John Authers, Christine Harper Discuss ‘Capital Ideas’

nine years at The Financial Times. The first book in John series is from Peter Bernstein. For those of you who are not familiar with Peter Bernstein, he is the Michael Lewis of his day. He began writing in the sixties and seventies. The book that we talk about today is Capital Ideas, The Improbable Origins of Modern Wall Street. Bernstein published this in You probably are familiar with some of Bernstein's other work. I Just Adore Against the Gods.

The Remarkable Story of Risk Uh probably his best known work, which tells about the rise of probabilities and statistics and actuarial tables and the insurance industry and why modern finance Oh, such a great debt of gratitude to the early people who were working on statistics and mathematics. You know, back in the day when ships would go overseas and try and come back with spices, it was a risky and

dangerous venture. The ability to ensure those trips, the ability to figure out the odds of safe return and build in a reasonable um compensation for those who didn't come back, well, that was really really important, and that was developed by early statisticians, and probability for your risks. Eventually that becomes the modern insurance industry. John wanted to focus on a book of Peter Bernstein called Capital Ideas, The Improbable Origins

of Modern Wall Street. It tells the history of how modern finance developed, and really it's quite fascinating, tracing the pioneering work of early scholars to the development of new theories on risk and valuation and returns. Really a very interesting book. So let's jump right into our conversation with John Authors and Christine Harper discussing Capital Ideas by Peter Bernstein. What made you guys start with this book? Given the what is it three hundred thousand books published annually plus

the seven hundred thousand self published. Uh what what made you go back to Peter Bernstein as the first book to experiment with this? I feel it's very important actually to look not just at the books that have just come out, but at the books that have been that have come before, and that we may no longer have been paying attention to, because often there is information that's hidden there in in clear sight. I'll give you one anecdote to back that up. Donald steel of the Barlat

and steel Um Investigative Journalism Partnership. They want a bunch of bulletz is for investigati journalism at the Philadelphia Inquirer came and gave a talk while I was at journalism school too many years ago to think about now. Somebody asked, where do you get most of your scoops from? Where's

your main place you get your scoops? And we were all expecting from you know, underground, dark park car parking lots, from anonymous sources or whatever, and he said, from rereading my old notes, you find out you talk to people, you talk to twenty more people, and then when you go back to the first person you talked to, you realize now what the critical question is and that they

answered it for you. And I then discovered I've not written that many books myself, but I've discovered precisely that has happened that on trying to unlock the key of a narrative, try to say something clearly, it's often going back to much earlier transcripts that had sort of said your treat become a sentiment in my mind, and that I hadn't actually re examined, actually gave me precisely the clarity answered the questions that I was asking again forgetting

that I actually had the answer to them sitting in my notebooks. So that's one critical part of it. I feel very strongly that we shouldn't just be looking at the books have just come out. In the case of capital ideas, Partly it's very very good nobody was going to say this isn't a very well written book, um. And also I thought it was very important to look at these ideas written at a time before the crisis, because for the last ten years I'm as guilty of

this as anybody else. The crisis was the most exciting period any of us who have been long term financial journalists or working finance have ever known, and for the last two years, it's been almost impossible to look at anything other than through the prism of that crisis. And that's particularly true of some of these ideas that are mentioned by by BENSTI I thought it would I thought it would might be very revealing to take a look

at them, what people were saying about them. Isn't it true that whatever we're looking at, you know, the expression is every general fights the last war. Don't all market commentators and indeed traders and investors have their perspective colored by whatever the last big disaster was. We would still be talking about the dot com collapse and the crash of technology and why value does so much better than technology, but for the financial crisis intervening or am I overstating that?

That's absolutely right? And I think one of the one of the things a lesson for me and I was journalists covering the financial industry during the crisis, and I think that very much colored my perspective on finance in that I saw the reliance on financial modeling and sort of statistical assumptions as flawed, given them flaws that were exposed.

