Guest User

January 6, 2022

Index Funds, Portfolio Theory

Episode 182: John 'Mac' McQuown: The Data Will Sort That Out

Guest User

January 6, 2022

Index Funds, Portfolio Theory

John ‘Mac’ McQuown has impacted the world of finance in many ways. Notable among his entrepreneurial endeavours, he co-founded Dimensional Fund Advisors, KMV and Diversified Credit Investments (DCI). He is also known for being the founder and director of the Management Sciences Group at Wells Fargo Bank where he had overall responsibility for creating the world’s first equity index fund.

One of the pillars of our approach at The Rational Reminder Podcast and PWL Capital is the idea of index investing, a concept that is both fundamental and deeply embedded. Today we are very lucky to have John 'Mac' McQuown on the show, who was behind the creation of the first equity index fund. It is hard for us to overstate just how important this contribution has been to the world of finance and any fund managers and investors that share our philosophy. Mac's work back in the 1960s, his position at Wells Fargo, and his contribution to the founding of Dimensional Fund Advisors all speak for themselves, and we are extremely grateful to get some perspectives from this titan of the world of rational and data-driven investing. In our chat, we get to hear about some of the key points in Mac's career and the general arc of the rise of indexing and diversified investing, the key figures that he worked alongside, his thoughts on the future, and the importance of environmentalism in today's world. So, to hear it all from a hero and giant in the space, be sure to listen in with us today.

Key Points From This Episode:

Looking back at the role of data at the beginning of Mac's career. [0:03:00.2]
Wall Street in the 1960s, and the amusing experiences Mac had early on. [0:04:20.6]
Mac's initial findings when he started analyzing institutional portfolios. [0:07:44.5]
Joining Wells Fargo and the team that Mac found himself on. [0:08:28.1]
The strong support that Mac and the quantitative approach were given at Wells Fargo. [0:13:36.7]
Early tracking of index funds and Mac's memories of the first index they tracked. [0:18:21.3]
The initial institutional responses that Mac received to his work with data. [0:20:46.5]
How Wells Fargo contributed to the first commercially available index fund. [0:22:24.6]
Mac's connection to Jack Bogle and the results of their relationship. [0:27:18.2]
The seeds of iShares; Mac traces the beginnings at Wells Fargo. [0:29:57.7]
Perspectives on why people still have belief in active investing. [0:33:19.4]
Mac's memories of working with David Booth during the founding of Dimensional. [0:34:41.8]
Differentiating between Dimensional funds and index funds. [0:36:44.3]
Weighing concerns about the growth of indexing and how this may affect pricing and governance. [0:39:52.5]
Mac's environmentalist philosophy and his thoughts on practical steps against climate change. [0:42:10.6]
How Mac defines success in his life and its relationship to increased curiosity. [0:45:00.2]

Read the Transcript:

Let's kick it off with a question about earlier in your finance career. And back then, data certainly was not like data is today. Can you bring us back in time doing studied finance and the role that data played?

Well, data upended the whole topic. When I reflect back on the finance I was to in graduate school and with my MBA, I majored in finance and it was for all intents and purposes, devoid of data. In large measure, that was because there weren't any really important scaled computers. In fact, when I was in business school, as far as I can remember, there were no computers whatsoever on campus. And that of course was a long time ago. But if you stop and think about the revolution that created by computers and data and the data of course followed from computers, and then of course, analytical procedures and ideas became the quest. And I would say both data and analytical procedures are still at the middle of the quest. Now it's changed a lot because we've gotten more sophisticated, but in a nutshell, we're still after data and methods of analysis.

So, you went to Wall Street in 1961, you mentioned your studies being relatively devoid of data. What was it like when you got to Wall Street?

Well, it was even more devoid of data. As a matter of fact, I have a kind of a funny one about that point. I went to work for a well known investment banking firm, whose name I'll skip over because the next point that I want to make is I was questioned by one of the senior execs I was being interviewed by before they offered me a job. And before I accepted it, and his question to me was, "Why would an engineer want to go to Wall Street?" And I'm not joking, that was a question that was posed in me and expected me to say something. Well, I was already clear from work that I had been doing across the river from Harvard at MIT, that data was going to be the story.

