Index vs Factor Investing and the Impact on Retirement Savings ft. Mathieu Pellerin (EP.110)

0:28We all need to make smart decisions with our money. Fund Advisors, where he conducts research on goals-based investing with a focus on retirement. Matthew is a regular speaker at industry events, and his research has been featured all over the major media. But today, we're going to be discussing his recently published research paper on the impact of factor investing on retirement outcomes. As always, you'll find links to all the resources discussed in the show notes at thelongterminvestor.com. And with that, here is my conversation with Matthew Pellerin. Matthew Pellerin, welcome to The Long-Term Investor.

1:07Thank you, Peter. Happy to be here. We're going to talk a little bit about your latest research that explores the benefits of core equity investing for retirement outcomes. And this research compares a market portfolio and a systematic portfolio with moderate emphasis on size, value, and profitability premiums. And I'm curious just to start us off, Matthew, what caused you to do this research in the first place? As is often the case in research, the inspiration is quite disconnected from the actual finished product. So there's a bit of a story there. So initially, I was attending a conference at the Georgetown Center for Retirement Initiatives.

1:45And one of the presentations was about the benefits of including private assets and defined contribution plans. And again, one of the presenters, what he had in his slides were basically simulations showing the benefits, which relied on capital market assumptions. And eventually, the presenter comes to the right slide showing his assumptions. And what just jumped out at me is really the assumptions for private equity were very close to that of small cap value in terms of the returns, in terms of volatility. And I had seen the Rational Reminder podcast with William Bengen, the inventor of the 4 % rule.

2:21He had played around with putting a bit of small cap value or small cap into the equity allocation, see if that allowed for a higher withdrawal rate. So I just thought maybe I should look at what's the impact of having, as you mentioned in the introduction, a moderate amount of tilting. Just like in the presentation, it was based, I think, on 10 or 20 percent in private assets, so kind of a limited number, and that showed a benefit. So that was the inspiration. But one of the things that we found in recent research, one of the papers that my boss and a few others co-authored, is that if you're going to have a moderate amount of exposure to size, value, and prof, instead of having a bunch of component portfolios, basically having a small cap and a large cap.

3:01And when the small cap becomes large, you sell it out of the small portfolio and you buy it in the large, which just adds extra transaction costs, extra turnover. You can have what we call instead a core equity solution that basically is fully integrated, targets all the premiums in a systematic balanced way. And that just yields a better outcome in general in terms of giving you more excess return with less tracking error, less turnover and all of that. So instead of looking at a bunch of components portfolio, I said, let's look at a core portfolio versus what people typically default to, which is a broad market index, something that tracks like S &P 500, Russell 3, et cetera.

3:38And also, one of the reasons I looked at that comparison was in the defined contribution world, which is where I spend most of my time, there's, again, a lot of preference for solutions with a low tracking error. And I thought it was just a very good comparison to set up the index funds that are in target date funds and managed accounts or just as standalone options. Just compare them directly to a systematic approach that has a moderate amount of tracking error. So something that people are more likely to stick with. I think we'll come back to that later in the podcast. So that was basically the impetus for this research.

4:12Now, Matthew, just before we start diving into some more of the details of the research, For those who are listening that are less familiar with the different factors, size, value, profitability, do you mind just at a high level defining those and how you think about those when you're going into measure and do research? Absolutely. So first of all, there's hundreds of factors out there leading to the rise of the so-called factor zoo. So you need some sort of filter. First thing, you just need some way to discriminate between those premiums and see which are based on data mining, won't hold up out of sample, and which are based on genuine differences in expected returns.

4:50So what we look for at dimensional big picture for the factors that we use, not just in equities, but in fixed income as well. We want something that makes sense before you even look at the data. So a theoretical rationale. You want something that holds up in multiple samples. So maybe you go back in the past, the premium still holds up or it holds across regions. If you find an initial finding in the US, you want that thing to work as well in developed XUS and EM. And also we want these things to be robust, meaning that if you do value, value refers to the propensity of stocks with a low relative price to outperform stocks with a high relative price.

