Bradford Cornell is an emeritus Professor of Financial Economics at the Anderson School of Management at UCLA. He is currently teaching a new course on Climate Change and Finance at both Anderson and the Rady School of Management at UCSD.
Professor Cornell has published more than 150 referred articles. He is also the author of four books: Corporate Valuation: Tools for Effective Appraisal and Decision Making, The Equity Risk Premium and the Long-Run Future of the Stock Market, and Conceptual Foundations of Investing.
Professor Cornell is a senior advisor to both the Cornell Capital Group and Rayliant Global focusing on the relation between valuation and investment decision making.
There is an overarching investment philosophy that permeates most of what we do here at the Rational Reminder Podcast, and while some guests' positions might differ at times, it is rare that we have someone on the show whose approach is as strongly contrasted with ours, as Professor Brad Cornell. Professor Cornell's arguments are so well-founded and researched that they require a re-examination of positions that we feel have been a given for us for a long time. He is the author of about 150 referenced articles, four books, and has conducted hugely interesting work on the current state of value investing. His research with Aswath Damodaran, and insights into Tesla's valuation provide great food for thought, and we get into all of this on today's show! Our conversation also covers ways to go about picking a fund manager and a slightly different lens through which to view past performance. We feel truly grateful to have such a different, yet valid, perspective expressed so well here, and cannot wait to share this highly useful information with all of our listeners. Tune in to hear it all from Professor Brad Cornell!
Key Points From This Episode:
The difference between a stock characteristic and a stock risk factor loading. [0:03:30.2]
Some of the challenges in using characteristics to develop an investment strategy. [0:05:43.8]
The problem of non-stationary frameworks as a starting point for investing. [0:07:33.4]
How little we know about the cross-section of expected stock returns. [0:08:32.1]
Concentrated, characteristic-focused portfolios versus something more diversified. [0:11:12.7]
Unpacking the 'big market delusion' and the huge power of the narrative. [0:12:11.4]
Looking at the example of the electric car market and what it teaches us. [0:16:18.4]
Professor Cornell's thoughts on how to pick a fund manager. [0:21:23.0]
Assessing the issues with mean reverting performance. [00:25:58]
The most relevant ratio: price to a value estimation. [00:30:35.2]
Some thoughts from Professor Cornell on the rise in ESG investment. [00:32:22.5]
Approaches to the expected equity risk premium for investors and planners. [00:39:45.0]
Bringing in historical context to the conversation about predictability. [0:45:16.1]
Professor Cornell's approach to calming down investors' reactivity to volatility. [0:47:56.5]
A great definition of success from Professor Cornell! [00:49:57.2]
Read The Transcript:
Our listeners are somewhat familiar with the concept of factor investing because we've talked about it, well, quite a few times on the podcast. Can you explain the difference between a stock characteristic and a stock risk factor loading?
Well, here's the way I understand it. Let's take a specific example like stocks with high PE ratios. That's certainly a characteristic. You could sort stocks that way. And you'd say, here are the high PE stocks, and then you could examine whether or not they have higher returns than other stocks. But the factor pricing theory is that this price earnings ratio is a systematic factor that reflects some sort of underlying risk, is the way Fama and French put it when they first developed this approach. And therefore it earns a risk premium by nature of that underlying risk, whereas as a characteristic, it may or may not be associated with any premium.
Yeah, that's very interesting. And it's not a distinction that gets talked about that much, especially in the practitioner world. Can you talk a little bit about why the distinction that you just described is important from the perspective of asset pricing theory?
Well, it's even more important I think from the perspective of investing too. If it is a risk premium as Fama and French say, then it's going to be permanent unless the risks somehow it goes away. So you would expect to earn it, but it is not in any sense a beating the market premium, you're simply paying for risk. I mean, in the same way, if you hold the S&P 500 instead of treasury bills, you're paying for risks. So from an asset pricing theory, that's the way it works. A lot of people sell funds on the grounds that they're going to invest in these factors and they make it sound like they're going to be beating the market. That is actually more like a characteristic, saying we've discovered some stocks that tend to be under or overpriced and we're going to invest in them or short them. So it's a very important distinction and it's not appreciated and it's not much understood outside academia.