And that was just serendipity that I got exposed to that professor and that early data, and the data I'm referring to are weekend share price for a collection of 50 initially, and then a couple of 100 stocks on the New York Stock Exchange over a period of quite a number of years. And if you stop and think about it, that today is kind of the holy grail of where analysis goes. And of course we not only have weekly data, we have even hourly data on some equities from some markets, but we have data from something like 50 markets around the world. And I think a lot of that data goes back at least a decade, if not five decades. So, in one lifetime mine, that game has totally changed.

So, what level of analysis were the institutions doing in their portfolios at that time?

Zero. There were stock pickers, but it was next to no level of analysis at the portfolio level for the very simple reason is that they had no framework in which to conduct it.

So, if I had asked you at that time, what the returns were in the S&P 500, you didn't have that, right?

No, no. Remember that came around ... Jim Lorie and Larry Fisher at the University of Chicago persuaded Merrill Lynch to collect data on the New York Stock Exchange from 1926 to 1960. And that was initially monthly data. And that was the first data set. And there were something like 600 companies in that set, and that data was built into a database by Larry Fisher, and it was available in roughly 1963. And one of the first people that I met who were studying that data was Gene Fama, who by the way, is still one of my partners, or vice versa, depending on how you want to look at that. But if you look at the puzzle of the period prior to that data, there was no data analysis.

So now you started looking at institutional portfolios analytically. What did you find when you started doing that?

Well, guess what? They were under-diversified, and in a nutshell, their performance, especially if you got around risk adjusting it, it was considerably worse than just the S&P 500, I mean, considerably, especially if you were risk adjusting it because those portfolios were so under-diversified. When I first joined a major banking firm, there were three and $400 million portfolios invested in 25 stocks. I mean, today that would be a criminal offense.

So you ended up at Wells Fargo and Wells Fargo Management Sciences was started. Can you talk about who worked with you there?

Well, that's actually a really curious story for sure. I mentioned already that I was fussing with data, really I was collecting data out of barons and punching it into cards, keycards, and reading them into a computer. And the professor that had me doing that was at MIT, not at Harvard, and I volunteered to do that to learn something. So, I had been fussing around with that data. And I was beginning to look at the statistical behavior of that data. I mean, I was already trained in engineering, data was nothing new to me. And when I went to New York on Wall Street, this professor from MIT and a couple of colleagues, one of them I knew quite well started to put together a company that would attempt to utilize that kind of data to manage a portfolio.

I think it was one of the really first attempts to manage a portfolio with data. So I got recruited by those guys to fuss around with the data as I had been when I was at Harvard on nights and weekends when I was on Wall Street. And it became apparent to one of the senior people at IBM, the data center was at 51st and 6th Avenue in the basement of the Time-Life Building. And one day he said to me, "So what is this stuff that you're doing?" And I said, "Well, I'm just doing what I'm told." And in essence, it's proprietary to some professors and so forth, I didn't reveal anything. Well, he carried that message to a colleague of his IBM. And I met that person on one of my weekend, Johns, at the data center, running data.

And he said to me, "This is really interesting stuff. What can you tell me about it?" So, I clued him in a little bit about it and about a month or whatever later, he invited me to San Jose to give a talk on data analysis just kind of in the abstract sense, before a group of banking executives. Well, who was in the audience? Answer, among others, of course, the chairman of Wells Fargo, Ransom Cook. So, Ransom comes up to me afterwards and he says, "I would like to have a chat with you about this topic. Are you going to be around for a couple of days?" And I said, "Well, I'm going to be around tomorrow." And he says, "Can you come to my office?" Which I did. And I go into his office and without any hesitation at all, he says, "I would actually like to see that work extended, how about coming to work for me?"

That was the first 50 words out of his mouth. If you don't think I could have been knocked over by a noodle, I was easily astonished. So, I go back to New York and tell this to my wife, and that didn't draw a particularly broad smile. She was in the MBA program at Columbia at the time. And then Mr. Cook persisted in a couple of phone calls and he got me to come back to San Francisco and meet several of his lieutenants and made me a very attractive offer, and he asked me how much I was making a month.

