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[Music]
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hello I'm Steve Forrester welcome to our
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project in pursuit of the perfect
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portfolio it's my pleasure and my honor
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to be here with dr. Harry Markowitz 1990
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Nobel Prize in Economics winner and the
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father of modern portfolio theory Harry
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thank you very much for joining me today
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thank you for having me
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I want to start off by taking you back
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to the early 1950s and tell me about
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your first investment decision when I
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wrote my article my 1952 article I had
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never invested I was a student with no
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one sale reports to it I mean it was a
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student without funds and the first time
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I had the opportunity to invest was when
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I had joined the RAND Corporation and
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Santa Monica
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they offered TIAA forces Scripps creff
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stocks versus bonds and at that time the
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studio time makes them look forward to
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telling this story people have it wrong
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have it right but but they don't have
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the right conclusion at that time I
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thought if the market goes up the stock
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market goes up and I'm completely out of
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it then I look silly and if it goes down
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and I'm a hundred percent in it I'll
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look silly so I went 5050 so it was at
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that time minimizing maximum regret now
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the story is sometimes told and I've
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seen it even the Wall Street Journal
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that Harry Markowitz even Harry
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Markowitz when he makes his portfolio
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decisions he doesn't use mean variance
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analysis he doesn't use MPT just uses
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minimum acts regret well that's what I
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did in 1952 but that's not what I would
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do today is not what I would recommend
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or more precisely it's not what I would
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recommend a 25 year old do know now I
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probably put them
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100% in stocks a lot has happened since
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I published that article in 1952 there's
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an infant structure we have this data
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that goes back to 1926 is light at least
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it shows you how I'm the average over
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the long run if you put a dollar in
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small caps who would be worth like
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13,000 or something like that because
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it's compounding at 12% you put it in
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large cavity we worth three or five
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thousand because it's compounding at ten
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percent but if you put it in government
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bucks and be worth 150 bucks as compared
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to fifteen thirteen thousand now we have
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optimizers we didn't have an optimizer
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in 1957 so on so the the conclusion is
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false that now Harry Markowitz 2017
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would recommend to a twenty five year
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that they go 50/50 so I want to come
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back to that later on in our discussion
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in terms of your views on the on the
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perfect portfolio so that's a great
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foreshadowing of what your thoughts are
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let's go back to when you were when you
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were working on your dissertation at
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University of Chicago and and you have
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this this unique ability to see things
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that that other people don't see can you
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tell us about one of the aha moments
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when you were in the University of
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Chicago library reading John Bear
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Williams investment book in and what
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what what were your insights that that
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came to know that my first that was my
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first
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aha moment and I've been seeking aha
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moments ferger's ever since I was at the
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stage where I was where I had to write a
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dissertation well back up a little bit
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with the story I went to my thesis
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adviser Yasha Marshak to ask for
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suggestions he was busy so I waited his
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auntie room and somebody's another guy
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was out there and the other guy was a
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broker waiting for marsac so we talked
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about why we
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here and he suggested that I do a
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dissertation you know in the start
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without the starting applying
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mathematical econometric techniques to
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the stock market so I went in before he
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did I told myself the guy out there I
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suggested that I do a dissertation of
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the stock market and applied to the
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stock market and Marshak said well
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Alfred Coles who adopt the Cole's
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Commission would like that he was it was
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actually interested in application of
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econometric techniques to the stock
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market he was the first to do
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experiments with weather forecasters
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could forecast have found out they
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couldn't and it's on so Marshak thought
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it's a good idea but he didn't have he
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didn't know the literature so he sent me
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to Marshall ketchup then dane professor
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Ketchum was the Dean of the business
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school I now understand and he gave me a
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reading list which included Graham and