Can you talk about some of the challenges that there could be in using characteristics to develop an investment strategy that's trying to capture one of the underlying risks?
Well, this is a real hot button of mine. It's something we talk about at Cornell Capital Group every day. And it depends upon how important you think the issue of non-stationarity is. And I happen to think that it's very important and we can talk about that and that will come up in other aspects of your questions, I think as well. But if a process is non-stationary, it has all sorts of implications for investing. Let me just take a simple example and I think it'll help your listeners. Supposed I'm drawing marbles out of a bin and supposed in that bin, there are six blue marbles and four red marbles, and I've drawn, I put it back in and I shake up the bin and I draw again, what can I learn from that process?
Well, I can't learn what color I'm going to get next, that's always going to be random, but if I draw enough, I can learn that they're 60% blue, 40% red, and the probabilities are 0.6 and 0.4, which is a lot to learn. That's all conditional on drawing out of the same earn. And what I think characterizes investing unfortunately, is nature changes as the earns on us. So we've been drawing out of one that has six blue and four red, and suddenly she puts in one that also has five whites for blacks and six yellows. And I draw another one and I'm in an entirely different environment. And I think that characterizes investing. And I don't think it's talked about a lot in the academic literature because there's not much you can do about it. If the world is non-stationary, you're pretty much stuck in a lot of ways. And that I think is one of the key issues for investing today.
Yeah. That's really interesting.
So are you saying the old framework, the old cross-section expect to return framework is a stationary framework? Is that what you're saying?
I'm concerned that it's non-stationary, I really don't believe it. And I would offer as one example, what happened to the value effect. I'm an old guy, so I've been following this literature and writing in this area for more than 40 years. And up through about 2008, the value effect was one of the most widely documented empirical irregularities. And that's why Fama and French interpreted it as some sort of risk factor that was going to be priced because it was so consistent. And then suddenly around 2008, it not only disappears, but it reverses. And I think that's just a classic example of non-stationary. So I tend not to believe the cross-sectional work very much. But that's my personal opinion. You could talk to another scholar or an investor and get, Cliff Asness and get an entirely different view.
It is worth thinking about though. So, I mean, given your opinion, what would you say that we really do know about the cross-section of expected stock returns?
Very little. It reminds me of a story that Richard Fineman, are you familiar with that name? The famous physicist?
Yeah.
When he won the Nobel Prize, they have all those dinners and all, and he was sitting next to someone like the queen of Denmark. And she said, what did you win your prize for professor Fineman? And he said, the theory of quantum electrodynamics. And she said, oh my goodness, we can't talk about that, I don't know anything about quantum electrodynamics. And Fineman said, well, ma'am, quantum electrodynamics is actually one thing we, meaning humanity, do know something about. We can talk about the weather or politics or economics, something if you like, but we really don't know anything about that. And that's a lot the way I am with a lot of this very technical investing literature. If the world is primarily non-stationary, most of it's not going to work in the long run.
That's fascinating. It's a skeptical perspective that I think we included or are guilty of not taking often enough. It's easy to take a lot of the academic work as given, like the value premium, like you mentioned.
Well, in our studies, we have one history. We have one look at the tape and we have now hundreds and hundreds of PhD students and young scholars spinning that tape every which way to find regularities. And you find regularities that don't exist. I'll tell you one more Fineman story, because I think they're so interesting. The reason I know these stories so well, he lived next door to my parents' best friends.
Oh, wow.
So as a high school student, he used to have me over to his house and just sort of paper me with questions. And that was quite an experience. It made me very academically humble the rest of my life. I didn't realize how unique he was and he made me feel like just such an idiot. But this was one of his favorite acts. He would memorize the first, I think it's 768 digits of PI and he could rattle them off.
And when you get that, I think it's 762, there is six nines. And that's really very rare to have six repeating digits in the first million or the first 1,000 for that matter. So he'd get to that, he'd go nine, nine, nine, nine, nine, and so on, and then break out in laughter. And I think the nine, nine, nine, nine, nine is true of much of our research on investing. We're looking at the digits of PI, we're finding the six nines. We're thinking they're meaningful, but we don't have a way to know that. And I don't believe we do know that.