And what was valuable to me in reading capital ideas was recognizing in that book how important those models were and that they just haven't been with us all forever. They had to be created and they were very valuable. Maybe they were taken too far. I think people would mostly say they were, but without them we would be in equally as much trouble. So that everything is sort

of a reaction to the last problem we had. And with capital ideas, there were too many people who just thought human judgment was the way to pick company stocks, and um, you know, they showed there's actually systemic you know, analysis that should go into it. But maybe we went too far and there was too much systemic analysis, not enough judgment. What what do you what models? Do you

think we're pushed too far? And it's one thing if we talk about um, the Gaussian Coppla and things like that, but specifically these are really very basic ideas that eventually got implemented. It's kind of funny to read, oh, this is the person who figured out that reward is a function of risk. I just always assumed because it's been so fundamental to me, it's hard for me to imagine. So the parallel is, you know, kids today who play with iPads and technology and apps, there is no, online

and offline. There just is if you're old enough, oh this is online, this is offline a six year old. No, No, that's just how the world is. It's digital, it's this, it's that. So to me, risk and reward have always been two sides of the same coin. It's hard to even imagine what it was like. Wait, people didn't know that that your reward was a fun shouldn't have how

much risk youer storm? Right? And yet there there's this a kind of inherent belief that we can measure future risk by looking at you know, John has had a lot of online discussion about this. Volatility is telling you future risk and that helps to a point, but not maybe all the time. And then also liquidity, you know, the assumptions about liquidity that we're going on during the crisis or the build up to the crisis, we're very flawed. And so those those are two things that I think

we're we're problematic. I think in finance, if we essue the word measure and replace it with the word estimate, we're much better off because hey, I'm guessing this is how much liquidity will be until it evaporates, or we're estimating how much risk there is. It creates a recognition that this isn't a hard and fest measure the old joke, why do why do economists for ideata to the third decimal point to demonstrate they have a sense of humor?

How did How did people respond? I would say that we had two main areas where people had a problem, other than points of people pointing out particularly nice little gems of Bernstein wisdom. The first was that many people didn't quite grasp that risk in these models has been defined as volatility, and many of them felt, I think, quite accurately, that there is much more to what they think of as risk than the version of volatility that Sharp and others put into their their their their models.

Let's put a pin in in right there and and digress a bit. Why do you believe people think volatility is equivalent to risk? It's, largely speaking, that's how it's defined. If you look in the models that in its final form, I guess Bill Sharp comes up with, and the Sharp ratio, which we're all used to as a risk adjusted return is is the return divided by the standard deviation, and so it's um And while it's plainly very important to

grasp that you get money, you're you. You get money by taking a risk that if you really want to make yourself rich, you're going to have to take a chance. Um the risk that people are bothered about. For many institutions, it's about matching their liabilities, meaning the future obligations they have on a even surprisingly to know. Even endowments are worried about whether they can match their commitments for the future.

And it's about to draw down. It's not about will this return waggle around a long way over the next thirty or forty years, but on balance particularly I don't have to access it all at one time. We're going to be fine. It's is it going to do very well for a long time and then crash and I'm never and subject me to a drawdown I never quite recover from. Uh. And that is much closer to the version of risk that people had in mind, and it's not the version of risk that's enshrined in in capem.

The one from the book that I really liked was more things can happen than will happen, which is really a variation of the classic definition of risk, which is the possibility that your future expected returns will not be met and and that's a pretty simple definition as well, but they both sum up. Hey, you know, if markets return x a year, let's use ten percent over long

periods of time. There are certain years where you're not going to get ten per and that's risk, at least to an investor who may need the money at a specific date in the future. Part of the issue, I think is that if you're an academic and you're trying to create a essentially a mathematical model, you need you need some number, some input that you can put in that model. And so what are you going to get

to measure risk? What's the number? Volatility is a number, So maybe that's the closest you can come and it and it responds to John's reference of of drawdowns if you need if you have a specific liability at a future date, and right before that date, one of these big, ugly drawnouns of cars. Just look at what took place in the fourth quarter and the first quarter of en If you needed that money in December, you were in trouble. If you could wait till April, Hey, it's all everything's

coming up roster. So it's not true risk, but it's volatility combined with liability. Is that that a fair statement? I think I think it is that sits following on from what's from what Christine just says. Yes, it's important to have a number, but there is a risk that you drift into the fallacy. This is a comment that all one person made you drift into the fallacy of the street light effect. I didn't know until now where