And I told him, and he tripled it and said, "Supposed we have that as your starting salary?" Well, I mean, come on, triple what I was making in one shot. So, I left New York and went to San Francisco with a reluctant wife and started working on this stuff, which mostly included hiring a variety of people to actually do the really difficult work, which I explained to Mr. Cook, I was really only capable of doing some. And he was very agreeable with that idea. So, in the final analysis, we made deals with a number of consultants and, or their advisors, which means they're more senior professors, mostly at Chicago, but also at MIT and Stamford.

And within a few years we had 11 or 12 different academics working on the problem. And mostly, what I was responsible for was the team that I had as staff working on the data, and the professors were the ones who were designing the experiments. Well, if you fast forward to today, six of those 11 professors have Nobel prizes. So, it was a perfect storm, and how the hell did that happen? Pure unadulterated serendipity, the generating function of the universe, I'm fond of pointing out.

Now, we understand that at Wells Fargo, you were given an unlimited budget, which is somewhat unheard of, I think. Why do you think that they were so supportive of this quantitative approach?

It wasn't really they, Ben, it was him. It was the chairman. My budget was taken out of the system and was the chairman's budget. And he alone made up his mind how much was going to get spent. So, whenever I had a request for what amounted to some more money, I went to the chairman and never once in the 10 years I worked for him and his successor was it turned down. He said to me one day, "Look at all the money we spend on systems and computers and all this stuff, and all we're doing is the same thing we did in the 1930s with punch cards and green shades and eye bands, arm bands. If we can't do something more than that, I don't know why we have these fancy computers." That's his point of view.

Well, guess what, a lot of his lieutenants were not that happy about it, but a few were. He stood up to it all the way. And there were a couple, his chairman successor too was a big devotee of what we were doing in the same kind of analysis. And he was very instrumental in populating a lot of effort at Wells Fargo around data analysis. But remember, this was the beginning of a perfect storm. Wells was not the only place, but it was among the first, that's for sure.

So what were some of the results of that incredible brain trust?

Well, obviously, probably the most important single one was index funds, pretty hard to score the significance of index funds. If you want to state it much more generally, passive management, but there were quite a few other things too. I mean, there were several people who were interested in automated credit analysis and retail credit scores. We worked on the development of retail credit scores, that was subsequently picked up by Fair Isaacs, because Fair was a good friend of the chairman. Well, you've heard of FICO scores, right? Well, we had some things along that line working before FICO existed. Another one I think that was interesting was what became known as MasterCard was at the time called Master Charge, and the whole idea was to try to move small consumer credit away from monthly payment loans, which was the predominant form of the lending at the time.

But monthly payment loans were opposite a given asset. They weren't open ended credit. And I would say that that creation of open ended credit, which we certainly did not invent, but we were among the first to subscribe to that idea and our chairman was the first to persuade several of his colleagues to form a consortium, to form MasterCard, or Master Charge. I mean, if you really stop and think about the implications of that, of course, American Express was already there. But the banks came second in that race. As I said, it was a perfect storm. I think another one of the really significant lines of inquiry had to do with how do you measure the profitability of a bank branch? There were no models of that question. They were just expanding the branch network kind of willy-nilly. I mean, that's unkind, but I don't mean it quite bad consequentially, but the point is there wasn't any end procedure for evaluating branch profitability.

They really couldn't even measure what the value added to the bank was of a bank deposit. There was just a history of people putting deposits and other people borrowed money, it was loans and deposits. But there was no analytical process for connecting the two. But again, I'm not blaming the banks, remember there was no computers and no data being focused on this kind of thing until just about that same time. So, I'm right back to my perfect storm statement, but that's what data did. You asked about the importance of data, there you have it.

So you mentioned the index fund being one of the most important things that came out of the work that you guys were doing. What index was the first index fund tracking?

Well, the one that finally ended up in an actual portfolio was in fact, the S&P 500, but we fussed around with the Dow 30 and of course we recognize quickly that 30 stocks, no matter how you choose them is going to suffer from under the diversification badly. And then of course the other thing we did a lot at the time was we talked about market portfolios, which was not an index at all. It wasn't a sample of something of a market, it was the entire market. But that was a hard egg to swallow in those days.