Fascinating. In your paper on characteristics and returns, you mentioned Besson Benders' 2018 work on the skewness and individual stock returns. If somebody decided that despite the skeptical stance that we just talked about, if somebody decided that they did want to pursue a premium that seems to be associated with a characteristic, do you think it would be more sensible to do that through a concentrated portfolio focused on that characteristic or a more diversified portfolio?
If you're basic and on the statistical patterns, you found the characteristic and you want to exploit it, I would do it as widely diversified as possible for exactly Besson Benders' reason. And it also sort of ties in with things like you want to talk about a little later, the big market delusion. You can have a situation where on electric vehicles, someone is going to be a big winner, but I can't tell you who that's going to be. So it's the same type of problem. You'd be better off if you really believe in electric vehicles holding a portfolio and not a concentrated position.
And that's our next question is about the big market delusion. So there's lots of stories lately of different sectors, such as cannabis, electric vehicles, clean tech AI that have had traumatic asset price increases. What do you think causes these increases for sectors with this kind of enormous growth potential?
I would have to agree with Bob Schiller here. I was just rereading his thing on the excess KPO. And he says in there, the pricing clearly shows the evidence of sentiment and narratives. And I think he's right. I think it does. And I think with electric vehicles, there's sentiment in narrative and it's driven the entire market of the stocks that you have companies that make that to unsustainable levels. That doesn't mean that one, maybe Tesla won't be a new Amazon, but it's not going to be 10 of them.
Can you talk about the power of the narrative? Does this convince people that valuations don't matter or does it mean something else to you?
Well, that's what we're struggling with at Cornell Capital Group every day. Let me just tell you briefly our kind of approach to investing. We think the only way to do it is a combination of just holding a very diversified portfolio and doing fundamental DCF analysis, and then skewing your investments toward those things that you think have value greater than price based on your DCF and away from those that have value greater than price. So you're basically punting all the characteristic stuffs.
Here's another thing that bothers me with the characteristic literature. I'm interested in Apple. I bought Apple stock at the IPO and I've followed the company ever since then. It's funny. I used to, when I was a graduate student at Stanford, I was interested in computing. So I used to go down to this place called the Biteshop, which sold chips and so forth on El Camino and Cupertino back before Silicon Valley was really Silicon Valley.
And I met both Jobs and Wazniak because they were customers and it got me interested in their company and then I've followed it ever since. But when you think about Apple, and this is going back to my non-stationarity point. The Apple that I knew was a small entrepreneurial firm making personal computers for people who were really interested in personal computing at the beginning. The Apple now is a $2 trillion mega company making personal devices like phones and the apps for them and all. It has the same name. And if I go to CRISPR and download the returns, I can get the series of Apple returns and do regressions, all sorts of things. But it is entirely a different beast. The only thing it really shares is the name. And I think that it has again fundamental importance for investors.
Yeah. That is an interesting and important point. Can you dig a little bit more? You mentioned the narrative piece, like what Schiller's written about. Can you talk a little bit more about the big market delusion, why these sectors that potentially could grow very large, why they see these big price run-ups? You had a fantastic paper explaining this big market delusion concept.
Yeah. Well, both Aswath, Damodaran and I, that's our weakest point. What gets these things going? There's no question that electric vehicles are going to be important and they're probably eventually going to be the dominant light vehicles. But the problem with that is it ignores competition. And I like to quote Warren Buffet in this respect. He said that if he'd been at Kitty Hawk, he would have shot the Wright brothers down because though their invention was incredible, it's revolutionized the way we live, airlines have been horrible investments from the start.
Most all of them have either merged or gone bankrupt or merged and gone bankrupt. And Mr. Buffet himself has lost billions of dollars investing in them. So I kind of see the same thing happening with electric vehicles, the Neos and the Nicholas and so fourth, maybe one of them is going to rise, but I'm kind of suspicious, I see two or three big players eventually dominating the market. I just don't know which one. If I had to guess, my best money would be on Volkswagen, but that's just my personal guess.
