matt, you've been instrumental in developing a lot of the fantastic team members that have joined us over the years. It's great to have you join us.
Matt Gour: Appreciate that.
Cameron Passmore: The book you chose is called The Power of Moments: Why Certain Experiences Have Extraordinary Impact. This is written by Chip and Dan Heath. We reviewed the book Making Numbers Count that was written by Chip Heath in episode 189. We also referred to their book, Decisive, in episodes 38 and 92. Chip is a Stanford Business School grad and Dan is a Harvard MBA grad. They've both been very successful authors for many years. It's a pretty cool book, actually.
While certain experiences have an extraordinary impact is exactly that. It's about moments in our lives that really stand out. This book dives into what are the elements of these moments in how do we recall them. Matt, why did you choose this book?
Matt Gour: Yeah. Initially, I stumbled upon the book during a study group that I'm involved in. It was a large part of their onboarding process. It's actually a mandatory read for all their new team members. Many of the other members had read the book. I took the hint that this is a good book to dive into. When I was reading into it, the impact for me was just, it made me appreciate how powerful these moments are. Sometimes we're so obsessed with process and life in general. When you take a second to step back and look, the book really makes you realize how these moments in hindsight really stand out. I also found it broadly applicable for both our professional lives and our personal lives. It was a very well-rounded book and very applicable.
Cameron Passmore: I gave a brief description of someone asking what the book's about. How do you describe it?
Matt Gour: Yeah, very similar to what you said. While the book is not a specific guide on how to create high-impact moments, it outlines and dives into elements that make impactful moments and helps us realize when these moments are occurring. It's about being deliberate in your awareness of the potential for these moments and the appreciation that these moments are far more important than the process overall.
Therefore, take the time in your business life to be aware when these moments can occur and ensure that you nail them for the benefit of everyone. Your customers or clients will really appreciate it. You'll also get something out of it as well.
Cameron Passmore: Do any examples of moments come to mind?
Matt Gour: For me, personally, the book maybe – there were a lot of points of reflection when I was reading the book. There's a small moment for me in my personal life. I'm saying this to highlight how somewhat meaningless a moment can be in the moment, but when you look back on it, it's very impactful. For me, it was in my competitive hockey career growing up. I had a coach that was really hard on us. One day, he took a moment to ask how my skiing was going. I had joined our high school ski racing team. He took that second to ask where no one really seemed interested in that, other than me, because we're obviously a hockey team. That moment really landed with me. It felt like it elevated me and made me feel proud in my skiing. That's just a really small example of these moments.
Cameron Passmore: When you think back on your hockey career, that's one moment out of that career, half joking here. That's one moment that actually stands out from that period.
Matt Gour: Yeah. It's wild to think of that one coach. We've had many coaches that had a great impact on our athletic careers, right? That moment where he took that moment to be more personal and drawn in something from my personal life into our hockey team really stood out to me for whatever reason, right?
Cameron Passmore: I find it interesting. I think back to I worked many years in a butcher shop in small town, in Quebec, I can remember certain moments, certain experiences with customers that stand out, even though I worked there for eight or 10 years. Just funny how those eight or 10 years and those hundreds of days that I worked there, you think about a handful of episodes that stand out, right? Just funny how the brain packages up thousands of hours into these handfuls of moments when you think back. I bet you think back on your own childhood, for example, and there's likely a handful of common moments.
I remember that you've heard me talk about my compound interest story, or collecting worms, or when you learn how to drive, or I think of in high school, we went a certain event skiing that really stand out. Going to JP, going down a certain run on JP. It's just funny how you get all these nice skied hundreds of days, we get these handful of moments that just jump out. It's so interesting to me. Matt, you're going to talk about something I found interesting in the book, which is the peak-end rule.