I mean, today, I would say that's kind of the right way to look at the world is to look at the whole market, but when you get really fancy, which is not really that fancy, you actually start getting into factor analysis. What other risk factors that explain performance. But now we're getting much more sophisticated, I mean, that didn't come up until several years later. But of course, that's where we are today is a factor analysis is pretty much the way the world works. And the question is, what factors do you want to be exposed to? And just how efficient any portfolio can you create? That's concentrated on a given factor, and of course the answer is that diversification is far less than the market. So in many respects, we're right back to market portfolios.

I don't think we can overstate how big a deal it was that you guys created the first index portfolio. How big an idea was it? Did you know you were onto something that big, that transformative?

Are you kidding? all you have to do is start looking at the data carefully, but that implies you have data. And that implies that you have somebody financing the look. So, I'm always very inclined to give the guys who ran the bank, Wells Fargo as much credit as the people doing the analysis, because if they wouldn't have signed on to spending that money, it would never have happened.

So we talked earlier about institutions that just didn't have data. And the whole portfolio management process sounds like it was pretty subjective, you mentioned stock picking. How did institutions respond when you show up with data and with this concept of an index fund?

Well, I would say that there were two polls of response, horrified and intrigued. The whole world revolved around stock picking in those days. I mean, what were the firms on Wall Street doing in those days, they were selling stock they weren't selling portfolios. Stop and think about that. Also, remember it wasn't that much earlier than when mutual funds actually came to the fore. I mean, we had mutual funds going back a long way, but they weren't very popular. I mean, it was between the late '40s and the late '50s that mutual funds began to take off. And it was amazing when you stop and think about it, one of my very close friends from business school went to work for T. Rowe Price, not exactly why he did. I mean, I don't really know. I mean, I haven't seen him in many a year, but it wasn't because of the primacy of portfolios. Actually, he was hired as a stock picker, because the way they were creating portfolios was like everybody else. I mean, we're talking about a radical shift.

So you are part of creating the first institutional index fund, Jack Boland, Vanguard launched the first retail index fund. But that was after what you guys had created. Can you talk about the involvement of Wells Fargo in that story? I know it was mentioned in the book Trillions, which we've talked about number of times on this podcast. Can you give us firsthand what that story is?

Well, one of the most important things that our chairman wanted, he referred to it as a portfolio that was safe to sell in branches. And of course, what today we would say is it would have to be an incredibly well diversified portfolio where the S&P 500 is a pretty good proxy for that. But there was no such thing as an S&P 500 fund in those days. Well, if you look at the story of banking, you're struck by Glass-Steagall of 1933, when the Congress in its infinite stupidity separated investment banking from commercial banking, because they thought that was the source of the problem that created the depression, which of course was very far from fact, but it was a convenience scapegoat. So, what that meant was that banks could not deal in stocks and that meant individual stocks or portfolios to the public.

If it was in a trust, the banks had a monopoly on trusts, but Wall Street had a monopoly on agency accounts. Now, does that make any sense at all? Of course, it makes none, but that separation of church and state was an enormous factor. And what do I want to call? The innovation that closed that gap and invalidated the Glass-Steagall Act, but it wasn't for several odd years, a decade or two later that Glass-Steagall Act didn't get rescinded. But I'm very critical of that kind of regulation because it's not predicated on data analysis, either before of the fact or after the fact.

They just implement that kind of regulation and they don't examine the consequences. Well, when it comes to financial analytics or financial analysis in general, you better be prepared to do your homework. And today, of course, and it wasn't 1933, there were no computers at all, zero, and there was even less data, but today it's inexcusable to have a regulation of financial inter-mediation that doesn't consider the consequences and study them. But remember, that's just a change in mindset which companies are changing technology. So in some sense, you can't blame those guys. They just didn't know.

So you are unable to bring an index product to the bank branches. That's what caused the conversation with Jack Bogle at the time?

That's exactly what happened. When we concluded our legal, concluded that we would be in violation of Glass-Steagall, the chairman said to me, "If we can't sell these portfolios in the branches, somebody has to be able to sell them on agency basis. And we had a lawyer in New York who was a former SCC commissioner that was working with us to get funds registered, and we actually got funds registered at the SCC even though we were a bank, it was in a bank holding company framework. And he said to me, after we ran into this snafu, "Well, I know one person who's interested in this topic, Jack Bogle.