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Dodd which is still in my shadows of
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course up and wheeze and burgers poor
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investment companies of their portfolios
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and we could see how things were
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diversified and classified by industry
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and then john byrne williams was the
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financial theorist of the day and
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Williams said that the value of a stock
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should be the present value of its
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future dividends and now of course
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dividends are uncircumsized figured he
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met the the present value of the
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expected value of future dividends later
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in the book he does say that when things
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are uncertain you should use the mean
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value the expected value my reasoning
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process went well if you're only
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interested in the expected value or the
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average the mean value of a vostok you
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must be only interested in the mean
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value of a portfolio oh and if you're
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only interested in the mean value of the
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portfolio the way you maximize that is
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put all your stock with all your eggs in
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one basket which I knew that wasn't
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right so I thought well you're trying to
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avoid risk as well as seek return I drew
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a graph with risk on will you want to
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return on one axis Andrew
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on the other and I thought of the
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returns on security is being like random
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variables I mean that means that the
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return on the portfolio was a weighted
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average of the returns on the individual
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securities where you choose the weights
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I knew offhand at the time what the
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expected value of a weighted average
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weighted sum was but I didn't know what
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the variance or standard deviation of a
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weighted sum was I looked I got a book
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off the library shelf expense keys
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introduction to mathematical probability
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my memories of that goodbye remember
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that whole thing very well and looked up
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the formula for the variance of weighted
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sum and there it was covariances
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correlations so I had the aha moment
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that the variability the riskiness of
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the portfolio attended not only on the
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volatility of the individual securities
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but to the extent to which they went up
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and down together and so there's still a
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lot to do that that became essentially
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my 1952 article plus a little geometry
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of pictures of how efficient sets look
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and there's still one more to do like
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trimming out how to compute these things
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an estimate but that was the aha moment
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so these ideas that seems so simple now
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but but yet you saw something that that
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no I don't know why Williams says that
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if you diversify sufficiently you will
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get the mean but that is only true if
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risks are independent uncorrelated if
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risks are correlated you don't get the
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mean you get there's a rule that says
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the variance of your portfolio and this
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is from chapter 5 of my 1959 book the
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variance of the portfolio doesn't
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approach 0 it approaches the average
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covariance so for all the correlations
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are 0 then the average covariance of 0
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and variance will approach 0 but in
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general
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I won't and how somebody could live
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through the 1990 but 1929 to 1932 crash
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and assume uncorrelated is difficult to
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see in retrospect I think his book came
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out in 1938 so he should have yeah he
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had gone through you know he had gone
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through oh he had seen the 29:32 was
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fresh in his memory the the notion of
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diversification goes way back the Bible
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had some refer to the Merchant of Venice
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Antonio why are you said is your
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business going bad my my goods are not
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to one bottom trusted but not and not my
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fortune to this year so my field so he
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knew about diversification but was like
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it was a good theory that would catch up
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with intuition and then you brought that
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theory and here we are now in March of
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2017 right and now this is the almost to
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the 2050s with the Davis over the
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sixty-fifth of security on our
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anniversary v is going xt60 look at the
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anniversary how times long at papers I
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want to talk about that this is the the
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journal Finance paper called portfolio
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selection and what's so striking about
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it is is how different it was compared
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to other papers that appeared in that
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same issue that looked at inflation and
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public policy issues and income
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statements what is it that made your
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paper stand out and and made it so
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different at the time and yet it
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wouldn't be that different from other
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journal Finance articles today
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well my emphasis was on portfolio
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selection you know because considering
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the portfolio as a whole they were all