the street light effect name comes from. It's about a drunk who is looking for his keys underneath the street lights, and the policeman asked, you're sure this is where you dropped them, and he says, well, no, but this is where I can see I mean, and that is I mean back to the financial crisis and what were some of the mistakes is that the data that was available on housing prices was plugged into everybody's risk model on you know, that's my second flag because we have multiple

examples of enormous draw downs in housing prices which nobody wanted to answer into their system, the biggest clearly being the Great Depression, whereby some measures, New York City real estate, film value, and real estate collapsed around the country in price. But there are other examples in California in the nineteen eighties and New York. But but it wasn't the argument that nationally housing prices have. And I agree with you on the on the Great Depression, but they probably that's

not gonna happen on average. But real estate is local. And the joke is if my head's in the oven and my feet are in the freezer on average, I'm comfortable. Well, okay, but I'll just say that the models that were employed did not use data. Yes, whether it was available or not, I agree, they chose to use recent data, which basically told them what they wanted to hear, so their free light was a little too narrow. That's that's exactly right. But but that goes to your point that models get

pushed too far. And if it's garbage and garbage out. If we're only going to take an era, we're not gonna go out of sample, we're not gonna go into national, we're not gonna go back a hundred years. We're only going to use The ultimate back test is only use data that gives you the result that you want. And Burnstein makes that argument. I mean, he does say in this book that your your models are only good as good as the data you have, and so he was

aware of that. But it's interesting how far the models were pushed without understanding that. One of the one other interesting thing is how much you see in the book how some of these models are based on simplifications which the people know they're making in order to be able

to render it um u usable at all. Now, the one example I'm really thinking of here is Bill Sharpen the concept of beta, so that the idea, the idea that the whole, the whole basis of the valuation of a stock is based on its sensitivity to the market as it's one most important overriding factor. And the reason that he came up with that because yes, it is more probably that's the single most important factor in why

most chair prices move. But the reason he came up with that is for for to make it calculable, because you had to have one overriding factor and then add on others thereafter. If you wanted to make the math doable, you need a number. And and you know, beta, particularly with the growth of passive investing, arguably is even more important than it used to be, but excus attention in ways that might be dangerous, and it helps it because

it's such a nice, clear cut number. It gives us the comfort of a clear answer that we forget that it was based on what was knowingly a simplification when it first came out. The reason we are calculating things with the notion that beta is the single most important element of the return of a stock is because it was just too difficult to calculate if you were going

to have a number of different factors. That chapter in a later chapter references the variance and the correlation between individuals, variants between different parts of portfolio, but also how margin visual stock will trade relative to the market. And something I have been told since I first started trading stocks a hundred years ago is that a third of the price movement is the stock, a third is the market, and a third is the sector that's referenced in the book.

But nobody ever bothers to define that. Has that was that tested in here? Has anybody actually said, well, here are all the correlations? Are we just all taking that for granted? I think Farmer in French tested it did well. They did enormous empirical work which basically disproved the contention that market sufficient in my opinion, And yet reached the conclusion that markets were efficients, but that here were all these inefficiencies that could be explained somehow or other startastics.

I don't, I don't quite. I think they did a brilliant piece of empirical work, and it's wonderful that they published something which basically suggested the original hypothesis is wrong. Well, well, I'm not quite sure that I agree with them that the original hypotheses is right. Nevertheless, you need a catchy nomencl you need a catchy title, and the mostly kind of sort of eventually efficient market hypothesis. I don't know if that's when any Nobel prizes, even though it's much

more accurate. Yes, well, I mean the problem with the efficient market hypothesis that's it relies on a lot of people going in and trying to beat the market. Um, which we've seen and and some people let's talk about Professor Andrew Low and m I T. He's argued that you need five or six active market participants ninety plus percent can can index, and that should be enough to for for price discovery to work. Um, but what's in it?