So, I went to Valley Forge with Dick, and I'll leave his name out by the way, but we went to Valley Forge and we had a conversation with Jack. He was already thinking about the same thing. We were just further along that path. I mean, if he were alive, he could defend himself, but maybe he was as far along as we were, but we were pretty far along by then. So, I took that back to the chairman and told him what I had discovered in my conversation at Valley Forge, and he said, "Well, go help him, somebody needs to do this." And that of course is what turned out to be the Vanguard S&P 500 fund.

I'm just curious, Mac, because I had read that Jack Bogle was a proponent of active management, but kind of changed through time. Where was he in that evolution when you met him? And did you have to do any convincing?

I would say that he was largely persuaded already that active management wasn't delivering its promise, but like a lot of other people, I mean, like Ransom Cook, the chairman of Wells, that was his intuition, that was exactly the same. The Trust Department was creating portfolios that were not well diversified. And of course the point of the matter is it wasn't being represented as being well diversified either, diversification was not the reason debt of portfolio management in those days, it was stock picking. It's amazing. But bear in mind, the world is round. But for a long time, we didn't realize that. When you stop and think about the revelation that that flatness versus roundness gave rise to, that's about the same scale of understanding that arose in the equity markets in those days. The flatlanders and the flatearthers, I mean, you don't want to take them to the gear team, that's not a fair treatment. They didn't get the picture, but an awful lot of people didn't get the picture for hell of a long time.

So it sounded like when you talked about you were kind of sent off to go help Bogle get this thing off the ground. Did Wells have a financial interest in this? Or was this just kind of, we have to get this thing out?

Ransom wanted to get it ... Well, Dick, by that time it was Dick, Dick Cooley. Those two guys saw the importance of the idea. And if Wells couldn't do it because of Glass-Steagall, somebody needed to do it. And there was somebody out there called Jack Bogle who wanted to do it and our council at Davis Book in New York knew him. The council worked for both firms and openly and that was well understood by both of us. So why shouldn't we be collaborative? We got blocked by law, by Congress. And I always go back to the same point, I mean, Congress didn't understand anything, but I don't think that's very uncommon. There's all kinds of regulation that arises out of special interests and lack of understanding and a lack of data. I mean, much less so to today than it was 50 years ago, but it's still prevalent.

Okay. So, you got your fingerprints on the Vanguard taking off with indexing, but meanwhile, back at Wells Fargo, there was something still going on that through the years was a seed or at that time was a seed to what is now iShares, correct?

Yes.

And what was that?

Remember the difference between an ETF and mutual fund? What is the crucial difference? The crucial difference is in a mutual fund, we value a unit, that is a mutual fund share. At the end of every day, they add up the value of the assets and divide by the number of units. So, there's a new unit value in a mutual fund every day. Well, a mutual fund is just a share in a company. There's no reason why the share in that company couldn't be traded continuously in an open market. And by the way, there was such a thing too. It was called closed down funds. There weren't a lot of them that they had existed, for sure. In fact, they go way back. They proceed by quite a bit mutual funds in terms of their prominence. Well, that's a perfectly reasonable thing to do also because if the shares are trading at a price that's different than the value of the asset, there's an arbitrage.

And the fund management company can actually issue more shares or redeem shares or whatever. And it could remove the disparity between the net asset value per share and the market price of that. So, there's no reason why that could be done. So it became increasingly apparent that that was going to take place by one means or another. So, what's an ETF, that's all an ETF actually is. It's just an open-end fund that has iShares competitively traded in an auction market rather than traded at an asset value at the end of the day. Much more sensible. There's no reason for ... In fact, another one of the things that's pretty interesting is having a conventional mutual fund with ETFs also in the same portfolio. I mean, of course it wouldn't last very long, because the arbitrage would take care of that. But when you get right down to it, it's just another artifact of history that had to be learned and adapted to the implications of the learning.

So, what's an iShare? It's an ETF. Well, so we launched those things too. And of course it got picked up and today it's owned by BlackRock. But I mean, we know those guys. I know personally those guys very well. And I mean, Fred Ibarra was a very good friend of mine or is a very good friend of mine, and he was the intermediary between Wells Fargo Investment Advisors and their acquisition by a pair of companies, and of course it ends up at BlackRock. But when you get right down to it, I mean, that's a perfectly reasonable way of looking at the world. And little by little reason prevailed.