It's interesting you mentioned that about the electric vehicles. It's always a question I've had with respect to Tesla. It's not like the competition is going to sit idly by and let them own this market share. But one of the narratives has been, it's not really a car company, it's a software company. But you still can't ignore Volkswagen, Toyota, pick the competitor you want.
I have two responses to that. First of all, if you just look at the data, their revenues and earnings, it's a car company, it's not an energy company or a software company. Maybe later it will become one. But if you become a software company, now wait a minute, what about Google and Microsoft and Amazon, all of these have, and Apple. They all have probably better software engineers than you do. And if that's what's going to drive it, why can't General Motors strike a deal with Google to provide the software? Again, I think they're underestimating the competitiveness of the market.
When we have these instances of what you described as the big market delusion, where everyone gets really excited about the sector without accounting for the competition piece, does it always end in a crash? How can this possibly play out?
I don't think always, I haven't really studied that. I don't think Aswath has either, but it certainly, if you think of the entire market of all the companies together, I think it does tend to play out that you may have one or two big winners if the market takes off as projected, like Amazon in the online market. We had back in 2000, hundreds of those companies and they basically all failed and then Amazon became a mega with. So I think you're going to tend to see crashes, particularly if they're priced like they are now, Tesla's already priced as if it's going to win.
What would you say if the theory is correct of the big market delusion, what would you say the investment implications are?
Well, I can tell you what we're doing at Cornell Capital Group. We're selling options on Tesla, but we're hedging it with stock to stay a little bit short. We want to be short because we think it's overpriced. And we liked the fact that it has a huge implied volatility, which makes option selling ideal. But if you just write naked options, as professor Schiller says, who knows when the narrative's going to take off again and it'll go up a couple of hundred bucks. So we hedge it by owning the stock and then hoping that the option will slowly just depreciate and stay a little bit short the entire time. So that's the way we're trying to do that one. Same thing with Neo.
Interesting. Very interesting.
General Motors and Ford and so forth who are getting into the space now are not priced high enough and don't have a high enough implied volatility to pursue that strategy.
Interesting. This sort of leads to our next question, which is about passive investing and market efficiency. Can you talk about what the increasing shift towards vehicles like index funds means to the future of market efficiency?
We just had a seminar at UCLA with professor Hidad on that subject. And he's claiming that the level of efficiency and competitiveness is falling. There's certainly, I think a possibility of that. It goes back to the original Grossman Stiglitz paper in 1980. And incidentally, Dick Rowland and I wrote a paper about the same time. That's one of the problems of academia. If someone scoops you by a little bit, they went 100% of the market share. Everyone knows Darwin, not many people know Wallace, but at any rate, we wrote a paper on the same subject, which is the obvious point that the market can never be efficient. If it were, it wouldn't pay to do research. At which point people would withdraw from research and prices would diverge from value and you'd see some inefficiency. So I think if there's too much passive investing, that's a risk.
But there's one additional point, I think I mentioned this in my paper. What about the role of the issuers? Suppose that most people are passive. So the prices do diverge from fair value and you don't have enough active investors in the market to arbitrage it. Well, what about it being arbitraged by the people actually issuing shares or buying them back. And I kind of see this in the whole SPAC revolution. We were talking about these spaces like electric vehicles, green energy, AI, so forth, exploding in value. And those are exactly the same areas where you see the specs. So it's the people trying to take advantage of the mis-pricing are not maybe as the traders as the issuers themselves.
That's fascinating to consider because we always hear the narrative of, as the assets all go passive, market efficiency dies. But that point that you just brought up I've rarely ever heard it mentioned as part of that overall discussion.
Yeah. It is really worth considering. And like I said, the SPAC experiment, just being a perfect example. In fact, at Cornell Capital Group, one thing we're trying to do is follow this facts as being sort of an indication of where we might want to pursue this Tesla strategy of buy the stock in short options if you can find it. Probably is most of those companies are small and don't have liquid options.
Right. I want to shift to fund managers. You had some fantastic papers on this concept. Is picking fund managers that have had recently strong past performance a good strategy?