Matt Gour: Absolutely. The peak-end rule is when people assess an experience, they tend to forget or ignore the length and that phenomenon is called the duration effect. Instead, we tend to rate the experience based on two key moments, which is either the best or worst moment within the experience and the ending. Psychologists refer to that as the peak-end rule. A very common example of that is when people go travelling.
People ask, “Oh, how was your trip?” I think of an experience that I had last year, or the year before on a ski trip. It was a week-long of backcountry skiing. I always talk about this one run that we did roughly midweek. It was probably the craziest train I've ever been on, the best snow conditions we've ever had. That's all I can think about, all I can talk about. In the end, we get helicoptered into this remote hut. On the way out, I had the opportunity to sit in the front of the helicopter, which I'd never ever done. Those are the two points that I always bring up.
Now, what's left out from that memory is the fact that we all got sick during the trip, COVID in particular. It was very challenging to actually perform during this ski trip, but that memory of being very sick doesn't even come into play when I recount that experience.
Cameron Passmore: The book talked about four specific elements that can create a defining moment. It's a bit of a tool that people can use to try to create them, especially in a business setting. Maybe go through those four elements.
Matt Gour: Absolutely. It makes a pretty helpful acronym, EPIC. The purpose is not to create these epic experiences. That's just a convenient way to rearrange the four elements. The four are elevation, pride, insight, and connection. In elevation, these are moments that elevate or rise above routine. An example that was in the book was a young child who forgets his stuffed giraffe at a hotel. Parents call the hotel. They find it. Typically, that would just be shipped back to their house. What the hotel did was actually take the giraffe and take photos with the giraffe throughout the operation of the hotel and emailed them to the family while the giraffe was in transit. They just took something very routine, returning the lost item, and elevated that and made a very memorable experience.
Pride, that's a moment that commemorates other people's achievements. Recognizing others, a very small effort, like my hockey coach did, it multiplies meaningful milestones, and the last is helping practice courage by preloading responses and walking through scenarios. On the multiplying meaningful milestones, the example in the book is this running program called Couch to 5K. All that simply does is takes the goal of running a 5-kilometer race and breaking it down into little bite-sized chunks. Walking 5K, walking and jogging one minute on, one minute off. Very similar to Fitbit users now, or Apple users with the rings. As you complete those, there is some recognition that you're achieving smaller goals towards the goal.
Insight is a moment that delivers realizations and transformations. There are two strategies for creating insight. The first is causing people to trip over the truth. If you know someone is overeating as an example, just simply asking questions about their eating patterns can help them realize like, “Oh, this is actually detrimental and not helping me reach my goal of losing weight.” The other is stretching for insight. An example in the book is someone that was very good at baking. They were excellent at baking cakes. All of their friends said, “You need to have your own bakery.” They took a risk and started their own bakery.
They didn't know if they were going to like it or not, but they stretched and said, “I'm going to try this.” After a year, it didn't work out, but at least they have that knowledge now that they can do it, or they could do it but didn't like doing it. The final is connection. These are moments that bond us together. Groups unite when they struggle toward a meaningful goal. It often comes at a synchronized moment. I think of our experience at PWL, where we would do off-sites together. Go find a location outside of the office and tackle a tough topic, or challenge that we're having. It just breaks that script and gets everyone together on common terms.
Cameron Passmore: Another part that was interesting in the book was the difference between organizational or company moments and personal moments. You and I talked about this earlier today. Why don't you share some insights there?
Matt Gour: When we think of moments, we're very aware of these transitionary milestone periods, and the third type of experience is a hit. In a corporate setting, we need to work towards obviously, mitigating hits, or service failures in our various business models. If that does occur, there's actually an opportunity to make that hit the peak. I had an experience recently when I was trying to return something at a big box store, their system was down. Instead of oh, come back later and see if it will work, the employee actually made a point of, calling me back, letting me know it was all ready to go. Gave me a variety of options to avoid having to come back into the store. In the end, I didn't go back to the store, but it was a negative moment where I just wanted to simply return something, but they made it a positive one by going above and beyond the bare minimum and really helping me out.