Earlier, you flat earthers as an analogy for people believing in active management. Now there are still flat earthers around today. You started this index fund or you were involved in starting this index fund revolution 50 years ago, and it's reshaped portfolio management and tons of assets are shifting, but tons of assets are still in active funds. Why do you think that is?

Hope springs eternal. I think a lot of people who are invested in equities start out with owning shares in a company that they have participated in the management of, and that company goes public and they still own shares, and slowly but truly, they're trying to figure out how to diversify if they're smart enough. But there's a residual psychology around owning a share of a company. And the conclusion of portfolio level reasoning is self-evident to those of us who think about it all the time, including you two guys, but it's not evident to everybody. Now, how long will it take before it is evident to everybody? One more generation, two more generations, five more generations? I don't know, but that's where it's going assynthetically. Little by little, it's converging on that conclusion.

So you were on the ground with David Booth when Dimensional was founded. Can you talk about the original concept and what about that idea? We know David talks about ideas. What was so compelling about that idea at the time?

Well, David and I go back to the beginning of time. David and I both saw something important, and not 100% independently, but maybe pretty close to independently. And that is that portfolios, institutional portfolios were dominated by large stocks. And if you stop and think about it, that's not unreasonable, because that's where all the bulk of the money is in the big stocks. But that just says that the small stocks are under accumulated in institutional portfolios. And the obvious answer to that is to create a portfolio of small stocks. That's what we did. That was the foundation garment of Dimensional. That's not rocket science, that's just simple logic, but I can tell you right now that there were a lot of people out there at the very beginning who didn't hear it very well. But once they got the picture, they got it.

And of course, today we think about it more in the factor sense than we do in the large versus small sense, but size is a factor, but is not the only one. And when you get right down to it, risk is even more important than size, but size and risk are correlated, the two are inversely correlated. The bigger the company, the less risk it has. But that doesn't go to zero when you get very large. By the contrary, it actually, again, assynthetically approaches the market as a whole. So, when all is said and done, it's not a very complicated picture. It's just the learning curve that everybody has to proceed along until they get the picture.

So Dimensional started on the basis or the premise of kind of like a small cap index fund, but we understand that Dimensional doesn't really make index funds. So could you try and explain the difference between a Dimensional fund and an index fund?

Well, an index fund, in strictly speaking, has its distribution of weights over the composition of the 500 stocks or whatever that is given by usually the amount of shares outstanding in that company. But of course it could be something else too. We were fussing around with equal weighted indexes at one time, is it will do short course and why that doesn't work. But the point of the matter is markets are moving around a lot. And a lot of it has to do, what I would call, not only just fads, there's some of that for sure. But where's the new money coming from? It's coming from small stocks. When IPOs occur, I mean, nowadays you can have $100 billion IPO. Elon Musk has that experience, but that wasn't very common, not long ago. I mean, if a company came to market for the first time, 50 or 100 million of market cap would be not uncommon.

So, there's a lot of dynamism in the composition of shares, not just prices, companies are buying back shares, there's mergers, there's spinouts, there's all kinds of stuff going on at the corporate level. So, there's a lot of corporate finance going on, not just financial economics. So, the combination of those considerations leads to the idea that you've got to have some kind of an intellectual understanding of the flow of shares themselves. So, we got onto that point in the early days at Dimensional, and we had some of that vision at Wells too. And I'm not saying that Wells alone had that vision. There were others that did too. But the point of the matter is that you can look at the world of shares just like the world of prices. And then you've got the dynamics of the way funds are flowing. So in open-end funds, new shares are being issued with regularity.

So the float is also a consideration. So, the shares being currently traded, because a lot of shares have been immobilized in portfolios that don't move no matter what. So there's a lot of dynamism and the number of shares going on into or out of the market. And just look at the IPO world in the last couple of decades. I mean, there's been a lot of IPOs in the last couple of decades. So, it's just the same old story, it's a learning curve that we've been ascending sort of step by step, and every time we find what we think is a new step, what we discover there is a new dimension.