This one I think I can answer confidently that it's not a Fineman answer, but it's the closest I can come. No, I do not think it's a good strategy for two reasons. The first is, stock prices are so noisy that over the horizon which performance is measured three to five years, I don't think you can draw any meaningful conclusions. But to the extent that the data show anything and Jason Hsu and David Nanigian and I have worked on this on and off. It shows that the fund managers who outperform are the ones you want to avoid. So if someone does really well for you like Kathy Wood, it's time to sell according to our data. And I can explain why I think that happens in a minute.
So you're saying that picking losing managers is a better way to go?
If you were only basing it on past performance, if you told me I can't do anything else, it's going to be based on past performance, then I would think you'd probably be slightly better off picking ones who had lost in the last three years than ones who have gained. Now let me explain, because now we're sort of getting how in the world could that be?
And it's so different than sports. The Lakers won the NBA title last year. Assuming that LeBron and their are other players, Anthony Davis get healthy, it would be very rational to pick the Lakers to be right in the mix to win again. And that's true of almost all human endeavors, great mathematicians, great pianists, they all remain great. But investing is a totally different game because it's competitive. And here's what Nanigian, Hsu and I think happens. The winners are winners because their strategy happened to work in the past and Kathy Wood's a perfect example.
She buys these aggressive disrupting tech stocks. We all know they've had a tremendous run-up in the last year. Well, to the extent that there's inefficiencies in the market, you would think that things that ran up a lot have become overpriced. And the investors who bought value stocks like banks and energy and so forth, they've underperformed. But that's because the stocks that they own with their strategy declined. Well, to the extent that the market's a little bit mean reverting, the things that ran up a lot come back and things that dropped a lot come back, the losing managers do better and the Kathy Woods do worse. So if I only had to pick on past performance, I'd probably pick the losers.
In the paper on this that you did, I referenced it in one of my YouTube videos. So I'm fairly familiar with that paper. You actually built a winner strategy and a loser strategy where the strategy picked while winning funds or losing funds and losing strategy completely dominated the winning strategy, which is just unbelievable.
Actually, and it was statistically significant too. I'm not sure I would believe it enough to go and travel around the country and urge institutional investors to fire their winners and hire people who have done very poorly. But there's the answer to that, the way I would approach it, if I had to pick a fund manager, it's in that paper too. And that is, I think what you should listen to is not past performance, but their theory, why do they think they're going to outperform in the future? And does that make sense?
So for example, when I read what Kathy Wood says, she's very unconvincing to me. I view her as someone who got lucky and rode the wave, but the theory that this is going to continue and you can open new funds and buy more disruptors and jump into Coinbase and that's going to take off too, that theory doesn't appeal to me. So I wouldn't buy it her fund.
On that same line of thinking, we understand now from what we just talked about, that past performance is not a good way to pick an investment. Does it tell you anything though about the manager's skill?
I don't think so. I think it tells you about their strategy. Again, I'm sticking with the ARK example just because it's so timely. Once you know that they were in that space, you know they've outperformed, I guess you could see within that space, did they pick stocks that did particularly well? And I don't know the answer to that. That would be more informative, but I don't think it's much of an indication of skill. I think it's an indication of you pick stocks and nature happened to pick your strategy.
Interesting.
Come back to my earn, you pick the blue ball, nature threw the ball and it was blue.
On the mean reversion piece you mentioned the asset pricing effect where a fund that does really well, probably bought stocks that did really well in evaluations will tend to come down eventually. In your paper, you also mentioned the black and green work on strategy capacity and things like that. Can you speak to that other aspect of the mean reverting performance?
It's the same issue. All the people piling into tech stocks now are driving the Teslas sky high, and that's going to crowd those trades. And I think push the prices beyond DCF fundamental value and lead to future under performance.
Just on ARK, because like you said, it's timely. And I know you've done a lot of work on Tesla evaluation as well, you and Damodaran together. Do you think ARK got the valuation right on Tesla or did they get lucky with their research?
Well, doesn't she have a price target like 3000 now or something?
Something like that, yeah.