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talking about evaluating securities or
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industries and the notion that you
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should have some kind of a theory up
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about what makes a well diversified
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portfolio and what is the trade-off
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between risk and return that some it's
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surprising that the human race went so
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long
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to leave me to discover that to fill
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that need and and really providing a
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process that helped to create a whole
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investment management portfolio
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management and let me tell you a little
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story of you know Peter Bernstein of
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course his book on there's a capital
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idea Capital ideas and something against
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the gods and strange history of
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residency of the history of risk he he
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was at a meeting that I was at to the
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Robert not has an annual meeting and I
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went one of his his advisers and Peter
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Bernstein Peter was there then he's no
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longer with us and after he has comment
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about to I'm somebody else's paper he
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just as a remark from the audience not
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as part of his paper he said it's common
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under somebody else's paper you younger
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people don't know what institutional
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investing was like before the 1950s we
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would sit around and have discussions
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like you see on television about I think
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this industry or I think there's some
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company and somehow we would clobber
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together cobble together a portfolio and
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he said now you have a process and it
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was at that minute a moment when he said
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now you have a process that I realized
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what I started of course there's a lot
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that goes into it besides you know like
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data and programs and so and so forth
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that's most about amazing what look for
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you to oversight over now 1952 was a
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great year for you you have the Journal
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of Finance paper but but a lot of people
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don't realize that that there was
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another paper that you referred to as
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Markowitz 1950 to be right that appeared
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in the journal political economy the
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utility of wealth and and it's through
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that paper that you've now been often
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referred to as is not only the father of
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Modern Portfolio theory but the
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grandfather of behavioral finance
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behavior like economics can you tell us
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about that paper and the key insights
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first confirming that you know
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certifying that I'm the grandfather of
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behavioral finance Danny Kahneman has a
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book out called thinking fast on
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thinking slow and of course if you're
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Harry Markowitz and you get a copy I
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think excessive thinking slow you get
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you a first thing you looked in the
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index to see if I refer to there's two
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references to me one was sort of
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inconsequential the other was told us
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the history of how prospect theory came
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about and the Kahneman says that there
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was that he and Tversky were struggling
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with some some experimental results
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which they just couldn't understand and
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finally Tversky came and said now I got
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the answer it's in a then 25-year old
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paper by Harry Markowitz it said that if
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you want to explain actually havior do
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not attach utility to to wealth attach
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it to change in wealth and that you know
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then that plus one and then it was a
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sort of a stripe of the curve depending
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on my curve had a pennant a concave
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portion the left on the losses so that
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was explaining why there's insurance
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people insure and then there was a
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convex portion which explained why which
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is part of the explanation why people
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buy bought lottery and then I was again
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a concave because otherwise you have the
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st. Petersburg paradox now that kind of
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this all came about come about I was
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teaching taking the Friedman's class in
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microeconomics uh he I don't remember
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whether it was a an assignment an
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optional assignment or a man
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notorious einman but he assigned a paper
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by Friedman and Savage I can't remember
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the name of the paper but it was trying
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to explain why there was both gambling
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and insurance and it had a curve which
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is very much like the market which
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currently later Markowitz curve in which
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there was a concave portion a convex
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portion of concave portion so I looked
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at this and I thought well you know if
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you took a it looked like a two-humped
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camel walking uphill so if you take a
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plank and you know put it against these
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two humps you get a double tangent and
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the behavior of people depend on where
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they are with respect to the these two
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tangency 's like for example if you have
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two middle class of people who are half