Cameron Passmore: Yeah. The other example I gave, too, is a hotel, I think in California that had a popsicle hotline. But if the service wasn't good, if the lobby was a mess, or the service was lousy, you can't go and have these surprise moments, which they talked about the benefit of, if your basics and your foundation isn't handled properly, right? It is different in a corporate setting like that.
Matt Gour: Absolutely. a lot of this seems like very common sense. One example was when you're leasing a car, and someone passes away while they are currently leasing a car. It's typically an obligation of the estate to continue making those lease payments and fulfilling that obligation. Mercedes, however, do something very different, where they –a lessor passes away, will actually send a condolence letter to the family and offer them the opportunity to just return the vehicle with no continued payments, or anything like that, which seems very, very common sense. It's very rare in their industry, especially amongst other automotive manufacturers.
Cameron Passmore: Mentioning surprises that there's a stat in there. They looked at hotel reviews on TripAdvisor and they found that when guests have a – what did they call it? A delightful surprise and astonishing 94% of them expressed an unconditional willingness to recommend the hotel compared with only 60% of guests who were very satisfied. The power of that surprise, be it a popsicle hotline, causes much greater reviews.
Matt Gour: Absolutely. Another thing that they mentioned in the book was a lot of companies tend to focus on their poor reviews, so the ones and threes, and how to fix those reviews and avoid any of those really, really harsh upsets. They suggest that really time should be spent and effort should be spent on getting people that are in the sixes up to an eight or above. I found that pretty interesting that typically look at the worst-case scenario and try to avoid any ones, or twos, or threes, but it's really getting those mid-pack neutral people up to a positive state will be far more impactful for the business.
Cameron Passmore: What can you do to be deliberate about creating defining moments?
Matt Gour: Yeah. I think the biggest thing is setting aside time and being very thoughtful with handling moments. It's very easy to get caught up in processes and trying to optimize processes. It's a good practice, I think every once in a while to step back for your business and evaluate it critically. In the context of moments, breaking apart your – gave a process, like onboarding a client, or client acquisition and seeing, okay, where is that milestone moment possibly? Where is that area that we can elevate the experience and maybe it's filling up documentation? It's not the most fun thing. Those are areas where you can pick that apart and give some further thought into how to make that a more beneficial experience for the client.
Cameron Passmore: All right, what was your biggest takeaway?
Matt Gour: Biggest takeaway, there's a lot of takeaways in this book. Thoroughly enjoyed it. For me, I think it debunked. I had this notion from some prior books that to have a client experience, it had to be this epic, very grandiose, large production, possibly large cost to have any impact. I remember I don't know what book it was, but it was a wealth management firm that made their office. This is like a theatre. It was very grandiose. I thought, okay, well, how do you think of that? It has to be this huge thing, where in reality, that's completely incorrect. It could be something extremely, extremely small to have a huge impact.
That was a big thing, but also, there's a moment in this and it's not necessarily related to our professional lives. It was more on the personal side. It was the idea of a gratitude visit. This is a concept that was developed by Martin Seligman, and where you meet face to face with someone who did something in the past that changed your life and you don't feel like you've properly thanked them. In this instance, it was someone writing a gratitude letter for their mom. You write the letter, you met with his mom and went over, and read the letter to her and this process obviously has a huge impact on the person receiving the thank you, but also an impact on the person writing the letter and delivering the gratitude visit that lasts over a month.
It seems highly impactful and I hope one day that I'll actually be able to execute on this, but it's a process that encompasses all four elements of a defining moment and that's part of why the benefit lasts for a month long.
Cameron Passmore: It's really interesting. I'm guessing the bottom line, you would recommend this book.