One of the things that we hear is a concern about indexing just as it continues to grow is it could potentially get too big and start distorting market prices or governance with companies. And I think Bogle had this concern as well before he passed. Do you have any concerns about indexing getting too big?

Well, it's somewhere around 40 to 50% of the market now, but not strictly speaking indexing passes would be a better way to put it. And passive doesn't necessarily follow the number of shares outstanding. Yes, I think that's a concern, Ben, but I wouldn't number it among my top 10 concerns. I think the danger is on the other side of that coin. I mean, I think it not going far enough is a bigger concern than two far.

Do you have any concerns about factor premiums going away as it become more and more popular?

Well, that's a very good question, Cameron. There's some deep roots in that question. Remember, factor analysis is partially imagination at work, because you have to imagine a factor before you start looking for one, unless you do just flat out data analysis, analysis of variance. We do a lot of that these days at Dimensional. And we're not the only ones who are just looking empirically at what factors show their heads. And when you start looking at the Tokyo First Section or the EMEA or the whatever, you find different factors.

You can extract different concentrations as it were. Some of that is a function of the nature of the markets that were formed. I mean, it's not surprising that certain countries have companies that are dominated in certain minerals, because that's been their comparative advantage. I mean, not everybody mines gold, but when you get right down to it, we're all examining the world through the lens of factors. It's just a question of how far down that road you let the analysis run. And my feeling is the data will sort that out. And I think there are plenty of people that are all that same mind.

You've made significant contributions to finance, which we and our clients benefit from. You're also an environmentalist. What practical steps do you think people can be taking in their day to day lives to combat things like climate change?

Well, that's a whole another book, Ben. At Sonoma farm, as you may be aware, we've created a micro grid where 100% of the power that we consume, I mean, you see all the lights on here, it's all coming from the sun. We haven't been connected to the local utility since the 20th of December 2019. And my marginal cost of electricity is zero because it comes from the sun. My marginal carbon footprint is also zero, because it comes from the sun. The problem with carbon is it has a big residual effect, dump CO2 into the atmosphere and it lives there for somewhere between hundreds and thousands of years. And it's not new news that CO2 is a insulating blanket that surrounds the planet and it prevents re-radiation of the incoming sun's rays from radiating back out into space and block the infrared.

And I think the basis of understanding that I have and my colleagues have, that have been working on this, trace it to those simple set of facts. But the truth of the matter is solar panels, like one of my professor friends at MIT points out, the cost of a photo cell has come down 98.6% per KW in the last three decades. And he says it's going to go down another 90%. Well, for all intents and purposes, photo cells are free. What's not free is the structure that holds them. And then of course you have to hook them up. You got to think about the systemic aspects of it, not just the photo cells.

So, we're really big on the idea of storing energy in the form of hydrogen, not just batteries, but I'm very fond of pointing out that if you take a cubic foot of batteries, the best ones on the planet versus a cubic foot of hydrogen at 3,500 PSI, the amount of energy in the hydrogen is 1000 times the energy and the battery. And we have no limit on the amount of hydrogen there is available. We have definite limits on how much of the components, the electronic components of the battery. Plus the fact not at the margin free, I mean, decomposing water is not free either, but it's extremely efficient relative to other means of getting hydrogen. Well, the world is waking up to all this stuff. Now.

So Mac, our final question for you, how do you define success in your life?

Yeah. All it does is really amplify my curiosity. I mean, of course it creates wealth too, I'm not denying that point. But when I think about what we don't know, I'm more intrigued than by what we do know. I'm very fond of pointing this out. I'm not very enthusiastic about the political system. And by that I don't mean the American political system. I mean, all political systems. There's no accountability. It's not a data generated process. Look at what we've learned in financial economics because we've got data. We, human beings, create regulations, implement regulations, and we don't set about studying the consequences. The first major regulation to have its consequences studied is yet to occur. I'm not a very big fan of that.

Well, Mac, this has been an incredible hour. I want to thank you so much. We are very gracious with your time. You've had an incredible career, a huge impact on Ben and I and all of our clients. So thank you very much.

Hey, welcome, Cameron. I enjoyed the conversation. Thank you very much, Ben. Hope you enjoy yourself.