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way between the lower tangency and the
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upper tangency
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there's no fair bet that they would
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prefer then when were they flip a coin
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and one becomes poor and one becomes
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rich and you don't see that in fact and
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then the people who are below the lower
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tangents of poor people they don't buy
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lottery tickets and then I don't know
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who's lining up in front of me when I'm
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trying to buy a Wall Street Journal on
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3rd Avenue area and so on I mean it just
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didn't make any sense and the only point
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that made any sense
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was it the inflection point where they
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were they be you're cautious on the
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downside and maybe a little bit you know
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willing to gamble a little on the upside
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and then I said I didn't call that
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that's usually current wealth but I said
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I call that customary wealth because if
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you have a recent windfall gain you move
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into the convex part I don't you're
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you're a little bit more devil-may-care
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you're playing with house money so to
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speak and if you have a recent windfall
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laws you become more cautious so so the
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only point that made any sense was this
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inflection point
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and as compared to your group your sake
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Tversky says common Tversky lives become
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its current wealth but like I talked
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about as customary wealth because of the
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you're usually there but if you had a
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recent windfall gain or loss so that was
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that was another aha moment you've had
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many of them I love them I just adore
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effect so you followed up your your 1952
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portfolio selection paper seven years
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later with with a book by the same name
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and it packed a lot of things into it
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there was a chapter on matrix algebra
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that I think many famous people
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including Bill sharp learned is
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available well of that absolutely so
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what what had changed and and what was
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in there in terms of some of the nuggets
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that eventually became the capital asset
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pricing model with Bill sharp under your
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tutelage was able to follow up on well
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there's no that's dispelled the notion
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that Bill sharp got the idea for the
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capital asset pricing model from me
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let me tell you the real numbers were
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down that path let me tell the
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relationship between made me a mill we
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think roughly 1962 success as far as
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Bill and I can reconstructed I was
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working at a RAND Corporation he was
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working at the RAND Corporation II I was
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working on the script programming
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language or something else besides
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portfolio theory and he compared with my
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door said my name is Bill sharp I'm a
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student I worked here like you do and
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I'm a student trying to get a PhD at
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UCLA UCLA
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right Fred Weston who was the publisher
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who is the editor of the Journal of
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Finance at that time had told bill oh
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why don't you ask Kerry for suggestion
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you like his 1952 article what did you
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ask him for suggestion and in chapter 5
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of Marcos 1952 of 1959 I talked about
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what I called arrived covariances the
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fact that there are just too many
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covariance is to expand correlations who
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expect anybody to in a team to
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individually look at them and estimate
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them so you need something like a factor
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model and I a point you know I pointed
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to him about the the idea that there's
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too many covariances and whether to try
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building a factor model and see how well
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it works so that became sharp 1963 a
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simplified model of portfolio theory
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which showed how if you're estimating
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fact you have factors for each security
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rather than covariance is you know if
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you have you know one hundred securities
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you got a hundred times 100 divided by
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two roughly covariances that's fifty
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thousand whatever it is up so whereas
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you'd have one hundred betas testament
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so now is your estimation process easier
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but he published ways of quickly tracing
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out efficient frontiers and in those
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days a computing computing wasn't like
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it is needed today you know you the
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biggest computers in those days weren't
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as powerful as your cell phone you know
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so so he published
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Sharp's 1963 article was on factor
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models his 1964 model was on a capital
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asset pricing model now I published on
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cap M but it's like I have a an article
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called eat market efficiency a surrogate
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a theoretical distinction and so what
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and the came out of the FHA well decade
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ago or so plus or minus the and it said
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the theoretical distinction was between
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the proposition the market is efficient