Matt Gour: Absolutely. It's like I said, broadly applicable for both personal and professional use, regardless of whatever industry you're working in. There are lots of inspiring examples. Like I said, it's not a step-by-step guide of do one, two, or three, but the examples and ways they frame things in the book really get you thinking in how you can implement this into your everyday life and in your professional career.
Cameron Passmore: Yeah. I'd also recommend it. I'm a big fan of Chip and Dan Heath's books and I agree with you. That was your review of The Power of Moments. Matt, thanks for coming on.
Matt Gour: Thanks for having me.
Ben Felix: Thanks, Matt.
Cameron Passmore: I think the aftershow is going to be quick. This week is my guess. One thing I wanted to recommend, I'm going to do a book review on this shortly, is Seth Godin released a new book. It's incredible in my opinion. It's called The Song of Significance. He was on a podcast that I like, which is called Conversations with Tyler, and it was an incredible interview. Tyler asked much like you, Ben, very sharp, very short questions. It was a very punchy, quick interview. Very different than Seth was all small with Tim Ferriss in a much longer conversation type. For those who listen to Tim Ferriss, they know that. With Tyler, it's very short and crisp.
He talked about the impact that marketing can have and how in a consumer society, we're all looking for products that help tell our story. I remember you and I talked about cars and cars are part of your funding and finding a good life. I thought Seth's answer was brilliant. He said, “No matter what car you drive, whether it's a nice new car, whether it's an old junker,” he says, “Your car is telling your story. Whether you like it or not.” You might say it's just, you get from point A to point B, that's part of your story. It might be an old rust bucket, that's part of your story.
We talked about signals and other books in the past. I thought he did a great job of explaining that. A phenomenal interview, a phenomenal book. Again, I'll do a review of the book in a few weeks. What have you been up to lately? I know you did some travel.
Ben Felix: Yeah, I'm on the FP Canada Projection Assumption Guidelines Committee. I had a couple of new members to the committee for this year, and I was one of them. I was in Toronto for that, which was great. PWL producers are expected returns methodology, which of course we talked about in this episode. FP Canada has a different methodology they've been doing for a while. I was happy to share our approach and how it compares to what FP Canada does. I think it'll be a very productive committee to be engaged with. That was good.
I noticed today that Angelica started advertising the CE credit program. That's being promoted a bit more. If you're a listener, well, if you're here, you're a listener. If you need CE credits, you can now do a quick questionnaire and get some credits. I saw our friend Jason posted on Twitter this afternoon that it'll probably get a lot busier in that store come December.
Ben Felix: Well, and that's the thing that people do their CE credits typically pretty last minute. Yeah, it'll be interesting because we're in – I mean, this is pretty inside baseball, but in Canada, there's a two-year cycle for continuing education. We're at the end of a cycle.
Cameron Passmore: The cycle’s calendar year. Yeah.
Ben Felix: Yeah, everyone registered in that category is going to have to do all of their required credits by the end of this calendar year. Presumably, people will be looking for credits.
Cameron Passmore: I think we have to do the questions, too, if we need credits, correct? We don't get credit for producing.
Ben Felix: Oh, well, we have to do it.
Cameron Passmore: Yeah. Update on some meetups. We're doing a live recording at Future Proof Festival in Huntington Beach in September. The time has been confirmed. It's Tuesday morning, September 12th. We're in the same time slot as Michael Kitces. Sorry, Michael, but we might be drawing some of your crowd away from you since we have Hal Hershfield joining us. Anyways, I feel bad for Michael, but he'll be okay.
We have a few people interested in a breakfast. We're still coordinating that. Toronto meetup evening has been moved to Thursday, the 21st. Thursday, the 21st from Wednesday the 20th. I think we have nine people coming out to that, which will be fun. We're doing a live recording of the CFA Toronto event on the 21st. If you're interested in joining us at any of these, you can email info@rationalreminder.ca. As I mentioned a couple of times, I'm doing a short presentation at the Ottawa Book Expo on July 15th. Tickets are available at ottawabookexpo.ca.
