In Pursuit of the Perfect Portfolio: Eugene F. Fama

you you hello I'm Andrew Lowe and welcome to the project on in pursuit of the perfect portfolio I'm really thrilled and honored today to be talking with Eugene fama then 2013 Nobel Prize winner in economics and the founder of many ideas in modern finance not the least of which is of course the efficient markets hypothesis Jean thank you very much for joining pleasure so I want to start today by talking a little bit about your background only going back to the old days when you were a high school student you were actually a jock weren't you writes dillion I see Figures yeah so what what sports did you play and when high school passionate about yeah um I played baseball for two years we lost in the semifinals of the state championship football we won the state championship when I was a junior basketball I was never very good at but Trek would you believe that I was second in the state in the high jump I heard that that's pretty amazing the only guy that beat me was the first American to jump over seven feet Wow and but he didn't take off a sweatsuit before he beat me you lived around in Philly so with all that how did you end up getting into economics oh well I thought I was going to be a high school sports coach in a teacher and I was majoring in Romance languages of all things and but I was getting sick of that really sick of and I took an economics course as a junior at tuft yeah tough ceará and I loved it so and I was pretty good at it so I stuck with it and was it professor Ernst yeah played a big role well he he hired me to work with him it was between my junior and senior year he had a stock market forecasting service and my job was to come up with trading rules to beat the market and did you yeah I always did he always worked a really sample I never had a sample okay but he always had me keep an out-of-sample a hot portion of the data and I just found out because I I wanted to see if he was still alive he's not but he was actually a premier athlete a golfer really he's in the BC Boston College Hall of Fame which is one good yeah does it golfer uh and so what made you decide to go to grad school then oh because I didn't want to work for a living um I figured it becoming an academic was a way to keep my sports life going and set my own hours so I could keep keep it all together and it worked out quite well I'll say and so Chicago was whole Chicago story how I came to Chicago yeah I applied because my professors at Tufts all of whom were Harvard econ graduates and I said I want to go to business school not to an economics department they said well go to Chicago because that's the only one that has a an academic orientation they didn't mention MIT by the way he's a hotter develop so I applied here and I never heard anything in comes April I call and the schools very small at that point of the Dean of Students he answers the phone he's doesn't even have a phone anymore huh it doesn't talk to Stu anyway he picked up the phone I'm chatting with him and he said well what I said what happened to my application he said we have no record of your application well and he said well what kind of grades do you have and I said pretty much all A's and he said well we just happen to have a scholarship for somebody from Tufts do you want it wow that's amazing it's serendipity without that phone call would have been very different I thought they never even accepted to lots of other places yeah um we came here but Chicago is the place for you yeah okay and so at Chicago who did you end up working with and who at the moment is for you looking back at that time this is long before your time france courses were ridiculous and you didn't pay to take any finance courses so I took all my courses and most of my courses in economics and when it came time to write a thesis you know we're in the early 1960s first computers are coming about so everybody's getting interested in doing empirical work yep and here was Merc Miller and Lester tell sir and benoit mandelbrot a mound to quite frequently and that was a way to get these people Lester Telsa interested in working with you I say and I had two kids so I want to get out as fast as possible so I thought doing something in this area would be would have that effect and it did yeah so in fact I think you owe Mulla first to actually use computers to look at the stock market I mean I I was using it and there was a guy in the physics department using it at night during the night because very limited capacity yeah we were the only ones you would call IBM and say this compilers not working it's doing this and they laugh so let me get you the second time they didn't laugh anymore right will you programming it Fortran yes okay and allocating 1,000 memory space okay there's a joke so your thesis was on the behavior of stock market prices ultimately published in real business but you found that the random walk is actually a pretty good description today at that point people hadn't really come around to talking you won't see the word efficient markets in that paper you won't write it before that people are kind of groping for what it meant if so first of all statisticians like Harry Roberts and people like that they were interested then when Lester tells her and the people at MIT who Paul Samuelson Kooten area of people got interested in it they started asking well how would we expect these things to help prices to behave if markets were operating properly and that was kind of the seeds of the efficient markets hypothesis but you go back to that point yeah we didn't have any models of market equilibrium right so they weren't aware of the joint hypothesis yeah problem they would just propose a test that if the market is