Which would make it as big as Apple. I think she got lucky. She told a story that was resonant with the media and with the narrative and all and bought a stock that did extraordinarily well. But yeah Aswath still valuing Tesla too, we're both still valuing it. We're struggling to get over $300. That's assuming that it has margins like Porsche and output like Toyota, that gets you to about 300. So now you've got to do better than Porsche on margins and sell more cars than Toyota. That is not an easy task and do it by a lot. Meanwhile while BW is coming after you, Toyota is starting to change gears. Mary Barra is saying the GM is going to be an electric car company in five years. No easy task, not one I believe can happen.
Jeez, you alluded to this earlier, but I'm curious by the Fama French definition of value is value investing dead? And how is that different than your DCF model that you're using now? I'd love to understand that difference.
Here's a story I tell and it was just the recent popular paper I've written on value investing. And it goes back to again, my early computer days. In, I think it was 1975 or so, Dan Bricklin is sitting in a class at the Harvard Business School, accounting class. And they have to make these big handwritten spreadsheets where they enter they're doing a proforma financial, you've got to enter the numbers for each year, blah, blah, blah. And then if you change something like you say, oh, I think it's going to grow 10% rather than 5%. Then you got to erase everything and so forth. And he was thinking, why can't we make this electronic, there's this new Apple to computer, why can't we just have electronic columns of numbers and if I change the growth rate, everything changes?
And there's an interesting big market delusions start here too. So I'll continue with this one for a minute. He joined with a computer scientists from MIT and they built a software program called VisiCalc. And VisiCalc was the first spreadsheet and it was a huge hit. It actually drove the sales of the Apple two computer. It was probably more responsible than anything else for the Apple to being a success. But this account sort of sat on its hands and went off in another direction. And when the IBM PC came out, this guy, Mitch Kapore, who was sort of a Yale PhD hippie, formed a company called Lotus Development and developed a new spreadsheet called 1-2-3, which ran on the IBM PC. And 1-2-3 sort of deep six VisiCalc. You can see that the electric vehicle analog here, and it became the biggest software program in the world. And it was so successful.
This is a rumor. I don't know if this is true. But Bill gates called Kapore and said, why don't we merge our companies on an equal basis. You'll own half of the new Microsoft Lotus and so will I. And Kapore turned him down. So Gates who had a crummy spreadsheet called MultiPlan, threw his money behind Excel, which he first developed for the Macintosh and Excel ended up dominating 1-2-3, and it became the Amazon. But you can see the same sort of dynamic playing out. It was a great idea, it was a huge market, but now everyone else has failed basically, except Excel.
Now maybe Google would get cheaper with Google sheets and they'll be competition there, but it tells the same story for investing. Just because you found a cool thing, MRNA, like Moderna's vaccine, that's cool, that's like the spreadsheet, but who's going to really make the money? That's what Mr. Buffett keeps worrying about. He doesn't want another airline fiasco.
So do you think value, I know we talked about characteristics and the challenges with that. Do you think that the concept of buying low-priced, price being based on market price and low, I guess being based on some metric like book or something like that, do you think investing that way is dead? Like we mentioned, it's been successful in the past going forward, is it useless?
Well, that's one of the reasons I went into that long-winded story about the spreadsheet, because it was my view if Bricklin had invented that earlier, Graham and Dodd would have written a different book.
Oh, fascinating.
Wouldn't have used all their indexes of price to book and price to this and that and we wouldn't have all these outdated ratios. There's one relevant ratio, it's price to your estimate of value. Now every MBA student can build a spreadsheet. So I don't think value investing is dead, but it should be interpreted properly. It's price to value and value should be your estimate of value, not something like price to book or price to earnings, or even the Cap ratio.
Interesting. We had Robert Novy Marx on the podcast recently, and he talked about his measure for gross profitability, does including a profitability metric like that in valuation using characteristics. Does that help at all?
Well, I've read Bob's papers and they're great papers, and he certainly finds it. It's a statistically significant effect. My thought would be profitability is one of the things you want to consider when you're building your proforma DCF model. The key drivers of any DCF value are going to be revenue, growth, margins, and discount rate. And so the profitability may really help you in projecting margins.
Yeah. Very interesting.
ESG investing has become incredibly popular. Can you talk about what describes an ESG investment?