At some point? What's in it for the active market participants? Well? So, so now I'm gonna I'm just gonna keep dropping names. Michael mob Us on the Paradox of skill, effectively says that you it's not hard to beat the market because people are dumb. It's that there are so many smart talented people and there just isn't that much outpha to go around. So maybe if many of these smart talented

people go away, it's less competitive. And I don't know where the number is ten percent, Andrew's five percent, those folks will have an opportunity to beat the market. And some people say that what people believe to be a scale, it's actually blind luck. So let's talk about Bernstein personally for a minute, because what you just said seems so much of an era that may or may not be valid any longer. I was surprised in the book to read him discuss his clients and his own participation in

the market. I had no idea that he was a professional investor and an advisor. I assumed he was a professor and or a historian based on how well researched and written Um The Power of Gold and and Against the Gods. These read like academic books that are just beautifully written. So here's the question, for a person in a post war era where the you know, the thundering herd of Merrill Lynch and and all the different things

that we're taking place. In the fifties, sixties, seventies, it seemed like stock ownership was moving from a rarefied wealthy person's hobby too fully democratized and here we are now back to bigger levels of of wealth inequality, and it seems what, what's the stat everybody likes to throw out the stocks and roun by the top ten percent something like that the top one percent owns so have was Bernstein of the moment in democratization and extrapolated that trend

out forever? Did he? Did he? Or am I overstating that? And just I would just say, I mean one point he makes is that in you know, uh, capitalist countries like the US at the time he was writing, it's assumed that markets are good, and the countries that were coming out of the Soviet you know world like more. You know that Poland was very excited about having a stock market. So there has been a democratization of markets globally.

So what's interesting, and we've documented a little bit in various articles we've written, is that if you look in some what you call developing markets around the world, they're very keenly developing these public markets, whereas some of the more sophisticated markets are now going into more private markets.

And so I I just find that fascinating. Whether there's a sort of a the you know, a curve at which you know, societies go beyond private markets into this world of making privately owned companies more you know, widely owned or more of an investment, an opportunity. We have a very specific legislative history with the Jobs Act under President Bush that basically change the game for private companies.

And it's not a coincidence that what is it a decade later we have all these unicorns billion plus doll evaluations that haven't gone public. Well, and you would have had no choice, but and you have you have you know, lots of pension funds that owned venture capital, they own

private equity. Right, So in a way, even though it through multiple layers of institution, you have the average person owning pieces of non public companies, the average person through I mean public they employees through their own and others, you know you and yeah, it's still small. But I think the question is and I think a lot of people in the industry would say that's the future. I mean, you hear some quant traitors talk about bringing quant strategies

to private equity. Um, I don't see why you couldn't have an overlay of quants onto anything that could be reduced to a mathematical basis. The problem with that is so much of this seems to be intuitive and um, what's the word I'm looking for, um, driven by human judgment. There are areas where machine learning and AI and technology are clearly supplanting human judgment. I am I'm not so sure that that a VC and and p E or the places where that's going to happen, although I could

be completely wrong. Well, and there's those liquidity at you. Well, that's the always the liquidity premium for vench capital and private equity, and the same thing with gated withdrawals and and um, you know lock up periods for hedge funds. You end up with, is it purely a liquidity premium or is that just you know, something to create a little smoothing for managers. Not On the subject of liquidity, we've actually managed to come to the second big points

that people made in their sponsors to um. There is very little. The word liquidity does not occur half as much as you think it's would in a book about all these fundamental ways in which people go about allocating their assets in public markets, and not unreasonably a lot of these these these people are geniuses that we're covering. Most of them at the time they were developing their theories had little or no experience of actually trading in markets.

They were very interestedly looking at lots of data and bringing very fresh perspectives to it, and they were certainly operating in an era before the degree of liquidity that we have found in the recent years was possible, and therefore where the sudden changes in levels of liquidity of recent years was possible, and you could try to to say, well,

you can just add liquidity as a factor. Ipotson's suggested that in recent years that low liquidity stocks could be a factor along the same lines as value or momentum or whatever. The cap size argument has been the premium you get for small cap over large isn't is in part a liquidly factor? Yes? But I think this is where the where people were nervous about the discussions of risk. The original risk models UM. The level of liquidity is very important and it's not exogenous. If things begin to

go bad, there will be less liquidity. When there is less liquidity, the price will move more, and that will be get still more in liquidity UM. And We've had some very interesting quite technical, so I'm not going to try to summarize them, but interesting responses from options traders. Basically, I suppose the very simplified way of putting it is when UM, when volatility goes up, correlations go to one.