efficient price places will be a random walk exciting like that yeah well in fact I think the last paragraph of your thesis actually called for more theoretical models yeah try to explain some of these asset pricing and nominees so it's very interesting and timely that sort of happened at the same time the cap em started the elevator yeah exactly two years later so out of that thesis what came from your mind in terms of how it shaped the way you thought about efficient markets was that a particularly formative experience looking at the data because many people think that theory came first but in fact it seemed like in your case it was a data no no it was groping for theory at that point right we're groping her off a theory I don't think it got codified until the paper that I had in the Journal of Finance in 1971 go where that's where the journey I brought this is probably ok was was stated the word efficient markets appeared in a little occasional paper that I wrote for the school here and then it got republished in financial analyst journal okay so that was the first place that I used that yeah it caught on right so I mean to say it caught on it's a bit of an understatement I stone why do you say that because it gets mixed with efficient portfolios right it's a yeah well but I mean the idea that price is fully reflect all available information I don't think came from you okay that I think had a huge impact and one of the things I don't think people realize is what the state of the practice of finance was at the time so how did your theory go across the practitioners what was Wall Street like at the time well Street at the time there were no standards about you know there were very few mutual funds like right and you are free to say anything you wanted right how what your performance looked like right and this was a direct challenge to say let let's that measuring and when we had the cap am came along a couple of years later and Mike Jensen wrote his thesis on you know the performance of mutual funds that kind of lit the bomb really right in the sense that now you couldn't get away without without actually testing how how well you were you were doing almost somebody else was going to do it for sure yeah so that that started the whole performance evaluation business which goes on to this day and right you always think you've seen enough mutual fund papers but then they'll be five more next year now it's a standard of the industry that you have to measure performance in a way then you outlined originally but at the time I would imagine it was pretty controversial oh yeah yeah you were not well-loved on Wall Street and I'm still actually well I don't know we could talk about that we hear that but it seems like that was a really big change in the way that academics were actually having to have an impact on the industry it was original impact before that right right there's no there was nothing there was nothing to go back and forth with right in an asset pricing or portfolio for Markowitz didn't penetrate when I joined the faculty here nobody teaching investments was teaching portfolio theory right this is 1963 Markowitz is thesis here was 53 oh but nobody was teaching it right no no yeah I went to Merton Miller and said what should I teach he said we hired you to teach the new stuff it was at each step three on teaching he wasn't he was teaching corporate finance but so I started I just took Michael it's his book and he ended it to the students right this is what we do yeah so you know you're known for empirical work and we're gonna continue on with that in a minute but I actually want to take a little detour about theory okay because you actually wrote a textbook called the theory of Finance Merton Miller it's a very popular was a pert Mary probably book at the time right now there are other books but still when it first came out there was nothing else like it and I actually looked at it when I was a grad student it's really hard and deep theory yeah right for example you've got dynamic optimization and they look great and that was a really surprise then you know somebody with a terrible back the reason I'm laughing is you know how we wrote that book now we were using it we wrote it in the process of teaching an introductory finance course MBA introductory yes that was it must have had some MBA so I'm not sure how many of them ever really got through it yeah that's what we wrote father that's how our perceptions of the market was so good but it actually ended up being a very influential book hundred students for many many years right so getting back to empirical work now so your your theory about efficient markets not they launched a whole host of papers right ultimately that really changed the industry in the way it worked how was your interaction with the industry at the time did you have any interaction or really was it just the force of the ideas well cause the change and how people started looking at more I would have a periodic interaction so Paul Samuelson for example was on the board of tiaa-cref and he had me go and talk to them about this stuff because they were just you know knee-deep in active stuff they still are actually but he wanted me to talk to them about what this new research employed for how they should do business because he wasn't have any effect right right and I did and I didn't have any effect on them either and that was kind of the experience uniformly there thereafter so I totally lost interest in talking to apply people because you know after a while I came to the realization they don't want to do this because it's going to kill their fees why would you want to go from 1% down to write fractions of several basis points to as your management fee they're not going