We're running out of Talking Sense cards, Ben. I think Angelica is working on an arrangement to get more made, but we're not certain. If you're thinking of getting cards, you might want to order them quickly. Anything else you want to mention?
Ben Felix: Actually, today, the day that we're recording this, which is a bit in advance of when the episode will be released, I recorded a conversation with TD Direct Investing. That's the second time I've been on their show. It's fun. I like the guys that run it. This time, we did an episode on, what do they call it? How to figure out a safe withdrawal rate for retirement. We basically talked about the 4% rule stuff. We talked about retirement planning in general. We talked a bit about expected returns, kind of like we talked about today, but not in as much detail. We talked about the challenges of retirement planning. We talked about the problems with the 4% rule. Then we also talked about the problems with constant dollar withdrawal rates and how flexible spending and flexible spending rules can improve retirement planning a little bit.
Of course, emphasizing that all of those are simple decision rules and more comprehensive financial planning is maybe better. If that's not available, some of these decision rules can be useful. Anyway, I think it was a pretty good conversation. They'll edit that down. Then the way the TD does these events is they'll play the edited version of that conversation to a live audience. Then after that plays, there's a live Q&A. Then they'll post the edited interview on their YouTube channel. The live Q&A does not get posted anywhere. If anybody wants to participate in the live Q&A, you would have to sign up. Unfortunately, I don't know where. TD Direct Investing.
Cameron Passmore: But your comments are available publicly afterwards. That's great.
Ben Felix: Yeah, the pre-recorded remarks are all – those are all available. I’ll also mention that I'm going to be very sparse in the details here. I'm working on a project with a collaborator that is focused on investing in personal finance for Canadian professionals. That's with a focus on generally, people with higher incomes, though not exclusively. Lots of information for people with corporations and all that stuff. There was a gap in, because this Rational Reminder audience grew globally in a way that we just didn't expect it to, we got a lot of feedback about even in the introduction, sensible investing and financial decision-making for Canadians used to be our intro. Now it's from two Canadians. Anyway, there was a gap in Canadian-specific content.
I found someone who's very passionate about that. We're going to do – it's an audio-video project, probably written content in there, too. We've made a decent amount of progress and it's going to be a pretty cool product when it's all done.
Cameron Passmore: That was cryptic enough, but it was good. Something to look forward to. A bit of a tease factor going on here. Yeah, I think it's going to be great.
Ben Felix: Yeah, I'm excited about it.
Cameron Passmore: All right, anything else?
Ben Felix: I don't think so. That's good.
Cameron Passmore: I think it's good. All right. Thanks, everybody, for listening.
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Books From Today’s Episode:
The Geometry of Wealth: How to shape a life of money and meaning — https://amzn.to/46qpjl5
The Power of Moments: Why Certain Experiences Have Extraordinary Impact — https://amzn.to/3pmYJJb
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Episode 38: Feelings in the Decision Making Process — https://rationalreminder.ca/podcast/38
Episode 92: Dr. Moira Somers and Dave Goetsch — https://rationalreminder.ca/podcast/92
Episode 100: Professor Kenneth French — https://rationalreminder.ca/podcast/100
Episode 102: Dr. Brian Portnoy — https://rationalreminder.ca/podcast/102
Episode 124: Professor Lubos Pastor — https://rationalreminder.ca/podcast/124
Episode 151: Professor Brad Cornell — https://rationalreminder.ca/podcast/151
Episode 169: Professor John Cochrane — https://rationalreminder.ca/podcast/169
Episode 189: Regret (and How to Read More w/ Neil Pasricha) — https://rationalreminder.ca/podcast/189
Episode 200: Professor Eugene Fama — https://rationalreminder.ca/podcast/200
Episode 224: Professor Scott Cederburg — https://rationalreminder.ca/podcast/224
Episode 248: Professor William Goetzmann — https://rationalreminder.ca/podcast/248