Well this is something I've also spent a lot of time working with Aswath, Damodaran on, and we wrote a paper called Doing Good or Sounding Good. And if read the paper, you can see we're on the sounding good side. And let me start at the very beginning. And I'm going to focus on environment because Eva Welsh and I are writing a book on, we teach a course at UCLA on climate change, energy and finance. And so we're writing a book on the subject. So I know to quote professor Fineman, I know something about the environment, I don't know so much about social or governance.
But let's take Tesla, we've been talking about it today. Tesla's biggest market is now in China. Is Tesla an E in the ESG company in China? Well, here's the problem, the Chinese grid is powered 60% by coal. So when you charge your Tesla in China, you're running on coal primarily. In addition, making an electric vehicle is far more energy intensive than an internal combustion engine, because you have to make all the batteries, which are almost all made in China, which use a lot of electricity. So that's dirty too.
So right now a Tesla is a far dirtier car in China than a Prius. That may not be true forever. If China's starts moving more to renewable energy, then maybe five years from now, Tesla will be greener than a internal combustion engine Prius. But you see the problem. There's just no way to even know what you're talking about for the most part when you say ESG, unless you really dig into it. And most people don't.
So would it be safe to say that the answer to the question, what constitutes an ESG investment is kind of like, who really knows? It's not that easy to pin down the answer?
Yeah. It's whatever the... Every CEO says what constitutes an ESG investment is what we're doing. It's very hard to know, and there's something else that worries me and troubles me about this. And you can probably see that my debt to Milton Friedman in this. But I'm very concerned that these CEOs are doing something that they know nothing about, spending all this time trying to write a book on climate change. I know how difficult the subject is.
So suppose I'm running a company. Suppose I run a gas distribution company or a auto service company or a bank, what are these people making these statements about we're going to be carbon neutral and we're going to do this and that? I don't think they're trained for it. And I don't think in a democratic society, they should be weighing in on it. The way we handle climate change is a difficult political issue that we ought to set the rules through the democratic political process and not through investors saying I'm only going to buy ESG or corporations making a proclamations. For example, you know I love these analogies. You can tell that now. Let's say are either of you football fans, American football fans, not soccer?
Not really.
Follow it a little bit? The NFL?
Yeah.
Okay. The NFL is a product and a key to making that product successful is to have good rules for the game. So let's take the rule pass interference. The defensive backs would say, oh, the best rule is we can do whatever we want. The receiver tries to run out for pass, we just tackle them. In which case they'd be no passing game. Then you ask the quarterbacks and they say, oh no, no, those guys shouldn't be able to touch my receivers. Neither party has the right incentive to make the rules as effective as they can for the system to succeed. And the NFL realizes this and they have a rules body. And the reason I'm saying all that is the right way to handle carbon emissions isn't by CEO proclamations or divestiture campaigns by universities, it's by setting a proper policy and price through the government, having the right rules and then letting the companies follow those rules to maximize their profits.
The research that I've seen on ESG rating agencies definitely lines up with what you're talking about just in terms of being hard to define, because the agencies often disagree with each other as well, which makes ESG index funds very problematic. Based on what you just said and that idea that it's kind of hard to pin down what ESG is any way, do you think ESG investing is benefiting society? Because I think that's someone investing in an ESG fund are kind of hoping for that, that they're bettering society.
Well, it might be, but this is something Aswath and I have discussed in great detail. So I run through a little example for you.
I think it plays out. So let's talk about a green company and a brown company. The green companies like NextEra, it's in renewable energy, the brown company maybe like Chevron, it's oil and gas. And so, but just call them green and brown. And now let's go back 10, 15 years. And no one's concerned about climate change. No one's paying any attention to the difference. They're both energy companies and let's say the price is the same and they have the same expected return, which equals the discount rate in a DCF. Now the world starts to change, people say, jeez, we need more renewable energy. We want green companies. Well, to the extent that the marginal investors willing to pay more for green, the price of the green stock will go up and the expected return, which is the discount rate, will go down and the reverse for the brown company.