to volunteer to do it yeah so at the same time you also mentioned that the cap M had been developed and people started to use that for an evaluation you obviously played a big role in that because the paper the farm of Macbeth approach to studying these factor models they actually had a very very important role in getting people to understand can you tell us a little bit about how you came to start working on that oh well so this is it was published in 73 but obviously you go back way before that in black Jensen and Scholes had written of still famous paper on testing that the cap band I officially was here at the time and he he would come in every morning early 7 o'clock and I'd be working there and we would argue and I kept saying Tim Fisher that thing that you're doing in that black Jensen shills paper it's just running a cross-section regression that's all it is they had this complicated portfolio approach right and I said you're just running a regression there and he said no I'm not yes they had no I'm not so finally I wrote that chapter of the look to prove to him that all it was was a cross-section regression and then I said well why not write the rest of that was how that arose in but that that paper became kind of the founding paper in cross-section regression approach to testing as a pricing models it was amazing because that approach you still used today is an incredibly useful way of thinking about selection bias being careful to make sure that measurement errors don't get caught up in the way you consider the portfolio's well I I think it has applications and more broadly in terms of you know very popular in economics front panel regressions right but that's a particular weighting of the data in which you great observations weight observations equally whereas in the family Macbeth approach you wait periods equally and you should ask yourself which way makes more sense right and I think the standard errors that you get out of the farmer breadth approach I'm much more much simpler to interpret yeah then what you get out of the panel regression approach when you put through to pass robustness right checks on it which are large sample properties whereas the properties in the family of this stuff for small sample preference yeah I mean you can certainly interpret it much more easily right it's a lot more intuitive simple oh yeah so that actually led to I think your Pharma French three-factor model the idea then actually it's not just the cap M it's nothing else going on is that right well or how did you come to that um if you go back in time so the cap in had a 20-year run basically and then like all models I mean so called anomaly static to come across well the first one was Roth buns is thesis on the small stock effect and then we had you know leverage you know the kinds of things geri-beri effect yeah a lot of lots of things came out so we wrote this paper in 92 which was the cross-section of expected stock returns in which we just pulled all the stuff - together and I didn't think that paper was a big deal actually I said there's nothing really ruin here a three factor model no that one didn't have the three factor model like that was just saying but the 93 paper yeah then the 93 paper that was different yeah the 93 paper was yes when we the 92 paper basically said there are all kinds of anomalies you can't put them aside any more and more important they're not more important but I mean in addition yeah the central prediction of the cap time just has never worked the relation between average return and beta has always been to flex right so that became known as the beta is dead paper right and the New York Times actually loaded that phrase is dead that's that's kind of that's not the right way to characterize it the right way to characterize it is there are too many other things that help explain average returns so that even if you had a strong positive relation between average return and beta you still have this problem that there are lots of other things that seem to be able to capture variation in average returns that that model doesn't get now you and Kenneth had a very long and productive collaboration for many years where's the state of the art now in the farmer French thinking what okay current perspective so we would based on that paper the 92 cross-section of expected stock returns we came out with this so-called three factor model in which we added every model of asset price every asset pricing model basically says the market portfolio is the core right and you start with that and then you know the cap M is the simplest version which that's the only portfolio you have to consider and then you have mertens extensions in which you have lots of other portfolios that are possible candidates hopefully attached to state variables and we kind of framed ours in terms of of that model although that's really a stretch because we didn't identify any right any state variables so I've come to the opinion that it's really what I call an exercise in empirical asset pricing in the sense that none of our theoretical models work yeah the most fundamental theoretical model is the consumption cap ban right it's hot all right it doesn't explain much for your kind so that one's kind of dead in the water the cap bomb is kind of dead in the water so I've kind of come to the opinion that maybe what we're doing is finding a set of portfolio's that spin the mean-variance efficient tangency portfolio and for a while maybe that's the best you can do so you use the characteristics of the data to identify what might be an appropriate model we haven't come to the end of it because you want to limit you know you want some constraints on that in that process you got to boil down to a small number