You know, all their all their clever ideas disappear, you know, the various ways they've tried to protect against risk gets much more, much more prejudiced, much more compromised. When liquidity drives up. Everything comes down to the same thing. And the concept as well that when liquidity is drying up, you sell what you can sell, not what you think is worth can reach a higher price than it's worth. You sell just whatever you can sell if you need

to sell something. So let's talk about three things. One is liquidly, one as correlations. But I but I have to bring up the portfolio insurance which was affected via options to be purchased in a crash. Now I know, I have the benefit of hindsight bias when I look back at this, But isn't it obvious that in the midst of a crisis, in the midst of a crash, buying put options that are in free fall are a not going to cover your shortfall and be gonna make

the crash even worse. How did nobody point that out beforehand? And again, Bernstein has also the benefit of hindsight bias because he wrote this five years after the eighty seven crash. Yeah, I mean, it's just a good idea that was taken too far and was because I think in hindsight it sounds like a terrible I think if it were on

a smaller scale, it wouldn't cover your losses. Well, it might not, It might not have driven things the way that that there was this sort of self uh, a flexive kind of quality to it that there was, so there was there the amount of portfolio insurance I was owned really too much added to the problem. So if if it was if it was done on a smaller scale, it might have been okay. And I wonder if if the seat belt effect applied, which is as we make safer and safer cars and at abs and air bags

and seat belts. The death rate has fallen in plateaud and the only explanation that seems to make any senses well, people feel so much safer they drive faster regardless of conditions. So all these safety devices don't help us other than letting us behave a little more recklessly. Did portfolio insurance have the same impact? I think it's indeed, um what I would say if you. Because Bernstein was an extremely

bright guy. Some of the comments he makes and the quotes he makes about the about Black Black Monday are very telling because they make clear um what the problem was and that the people who brought it up didn't

really grasp it themselves. So Bernstein, and I'm quoting here that the shortfalling plan sales was a direct result of frenzied conditions that violated the underlying assumptions of portfolio insurance that ready buyers are always willing to accommodate the sellers in the insurance camp, which obviously was an assumption people forget, and liquidity is a fancy word for a ready buyers exactly.

And and they realized that the problems of portfolio insurance in the crash were related to problems, and this is a quote from Haye Neyland. They realized that the problems of portfolio insurance in the crash were related to problems of market liquidity, not to some fundamental flaw of the underlying technique. If it's a problem with market liquidity, surely that is by definition, if it's a technique for buying and selling in the market, if probably with market liquidity undermines,

it sounds fundamental to me. And then this glorious quote that Rubinstein, the other Leliand's partner in this the two gentlemen behind Flier Insurance who have taken a lot of the blame for Black Monday Um deservedly, Yes, bern Bernstein quotes into this effect. As a result, it was the market of that failed to provide conditions where portfolio insurance could work multi market, the market mass with the model.

It's it's really stop and think about that rationalization, which brings me to something that that is related to the correlation and the volatility issue. So when when volatility spikes and all correlations go to one that very much hints at the behavioral issues of market participants, which as much as this book talks about a lot of theories. They all seem to predate the diverse Ky and Conman and

Sailor and Chiller and go down the list. There is almost nothing in this book that says, hey, sometimes back to E. M. H And and Fama French, sometimes investors are just plumb crazy and do such stupid, self destructive things that all bets are off and you just have

to wait for the smoke too. I think there there is an anecdote about black Sholes and how me Merton Black Controls tried to try to put their theory into practice and and bought some options and and did some trades, and they lost some money, and they realized that, Um,

sometimes the market knows things that the models don't. So I wanna I want to ask Christina a question about something John said earlier that the two gentlemen who won the Pulitzers at UM Philadelphia Inquirer always go back to their notes and later on in the conversation it's what was written earlier but lacking context, um to be better understood. In the early part of the book, there's a quote from I'm sure I'm gonna mangle his name, Bachelia. How do you pronounce okay Um? I spent a very much

less time in Paris than you did. Um, but I love this concept from It's so far ahead of the rest of the book, which is quote, the mathematical expectation of the speculator are zero. Now stop and think about that. It's it's foreshadowing what a zero sum game is in markets. It's foreshadowing indexing, it's foreshadowing passive over active. This is a hundred and twenty years ago. How on earth had did that just sit there and nobody noticed it for