5:29So cheap beats expensive. And that premium is very robust in the sense that we use price to book at Dimensional. There's a number of reasons for that. But the truth is, if you use price to earnings, price to cash flow, price to sales, it's not going to be sensitive to the way you define it. You'll still get a spread in returns between cheap stocks and expensive stocks. So once you have that theoretical foundation, the empirical research, and the robustness, then that leads to the set of premiums that we use. So in the equity front, which is what this paper is really focused about, we use a value, which I've already mentioned, cheap beats expensive.

6:02We use profitability, which refers to the tendency of firms with high operating profits. So you're not looking at net earnings all the way to the bottom of the income statement, you're looking further up. So basically sales minus cost of goods sold. And what we find is that firms that have high operating profits relative to their book assets or book equity, they tend to outperform unprofitable firm, especially when you pair that with value because profitable firms tend to have a bit of a growth tilt. But keeping the price of a firm constant, if it's more profitable, it tends to have higher expected returns.

6:38And the last one, size, just refers to the tendency of firms with a smaller market capitalization to have higher expected returns in the long run than large firms. So these three things together, they're the key drivers that we're going to look at as we discuss this research. And they're the main ones that we use at Dimensional. We use others, but the kind of long-term drivers of the asset allocation are these three factors. And so just to repeat back some things to you really confirm before we dive in, the research is comparing what we'll call a market portfolio, because in a lot of 401k plans, retirement plans, you can own the total U.S.

7:15stock market, for example. Whereas when you're referring to core equity investing, you're still talking about being broadly diversified across the entire investment universe, whether that's U.S. stocks or otherwise. But the weighting isn't exclusively based on market capitalization. like an index. So for those listening, an index fund, the bigger the company, the bigger the weight it's going to hold, whereas this core equity investing takes into account the size, the relative cheapness or expensiveness, and the relative profitability of companies. And so, Matthew, I guess maybe this is overly obvious, but why did you feel that this research was important in the first place?

7:55Actually, this paper is interesting because to me, it's about taking something that we know to be true on one scale and putting it on an other scale. So we know that this core portfolio, if you look at it on the scale of annual returns, well, it's going to outperform. And the portfolio we looked at over the last 100 years, the index outperformed the broad market by about 1 % a year. And putting that on the scale of dollar outcomes, So what does it mean for somebody that holds a diversified asset allocation? So what we looked at in the paper is a full glide path, meaning that you have an asset allocation where you start 100 % invested in equities when you're young.

8:38And by the time you're middle-aged, you start to divest out of equities until you reach a 50-50 allocation between stocks and bonds at retirement. So when we compare market to core, we're really comparing a full asset allocation in both cases, but we're just moving one piece of it at the time, which is the equity sleeve. So the idea, and again, the impetus for that is it's basically a stylized version of a target date funds and also a stylized versions of what many advisors do with their clients, which is have them de-risk as they approach retirement. So I think why it's important is just to be conscious of how the small difference in returns, not small, but 1 % doesn't sound like a whole lot when you hear about it at first.

9:17But when you think of it in terms of the accumulated assets that you can be expected to enter retirement with, which are 20 % higher. So if you're expecting with a market portfolio to enter with 1 million, now it's 1 million 2, that's an extra 200K. Now, for some reason, I just feel like it has a punchiness to it that maybe just comparing returns doesn't. And I think it's important for people to be aware of that because the flip side of that statement is that if I invest in an index, what I can be expected to give up on average is that 200K. So suddenly you feel with the index, I'm doing the default thing, I'm doing the safe thing, the kind of most obvious thing, but actually you're giving up on something that could be a very good substitute and do a better job in the long run.

10:07So I think it was to highlight really what this means in terms of financial outcomes that this paper, I think, is interesting. Well, and as you start to dig into some of those outcomes, I'll remind listeners and viewers that I will link to both the paper that's on SSRN right now, as well as a blog post at Dimensional that summarizes, well, the blog post summarizes the finding, the paper is the whole paper. But I'll go ahead and link to those in the show notes at thelongterminvestor.com. And Matthew, I'd love for you, since you've already started a little bit, to dig deeper into what did you find in this research?