of so called factors of portfolios that you use to explain returns yeah we're not anywhere near the end of that okay or even near the end of Ken and I are working on this right now how you test for model compression right um reducing the number of variables that you that you that you look at so I think facing that issue straight out is interesting and important but it's basically an empirical orientation of in many attempts to identify state variables that right explain these things but the cancer this from them from the beginning I said these variables are all just variants of price yeah so if a model doesn't work you expect them to pick up the dimensions of average returns at the model mix this is and it's not because they're related to any particular state variables they're all just linear combinations of different state variables and we don't how to unscramble right but how do you prevent the inevitable concern of data snooping where oh absolutely yeah real sensitive to that so I preached robustness in other words I want to see the same phenomenon so we use for example 63 to whatever it wasn't that 1989-90 yeah we've obviously extended it up to date sending on kids website he publishes the data regularly that's very helpful and we went back and collected the data back to 26 yep let's see if it worked and then we went out of sample internationally to see it for work so robustness is the key okay to all this stuff because you know we many of us out there using the same tapes right you're going to find stuff that's in there whether it's real enough right whether it's just sample specific so you robustness is by theme really all right so I'm going to come back to that when we talk about behavioral anomalies before we get to that I have to talk about your 69 paper the fama Fisher Jensen roll paper okay that's a paper that on the surface looks pretty straightforward but it was the first paper that really looked at stock market reaction many events in information right tell us a little bit about how you came to that how did you come to work on that problem okay so I things are really funny because his totals around uppity right so the crisp tapes had come out shortly before that right and Jim Lori who was he had solicited money from Merrill Lynch to put that together yeah and believe it or not he was afraid that nobody would ever use the tapes grisly it really and it's used by everybody that really shares Eric remix right so he said came to me and said can't you do something with this and I said well what what's on the tape I mean I had just finished my thesis where I collected my own data right and he said well we've got you know prices and everything is useful we have stocks but say that's the only thing that was on there it was stock splits so I said ok we'll do a study of stocks in Jensen enroll where PhD students at the time so I ended off to them to do the dirty work and that's how that paper developed so the methodology was something that you had designed just at that moment right for that particular issue because that methodology is now used not only by all academics it's actually used in industry I don't know if you realize but it is badly in court cases - exactly in court is used all the time they had ocular damages the notion to stand in there right those are details that judges may not get excited about but right but it's an incredibly influential paper yeah came about but I you know I unabashedly say it gave rise to an industry yeah well at least maybe two or three industries Miller out this is terrible but Merton Miller always said when we had tenure decisions in accounting most of the papers would be events that is that's just a tease but you know I turned that as dick Taylor likes they always have these little I call them anecdotes about when the markets doesn't work don't work it's okay but there are thousands of these papers where it seems to work very well yeah well events that he said those are the bests I think studies of how well markets adjusted and well they read the vast majority tell you that markets adjust when the information is revealed and the actual event you don't see much right exactly what your conjecture because of efficient markets right yeah so now you mentioned dick Thaler not only turned to be advanced what do what's your thinking because it seems like behavioral finance has been at odds with efficient markets but on the other hand they seem to be almost opposite sides of the same coin so what are your thoughts cuz you obviously hired dick here Yeah right I was ya involved with that right so I've started to tease him was saying I'm the most important person in behavioral finance because without me they have nobody to pick on exactly and that I said you know twenty years ago I wrote a paper market efficiency long-term returns in behavioral finance where I said look guys you have to grow up be challenged you can't just be complaining about market efficiency all your life you have to come up with something that we can test and reject right and takes a theory to beat up here that's as I said right in a testable theory and I reminded him of that a couple of months ago okay because if you read his recent book yeah misbehaving right same thing right and when I say to what where is the theory that we can reject that we can call behavioral finance as an exit not yet no well I mean not yeah give me a break okay I'm trying to be kind okay so now let me turn to more recent work that you've been doing okay and thinking about how to apply these ideas because obviously your work actually has a lot of practical implications many people take efficient markets as well as the farmer French three factor in some cases five factor model and put it into practice can you