I don't know, almost a century. It's amazing. Yeah, and it and it it's and fuel every investors um insight into what they're doing every day. So we should just haven't taped to our wealth right right to your to your trading term. So given that we have all these PhDs today, we have all this work from Nobel Laureates that makes the canon of investing. What should investors be

picking up from this book today? What's what's the takeaway that professional investors should be thinking about if they either read or reread this book. To me, it was the value of the economic ideas that have been um absorbed into the financial world and the limitations it's not just the value, it's the limitations. Hey, this is a better idea than before, but let's not get too far out of so you're not you shouldn't go with your gut, but you you shouldn't assume the model is gonna fill

you with total confidence. But what are your thoughts? Do you do? You think that's fair a fair statement? Yes, sorry to be boring, and degree agree. But basically these models are good models given that they're trying to model something that all of us know from our lives. Trying to cover markets are almost impossible to to model. Um they are in most of the cases. There are things that when you're trying to work out how to allocate assets, pick a stock or whatever, you should at least take

a look at the math of them. And if they are if they suggest that this would be a really bad idea, you should think very hard. They are You know that they are a systematized way to enable you to think rationally. They aren't the kind of infallible guide that some people felt them to be. And ultimately, the reason they became as unpopular as they did, because they were blamed h as much as they were for the crisis,

is due to factors of overconfidence. They did feed in, among many other things, to this broad over confidence that allowed the crisis to happen. So so here's a couple of bullet points that I pulled out of the book that I thought were fascinating and and maybe maybe you

guys can can share some thoughts on this. The first was I had no idea that before the nineteen fifties, if you had a trust or in a state that was being managed by a third party, the law was literally you can only have a fifty exposure to stocks and the rest had to be bonds or cash instruments. That was fascinating. Did did you did either of you before you read this book know that that was a substantial change in in how portfolios were managed. I I

didn't realize that. But it makes sense in the wake of the depression that so ben those PTSD people are again, the generals are looking back and oh there can be a crash. So therefore no more than that was the guard rail. Well, again, it makes sense. I I covered Mexico for a while in the wake of the crisis. I had to cover the moments um more than a decade after Mexico's great financial crisis when they allowed the state's pension system to invest in anything other than bonds

for the first time. It took huge negotiations with the unions before they would permit them to put put retirement money into anything other than bonds. But again, given what happened to Mexico in ninety four, you can understand why the unions thought this might be a bad idea. And I don't want to give short shrift to Paul Samuelson, John you just mentioned earlier, So let me ask this question, why did Samuelson's work send such shock waves through the

regular community of investors. I think there's a beautiful anecdote. Um it's actually Sharp that has the conversation with Burn's been rather than Samuelson, but about Samuelson's work. That just Bernstein is talking to him about the investing he does h and Sharp says do you beat the market? And Bernstein is slightly offended at the time and also goes, well, how would I know? How would you judge? Which is

astonishing in and of itself. It's that's less than fifty years ago that conversation happened, and that was the moment that Bernstein really started looking into all these ideas and taking them seriously. That was literally his epiphany right then, and they're sharp forced him down this bath. And and that, to answer your question, is also why people find found Samuelson so shocking. It seemed obvious that people who knew

what they were doing would deliver value for you. The the idea that they actually could not not not not just did not could not add value in the act was just mind blowing. What's astonishing to me about that point in the book, which is actually fairly oh it's a Bill Sharp chapter. There was no performance reporting. No one said here's how we did this quarter, here's how

our benchmark. The concept of benchmark did not exist. It's it's mind boggling, isn't that you deal with professional investors who live and die on their quarterly benchmark and complain about people trying to make them do monthly or weekly? Which is But isn't it interesting how far we've come that now? It's I think what's more commonly complained about now is how much people look at the benchmark instead

of that, instead of looking at absolute returns. Right so that you have funds said brag about making a minus one percent return, you know, because the index was down and you know obviously that wouldn't have happened in the fifties. Well that and that that least the very strange concept. Um. I find this this, this, this, this is the point

that somebody made me extraneously. After after reading this, you come to the what a lot of these ideas weaken is the concept the sense of ownership, so that now you can be in a position where you own a lot of a stock, but you're underweighted. So for example, if in Britain you more or less have to have more than ten percent of your portfolio each in BP and SHELL. So if you decide only to have five percent of your portfolio in BP, then you are underweighted.