10:42So really, the finding that we emphasize the most is the one I mentioned with the accumulated assets. So if you look at an investor who's 25, they just make regular contribution to an account, they follow this sort of balanced glide path. And the only thing that you're comparing is the difference between market index and core in the equity sleeve, you get that 20 % outcome. We looked at it with equal contributions. We also looked at it with rising contributions. So maybe when you're 25, you have less income, you save less. But by the time you reach 55, 60, you're kind of in catch-up mode and you end up saving more.

11:15So even with that setup, the result holds as well. It's closer to 15 % in that case. But what I want to emphasize is as long as it's kind of a long-run consistent thing, under most reasonable assumptions, you would expect a similar finding to hold that you will get a pretty substantial increase in the assets that you bring with yourself at retirement. Now, the other finding is irrespective of the assets that you enter retirement with, there's also benefits to sustaining spending. And this one I think is more interesting because finding out that something with higher expected returns, you compound that over a long horizon, it has a big impact on assets.

11:52I think it's fairly intuitive. The number, I think, is still pretty powerful. But what's less obvious is when you have something where you have a liability that enters the mix, you have cash flows going out. And the main finding there is suppose you have two investors entering retirement. They have a 50-50 % mix of assets, stocks and bonds. Again, you're comparing market to core. And they spend according to a 4 % rule. So they're just going to spend 4 % of their initial assets adjusted for inflation every year. We use that not because we think it's the most realistic or that you cannot improve upon.

12:24It's just to have a very simple benchmark to make the point. And what we find is that when you look at the historical distribution of returns, there is a very low failure rate, both under market and core. There's still a slight improvement with the core, something like the chance of running out of assets over the next 30 years falls from 5 % to something like 2.5. And that's normal because the 4 % rule was initially designed so that in historical back tests, 4 % was the highest rate of spending that would lead you to not have a failure with a 50-50 portfolio. So that's kind of intuitive that we find that.

12:57What's interesting is if we look at a more conservative distribution for return, So we take the historical sample for the last 100 years, but we adjust the equity premium downward. So what if stock returns overall are lower in the long run? And there what happens is the failure rate is higher with the market allocation, closer to 20%. And the failure rate with core drops by seven percentage points all the way to 13%. So there, I think it just shows that there's a benefit to sustaining spending as well, which maybe is underappreciated. And I think one of the important things there is, you know, when you compare a core, it's not a free lunch.

13:33You take tracking error relative to the benchmark, you have volatility that's just slightly higher. So one of the questions that people may ask is, when I enter retirement, what about sequence of returns risk? What if I know value profiles start underperforming at the same time? What's going to happen then? And I think running those simulations establishes that even when you take all these effects into account, the higher expected return really ends up dominating. And in the paper, we actually look at, because the paper is based on 100 ,000 simulated paths, so 100 ,000 simulated 30-year retirement.

14:06And something we did just to reinforce that point is look at each of the simulations and classify them in four buckets. Either if you're holding the market and the core, you would have failed in both situations. You would have succeeded in sustaining your spending in both situations. But what's interesting is the two other pairs. There's some scenarios in which holding a kind of index fund, you could have sustained your spending, but you would have failed with core and vice versa. And what we find when we compare the numbers, the frequencies, you're 100 times more likely to fail to not sustain your spending with a market allocation relative to core.

14:43So I think it really drives the point home that even if you focus on the scenarios in which you would have regretted your decision to go in core at the beginning of retirement versus market, the probability of that is small in absolute terms. And it's also very tiny compared to the more likely scenario, which is that the lower expected returns are going to hurt you. Then the last finding, which I guess is maybe less crucial for DC, but more important for your part of the world, which is wealth, is the bequest. So if you're thinking of succession planning, if you look at the assets that you're expected to have at the end of your 30-year retirement, again, assuming that you're spending with that 4 % rule, again, that's another result that's independent from the accumulation phase.