talk a little about your interest in practice and maybe some of the work that you've been doing for years now with dimensional funded games well dimensional Fund Advisors was started by David Booth and Rex Sinquefield who were students both was one of my research assistants way back when as a PhD student and director was in one of my classes Rex was the first one to go off to American Standard he as a kid and within a couple years he worked his way up to be the in charge of all they're investing he he brought out the first actual index fund based on that the efficient markets hypothesis Wells Fargo was doing it pretty much at the same same time but they didn't come up with an actual index fund because Myron and Fisher always wanted to fancy it up okay uh-huh so Rex actually did the first one and then Booth came to me and said I'm starting a company do you want to be involved I said sure never been involved with a business so I'll be involved ok with it and I've been you know working with them ever since initially all they had was the micro-cap fund so the 910 deciles of that of the equivalent in why I see stocks I was tiny put any stock portfolio and then I had done a lot of stuff in the 70s on using the structure of forward raids to predict returns on longer-term bonds and they came up with products based on that pretty quickly and then when the farmer French stuff came out they had clients for that very so-called value stuff before that paper was even published huh he brought a guy out one of the clients out here to the University and on my computer screen I showed him the results and he said ok I'll take 20 million of that Wow I want a big one in the small one uh-huh and he said fine ok and then we went over to the middle T and hit a hamburger but now all of their products are kind of centered on that model you know us products and international products the business is an enormous business I mean it's grown phenomenally over the last several even just years never mind the decades it grew right through 2008-2009 right kind of testimony that if people buy into efficient markets they don't bomb out as easily right as a little by interactive interesting but gene the ironic thing is that this particular set of portfolios that DFA is constructed has actually managed to outperform a lot of its competitors but as a means to help perform the segment's ok alright so you still believe that this is an example of efficient market works rather than a counter example and it's just I always distinguish between asset pricing and efficient markets those that those are that - what I call it the twins of asset pricing Siamese twins of asset pricing you can't separate them right and the the risk return part of it is what they're Dale dealing with so I think their products are just riskier they have a little tilt that tilts the value they have straight value portfolio small stock portfolios and big stock portfolios and basically they've glad you tilted portfolios practically evolved of all sorts yeah it's a fantastic success story guys obviously we are sitting in the Chicago Booth it's a business so David has been very generous in our history and has done well as thanks to you and the ideas that you've developed quite an impact right so now we get to the most important part of this interview which is the pursuit of the perfect portfolio in your view what is the perfect portfolio what would you recommend and how far away are we from being able to achieve that for the typical individual investor I don't think there is a perfect portfolio I think you have at least in my current view of the world you have a multi-dimensional surface that's characterized by a continuum of portfolios with different sorts of tilts okay and the market portfolio is the center of of that universe and in aggregate people have to hold the market portfolio right that's it and that's an efficient portfolio and any model you want to you want to think of and then you can decide to tilt away from that towards other dimensions that we think capture different kinds of risk but and that's a personal decision but your your as David booth says you wanted diversification is your buddy right if you decide to tilt the way you want to do it in the most diversified way you go you can know is there a possibility of over diversifying you know people like Warren Buffett have argued that instead of not putting all your eggs in one basket he prefers to put all your eggs in one basket and watch that basket very careful yeah so is there a chance that we end up you know somehow and spreading our portfolio too thin oh yeah I don't think that's possible okay you know if you ask Warren Buffett would what people should do with it but folios he says go pass em right right that's true I think he provides an interesting case in the sense that everybody points to him right as evidence of a market inefficiency of some sort but there there are two problems with that one is nobody says that if you run companies you can't add value right right nobody says there's no such thing as human capital right right and then there's that does that part the other is if we have I don't know several hundred thousand businessmen right and we pull out the most successful one what's the probability that that was luck not skill right even over a long period of time yeah so you get a big statistical issue there because that's the way right people get identified sure I would I would like like to have somebody examine whatever the performance what has the performance of his acquired companies looked like since he was anointed huh yeah so stake I had a kid come in one time an undergrad that said he had tested that and he promised to show me the results today I never saw it right I must