You own it, but you want it to do badly because you are betting that it will do badly even though your clients have five percent of their money. Right, it's about tilts, not absolute ownership. But but yeah, but the concept of if you own it, you're rooting for it has disappeared completely. I want to bring this forward to the modern era. There it was a quote um from Bernstein about industrials did not need as much capital as transports. That makes me wonder industrials did not need

as much capital as transport. So if you're putting up a factory, you need need less money than the transports or the rails who had by rights of ways and and lay all of this track and then quote unquote rolling stock a phrase that you just don't here today. Um, So what does that mean about tech stocks today? If if Facebook brought Instagram for a billion dollars when it was I think nineteen or nine, maybe programmers um follow the progression. Rails and transports needed a ton of capital

and a lot of labor. Industrials needed a little less capital and somewhat less labor. Modern tech companies need a whole lot less capital and just a handful of labor. What does that say about valuations based on the ideas in this book? Are we looking at perhaps a shift that has allowed pe multiples to climb for the past half century? Interesting question? Um. Certainly the notion ideas like like Topin's Q or trying to come to an intrinsic value that is based on assets, need to be revised

with the notion of very much. For the notion of intangibles, Intellectual property is different than factories and equipment there is a concept that Bruce Greenwald, who I was taught by my MBI that Columbia uses of franchise value and of earnings power. I that that Facebook may not have a lot of capital tied up in a lot of workers working, but it does have a certain amount of franchise power,

which conceivably is weakening as we speak. But that's that is the measure you somehow have to hear the mot Yes, always we need to have a moat around your business

and prevents competition. So so that was the first question, and I think you've you've sort of I don't know if there's an answer, but at least but I think, I mean, it's interesting that just this idea that a company's ability to access capital should be dependent on its need, right, because now I think people will give capital to companies that don't need it so much and then just a lot of executives get paid a lot of money. Well,

there is that with all the buybacks. We just saw Netflix raise another two billion dollars at five percent, because hey, content is expensive. Um Uber has had no problem raising capital even though they've just burned through a ton of it. You could you could go down the list of of tech companies and unicorns that are so heavily cap Look at we Works, which just filed to go public. They bought the Lord and Taylor flagship here in New York,

which is a giant block long um department store. The issue of capital flowing to places where maybe it'll be repaid, maybe it won't. It's kind of shocking, isn't it. What what does that say about that? But the question I really have to ask, So the book has written in all of the academics Harry Marko, It's Bill Sharp, Gene Fama, go down the list. Are all born you know, either

certainly before World War two for the most part. In fact, I want to say just about everybody was born before World War two, and most of them did most of their work in their twenties, thirties, forties, which raises the question is there a person born after who one day might be mentioned alongside of them? Has has all the low hanging academic fruit been picked? And this is going to be the pantheon? Or are new up and comers coming about who you know from the world of millennials?

Are there going to be any academics who can put out work of this stature and this influence when you mentioned the behavioral economists for sure, so I would none of whom are under fifty. Okay, Um, well, Andrew Lowe, who is also beyond fifty at this point. But Andrew low what he's attempting to do, which has come up with an adaptive markets hypothesis that is advance. Yes, I'm not sure he's quite managed to do it, although he's written fascinatingly about his attempts to get there. If somebody

does get there, that would be very interesting. Indeed. So that's my conversation with John Author's he's a colleague at Bloomberg Opinion, and Christine Harper, she's the editor in chief of Bloomberg Markets mag zine, about Peter Bernstein's book Capital Ideas, the Improbable Origins of Modern Wall Street. If you enjoyed this conversation, we'll be sure and look Up an Inch or Down an Inch on Apple iTunes and you could see any of the other two hundred and fifty such

conversations we've had over the past five years. July twelfth is our five year podcast anniversary, so be sure in swing by and check out some of the special features. We will be running that week. I would be remiss if I did not thank the Crack staff that helps us put together these podcasts every week. Robert Bragg is my audio engineer. Attica val Brunn is my project director. Michael Boyle is my producer slash booker. Michael Batnick is

our head of research. I'm Barry Rehults. You've been listening to Masters in Business on Bloomberg Radio