15:22So no matter how much assets you bring with you at the beginning of retirement, the ratio of your bequest to your initial asset goes up. So I think off the top of my head, for instance, under the historical distribution, if you have a market allocation, you enter retirement with$1 million, you're expected to have$1.3 million in bequest. With core, it's something like$1.6. So again, that's an extra$300 ,000 in outcome. That's pretty significant if you're thinking of leaving your money either to children or a philanthropic cause. So really, those are the three big findings that at the beginning of life, you have a benefit on the accumulation.

16:03In retirement, you have a benefit on the spending. And even at the end of life, you have a positive impact on Big West. So it's the entire life cycle kind of benefits from that allocation. Matthew, I appreciate you walking through those different outcomes from the research. And I referenced it a little bit earlier, but maybe you can get into some more details about implementation as you're talking about these core portfolios versus abroad market index. Yeah. And that's an important thread to get back to. So when we mean core, first of all, we're starting with a broad market universe. So something like all stocks in the US, which is even more expensive than some of the index out there in the sense that some indices, for instance, might just consider mid cap and large cap, whereas core is really all the stocks that are trading out there.

16:48Then the weighting scheme is based on market prices. Because one of the nice things of market prices, if you look at the complete market portfolio, it is self-rebalancing. You never need to rebalance within it. So if a large cap stock, for instance, goes up, it becomes 2 % of the market instead of 1%, well, you're holding it in the same proportion at the beginning. So you're going to still be right on target at the end. So what we do instead of doing something that ignores market prices, we start from the market prices and then we kind of adjust them so that, for instance, a large cap stock with value characteristics might be overweighted and a small cap stock might be overweighted.

17:26But again, we pick those kind of adjustment factors so that you still hold a very broadly diversified portfolio, that the weights are not too far out of whack with the market. And that's kind of the core, pun intended, core ways of constructing the core portfolio. And also on top of the weighting scheme, there are some targeted exclusions. So for instance, within the small cap segment, we find that the style of firms with the highest asset growth have abysmal returns, for instance. And they're a very small segment of the market. So you're thinking of dropping maybe 200 names out of, I don't know, 3 ,000, for instance, in the US.

17:59So excluding them, and they're also, by definition, a tiny segment of the market cap. So with that mix of targeted exclusions and also the weighting scheme, you end up with something that has thousands of names, very broadly diversified, low turnover. And then for kind of the long-term drivers of expected returns, as I kind of hinted at earlier, you put the kind of balanced emphasis on value and prof. So you would expect, for instance, within large cap, stock with value characteristics and a stock with high prof to be overweighted by kind of the same amount. So you're not favoring one factor over the other.

18:31And what's interesting about that design is, first of all, by modulating how hard you tilt relative to the market prices, you can give investors a choice about the kind of trade-offs that they're willing to accept in terms of tracking error versus outperformance. What we use in the paper is an index that basically mimics the US core one fund that Dimensional has, so kind of a more moderate amount of tilting. And what's interesting about the core construction to the balance emphasis on the premiums is the premiums are not perfectly correlated. So the biggest premium of all is the market premium, the equity premium, but also there's value, profit, and size.

19:04So that's four ways that you can win, basically, that they can have positive returns. And it's more rare for the four of these premiums to have negative returns all at the same time than a subset of them or even one. So that's another way that helps give you a better trade-off between the tracking error that you take and the higher expected return because you're just kind of smoothing out or diversifying some of the factor-specific risks. so to speak. So you end up with something, again, very close to the market, but with enough of a tilt that you can outperform. What I find so interesting about the way that you did the research in general is thinking, you know, again, more from the planning perspective, despite the fact that what you're really doing is portfolio design.

19:48And I don't think anybody would argue that if you end up in your defined contribution plan in a broad market index, because all of them have it, that's going to be better than a lot of the options out there. But as you talk about the reduction in failure rate on a spending pattern or retiring with a certain amount of assets, you do keep bringing up this tracking error piece, which I think is important. And I've come to learn in my career that it doesn't matter if you've built the perfect portfolio if the investor can't stick with it. And so you and I have both used the word tracking error a few times here, which just again, the level set for all listeners and viewers is typically measured by the difference between the investment strategy and the benchmark index.