not have been very compelling I don't know any funny girl for in a sec yeah well so in the end then it seems like having individuals pick characteristics that are appropriate for their personal circumstances would be the approach that yeah you know I think the big problem facing investors is that they don't understand the importance of uncertainty about outcomes yeah so for example I get to do a lot of talking to institutional people and financial advisors institutional people especially tend to change their portfolios based on 3 to 5 years of past returns right and I show them simulations in which that's basically noise you know 3 or 5 years of past returns there's almost no information in that about expected returns uh-huh and they kind of shock to buy it but I think that's the the reality is that there's no free lunch out there the the higher expected returns on stocks comes about with lodgement amount of risk and what that means is over long periods of time you can lose on a purely chance basis huh and we don't have enough data to know what the true expected return is so we've got data going back to 1926 that leaves us with an estimate of the risk premium over one month bills that could be the average numbers 5 6% a year but the standard the two standard error bounds around that right and a big very noisy yeah yeah yeah so what about all of the technological innovations that we've seen over the last few years things like ETFs and online trading Romo advisors any thoughts on where markets are going and what you think in terms of you know markets if if I think about DFA in the beginning there people went home with small computers every night is Becca right now they have multiple systems I mean all over the world that's changed in the old days they did a lot of block trading huh God right because now everybody splits up their artist puts them out on multiple platforms and does their does their trading so trading has become much more competitive much more fast-moving you have to be very careful not to get front run by you know anybody that can figure out what you what you might be trying to do so that's all changed dramatically and of course information is now much more easily available but you know I frankly don't see the tracks of any of that and the behavior of returns I mean the market so look I get this every time I give a talk you get that question the markets more efficient now because more information is there and it's more quickly available well maybe there's just too much noise in the data but you can't see the tracks of that in the data do you see the noise increasing over the last few years or is it about the same about the same okay you know we go through periods of higher volatility lower volatility but after the third East basically the process that's pretty stationary so yeah in a really quiet period I mean believe it or not the forties to about 63 are a really quiet period you have only two returns outside that barely break ten percent monthly yeah and then thereafter you get quite a few that break ten percent but you don't get what you got in the 30s which is a lot of plus and minus things bigger than 20 right right it has the financial crisis changed any of the dynamics of markets over the last if you're here detail uh-huh okay I mean I can't do yeah so would you say that you've changed at all your investment philosophy over the course of the last ten or 20 years are you still investing in the same way the 20th say no okay but if you went past that before ninety two before we did the cross-section of expected stock returns I'd have said everybody should hold the market portfolio right now I'd say no your taste might cause you to tilt a little more to its smaller value or whatever right but you know it's do I still think the market is the centerpiece right right and most people should sit there because it's a cheap way to go you know yeah it's very inexpensive to hold a market portfolio from Vanguard or somebody like that hell there are lots of providers that do it in very low cost but get to be careful because there's some that do it at high cups right yeah and cost will eat you up great and looking forward any thoughts on a follow French 7 factor model coming down the bloody wood we're doing the we came up with a five factor model it seems very robust yeah but I don't think it's been fully vetted yet okay and I'm suspicious about the investment factor mm-hmm because there is this phenomenon that's been there forever that all asset pricing models have problems with unprofitable stocks that invest out small and profitable stocks that invest a lot there were a big problem in our 93 paper when we look backward we thought it was we thought it was M X Nasdaq you know the high tech companies that were causing the problem but when we brought it back to 26 it was still there right and those guys weren't there at that at that time they would internationally it's there again yeah so that factor gloms onto that's enough and some little suspicious of it ah and the other one is the profitability factor which is almost entirely due to small stocks because you think about the market the cap weight market is big profitable company right right so that is a high profitability portfolio yeah the cap weight version of it sure well gene is no exaggeration to say that your theories have really democratized all the finance I mean the efficient market hypothesis allowed all of us to manage our portfolios interest rate for way so on behalf of all investors thank you very much for giving us the perfect portfolio unless ya you

Channel: MIT Laboratory for Financial Engineering

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Length: 37min 45sec (2265 seconds)

Published: Thu Dec 15 2016