So to answer your question Ben, yes, it could help society by lowering the cost of capital for the green company. But the way it helps society is that investors have to be willing to accept lower returns. You have to say, I'll take 8% on NextEra and give up 10% on Exxon. Now, most investors I talked to is no, no, no, no, no, that's not what we meant. We meant we want 12% on NextEra and 10% on Exxon. And that's what we've gotten because NextEra's stock has done much better than Exxon. But they're confusing the transition period with market equilibrium.
Because when you go back to the beginning, if the rate falls for NextEra and rises for Exxon, Exxon's price goes down NextEra's goes up, the historical returns make it look like NextEra is a good investment. But going forward, the expected return is just the reverse. Now I think sophisticated investors know this, but they keep their mouth shut about it. They sort of say, oh, you can have your cake and eat it too. Come into our ESG fund, pay us the higher fees, even though we're often holding Apple and Google and Facebook anyway, and you'll get better returns. Aswath and I don't really think the hand holds water.
The market equilibrium point is so important. Everything that you just said is so important for people considering ESG investments, where it's like you look at the last three year returns and it looks really good, but like you say, it's because the cost of capital is coming down and the expected future return is actually much worse because of that. But it's for the average investor, very confusing.
And it goes right back Ben to what we talked about earlier in the program, which is why relying on historical data is so misleading. If you're really considering an ESG focus fund, you should be thinking in terms of going forward in the equilibrium returns, not what happened during this transition period.
Yeah. That's a really interesting point. And 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?
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 4150. And 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 4150 and you go to Aswath, Damodaran site, he has an applied equity risk premium calculation there, you can compute what 4150 implies for stock returns going forward. And it's about 4% over treasuries. So 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 and 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 behavior of the equity risk premium is the fundamental issue that I think investors should be looking at.
How would you take that message to overseas markets? What do you think about global views on equity risk premium?
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. And 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. So you'd be bearing all the risk and earning 3.5%.
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.
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. And 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 game stopped finally, found the light - too bad they couldn't have sold them at 400 for them.
Yeah. You mentioned with Aswath's site, being able to calculate the current implied equity risk premium based on price levels, that implies, I think, predictability in returns. So 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?
Well, it really, what you mean is the future average return?
Correct. You're right. Yes.
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. So 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.
When you say low, are you saying broad market? Are you also, for example, looking at your DCF model or a value model, or perhaps a size tilted model or some other factor?
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.
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.
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. And what Vernon said, and this has always been my beef with behavioral 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 behavior is said that everyone was always under reacting or overreacting or anchoring, it was suddenly something happened and it went bonkers. And that to my view is what the alternative to the efficient market theory is. It's not, there's some behavioral deficiency, it's a 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 Xpost, 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.
Yeah. Again, this is another divergence, but you talked tin one of your, the big market delusion paper. You talked about how that phenomenon of seemingly crazy but unpredictable behavior 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.
Yeah. And I think Bob Schiller's 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.
So 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?
I just did a little video for Cornell Capital on this. And I 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. And 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. And if you're not, if you're not planning for that, you're not being rational, you're praying for a miracle.
So basically learned to love or learn to accept volatility and get as much data as you can around the cash flow.
Yeah, I think that's the best you can do.
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?
They should be using the 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. So we're looking right now at 41, 50 at about 4% for equities over the long run going forward.
For US stocks, right?
Yeah. And you'd have to plan. So if I'm running a pension fund, oh, I got 4% over equities, I mean, over the T bond, is 5.5. So 5.5 on equities. High-Grade corporate bonds, what? Three? So if 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.
Yeah. Fascinating. Our last question, completely different question. And for someone who has such an incredible career and has built a great body of work, I'm curious, how do you define success in your life?
I define it with three criteria. First, you want to do interesting things. You only get to go around once. So do things you're really interested in. And actually got that impart from Fineman, he was so interested in what he did. It was really inspiring. Second thing is hopefully you'll make a contribution doing that, but you never can be sure, you just do your best, do interesting things and hope you make a contribution and then raise a good family that you can pass on to the next generation. I've been lucky. Both my sons eventually got interested in this subject and started a business that I can help them with.
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'Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross-Section of Expected Returns' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3484123
'Doing Good or Sounding Good' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3557432