20:33And so the moment that you decide to deviate from this market portfolio or this broad market index, you're going to introduce tracking error. And we all love positive tracking error, which we call outperformance, but negative tracking error is part of the cost of these higher expected returns. And so I guess with that in mind, for an investor that is going to take this factor approach, what do you think are some important things to know in advance? And what things should an investor think about during those periods of negative tracking error? That's an interesting point you make about tracking error.

21:07Definitely, we don't get a lot of client questions when the tracking error is positive. It really tends to be obviously during periods of underperformance. There's two sub-questions in your question. And I think the first one is maybe the one I would emphasize, what do you do in advance? Because when you're underperforming and you're in the middle of maybe a challenging situation, you're more likely to make mistakes, maybe to sell out at the wrong time or just like make rash decisions. So really, if I had to boil it down to one key principle, I say I would make two statements. The first is, how much do you really trust this?

21:43And after you've reviewed all the evidence, that you've reviewed the theoretical rationale, you've reviewed the evidence, how much do you trust this, that you actually feel like this makes sense? And that's something, again, that when you're in the financial planning world, you can kind of gauge for individual clients where it's going to be a good fit to kind of customize on that part. Because I do think one of the things that's easy to lose sight of is when you have 100 years of data, an extra five observations don't change the conclusion of that sample, right? An extra five years doesn't change much.

22:14But for people, it can still feel like an eternity. So you really have, before this even happens, think about if I have five years of negative returns, does this thing make enough sense to me that I won't revise my beliefs exposed, that I will still believe after a run of underperformance that it makes sense? So I think that's the first question I would ask. And that question, I think, is somewhat correlated with the amount of tilting that you're taking to an extent. So for instance, if you look at our funds, the US core one, since its inception, it gave basically market-like returns. So you had one of the worst run in history for value, a 10-year of underperformance in the 2010s, that you had literally the worst annual return in 2020, I think, for the value factor.

22:58So again, this is one of the things where it would have been easier for most people to stick with a core one, where the underperformance would have been more modest than a core two or have even a more tilted allocation. So that's the first thing, determine how much you trust this, and then adjust your allocation accordingly. And then the other connected question, which can help you kind of pin down which amount of exposure to those premiums you want, is how much pain am I willing to take, basically. It's just a matter of risk tolerance. I would emphasize that you have to be careful there. When we're talking about tracking error, you're talking about underperformance.

23:38But over the last 10 years, having 8.5 returns overall instead of a 9 % return, for instance, that's a scenario that I think most people could have stuck with or it wouldn't have derailed your financial goal. So it really becomes more of a matter of how much are you comfortable with that, saying that you can have this amount of underperformance lasting for some time and be honest with yourself up front. Because especially after a good run of returns, people think that it's an arbitrage. I'll get back in and then I'll get all these nice returns afterwards. So those will be my two elements of an answer.

24:09Like just make sure that you truly understand the rationale, that you're comfortable with it. And then after that, be honest about the amount of underperformance that you're willing to accept. And then during periods of underperformance, I think for most people, the right behavior to have is not think about it, just stay in your seat and keep going. Well, at least if you're using this in your 401k plan, perhaps you won't notice. Reports aren't always as transparent as if you're working with a fiduciary advisor directly and you see clear benchmarks. But even so, I do know that a lot of people say that they can tolerate underperformance for 10 years, but they think of 10 years as the long term.

24:48whereas statistically it really isn't. So obviously, self-serving statement, having an advisor makes this sort of approach far easier than if you are doing your investments on your own and don't have somebody to act as that ballast and keep their hand on the wheel when things don't look like maybe they're working. Just on the note of 10 years is not really the long term. Can you maybe talk a little bit about what is the long-term in terms of data, in terms of looking at strategies? And as you mentioned, we could have a hundred years of data. Five more data points is not going to make that big of a difference.