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in the sense that it has correct
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probabilistic information everybody has
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the same beliefs and they're correct
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oh and everybody has a mean
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insufficient portfolio you have to
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distinguish between that efficiency in
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that sense everybody's processing
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information correctly and the statement
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the market portfolio is a mean variance
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efficient portfolio in what I show in
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that paper that FHA paper on a
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theoretical dissection and so what is
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not only do you have to distinguish
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those concepts but the in order to
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deduce that the market portfolio is any
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mean variance efficient portfolio and
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there's this linear relationship between
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expectorant and beta you have to assume
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either like sharp and linter that you
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can borrow all you want at the risk-free
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rate or you have to assume like Roy did
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that you can short and use the proceeds
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so you can give your your broker a
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thousand dollars short a million dollars
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worth of stock one and go long a million
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and a thousand dollars worth of stock -
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and it's a feasible solution you know I
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don't think I'll get away with that I
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don't think what it tried tried it your
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broker if you do tell me what your
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brokers name is so there's a ranked team
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that has constraints so and it's also
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true that there is not a linear
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relationship between expected returns
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and and beta defined and justified so
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these folks who find that there's not a
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linear relationship and then have all
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these fantastic explanations but why
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there isn't a linear relationship my
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explanation is very simple there is I
00:23:40
don't know about you but I can't borrow
00:23:42
I wanted to history write that said I
00:23:45
should add that I still think kappa mo
00:23:49
is very important because it is a null
00:23:53
hypothesis against which you can test
00:23:55
you know empirical results you could a
00:23:58
lot of people do and it's just their
00:24:00
interpret you know when they find there
00:24:02
isn't a linear relationship and they
00:24:03
have all these fantastic
00:24:05
explanations like I say as I said I
00:24:10
think it cap em was very important
00:24:13
historically and still is as he as the
00:24:16
null hypothesis against which all things
00:24:19
get measured let me come back to
00:24:22
something we talked about earlier let
00:24:23
you and sort of that sort of a circle
00:24:26
circle back the perfect portfolio okay
00:24:29
what what do you see as as is the
00:24:32
perfect portfolio for individuals for
00:24:35
institutional investors is there a
00:24:38
perfect perfect portfolio and and what
00:24:41
might be coming out of your work that
00:24:42
would suggest one type of portfolio for
00:24:45
sure another okay it sort of tied into
00:24:47
first lay since I don't believe that you
00:24:51
know because people can't borrow they
00:24:53
want to originally right I don't believe
00:24:55
that the market you know the market
00:24:57
portfolio plus or minus leverage is even
00:25:02
efficient so it's certainly not
00:25:05
perfectly the difference between a major
00:25:09
difference between mark was 1952 and
00:25:14
mark was 1959 is mark was 52 proposed
00:25:18
mean variance efficiency and it analyzed
00:25:21
it subject to one particular constraint
00:25:24
set the sum of the X is equal one of the
00:25:26
X's are not negative by 1959 I had come
00:25:32
to realize that you might want lots of
00:25:35
other constraints on the choice of your
00:25:37
portfolio might want on upper bounds on
00:25:40
individual securities you might want
00:25:41
upper bounds on on how much you have
00:25:45
uncertain in industry or you know sets
00:25:48
of securities you might have other
00:25:50
linear constraints like you want to have
00:25:52
income a certain level its compared to
00:25:55
and so on so what I provided in
00:26:03
Markowitz 1959 was a computer program
00:26:08
that found mean variance efficient
00:26:13
portfolios subject to any linear
00:26:18
equality or inequality constraints of
00:26:21
their linear constraints like the sum of
00:26:25
the x's equal 1 or inequality like this
00:26:28
plus this has got to be less than or
00:26:29
equal of that and these are used in in
00:26:33
practice like I have a client who does
00:26:37
portfolios of closed-end funds buying
00:26:39
when there a deeper discount selling
00:26:42
alert less deep discount but it he has a
00:26:46
world index on all country world index
00:26:50
benchmark and so he constrains the
00:26:53
portfolio not to deviate too much in any
00:26:56
one country and not to deviate too much
00:26:59
from the benchmark in any one region and
00:27:02
he doesn't want to turn over constraint
00:27:04
to be turn over to db2 to great and so
00:27:07
he has a turnover transfer and so on so
00:27:10
talking about the individual well
00:27:14
individuals differs if some are somewhat
00:27:18
they differ in their tax situations so
00:27:21
it should be an after-tax mean variance
00:27:24
analysis and that gets a little tricky
00:27:26
because there are things with different
00:27:29
time horizons you put it into a the 401k
00:27:32
plan you can't get it back out without
00:27:35
penalty until you're something you know
00:27:37
59 and a half or whatever okay so the
00:27:41
the correct part only not the perfect
00:27:43
portfolio with the correct portfolio for
00:27:46
the individual depend on all the risk
00:27:49
preferences you know they're willing to
00:27:51
trade off you know trade off from is for
00:27:55
return you don't want them dropping out
00:27:59
of the program prematurely so if you if
00:28:02
if it looks like the right thing prove
00:28:05
them for the long run if they have them
00:28:06
50% in small camp and you know small
00:28:10
camp is very volatile or maybe it's 50%
00:28:12
of the emerging market which is very
00:28:14
volatile and if it has a bad bounce
00:28:16
right out of the box you'll decide
00:28:18
that's a stupid asset class
00:28:20
this is stupid manager
00:28:22
program so there are constraints on the
00:28:25
choice of portfolio which varies from
00:28:27
individual to individual some individual
00:28:30
they have shorter or longer horizons
00:28:33
they they are willing to tolerate their
00:28:37
they're willing to invest in certain
00:28:38
asset classes or not they have different
00:28:41
tax situations and so on so there is no
00:28:44
perfect portfolio there is a right note
00:28:47
we will assume that there is a right
00:28:49
portfolio for them and part of the
00:28:53
process is to involve the rightful OOP
00:28:56
they want part of the process is always
00:28:58
to involve the user the investor what is
00:29:03
their trade-off between risk and return
00:29:05
in the old days you just showed them up
00:29:08
a frontier if he said pick now you do
00:29:11
Monte Carlo simulation to show them
00:29:13
whether it's a few points from the
00:29:16
probability distribution of how much
00:29:18
they can spend when they retire and so
00:29:20
on and so forth so there is a perfect
00:29:22
portfolio there's just the right
00:29:24
portfolio for any specific individual is
00:29:28
a lot of work to find them so again it's
00:29:30
the process that you provided it's
00:29:32
certainly going to be diversification
00:29:33
right it's going to be an important
00:29:35
element to that but not necessarily the
00:29:37
market portfolio so typically not in
00:29:40
fact you front frontiers you know they
00:29:43
start out with a fairly unda versified
00:29:45
portfolio and they pick up securities
00:29:47
and they lose securities and people are
00:29:49
different you are different you know
00:29:51
different people are in different points
00:29:53
on the frontier and nobody's holding the
00:29:55
market portfolio because the market
00:29:57
portfolio probably isn't even an
00:29:58
efficient portfolio and it's certainly
00:30:00
not an efficient portfolio for everybody
00:30:02
and we can't for one lend at the
00:30:05
risk-free rate so it would be if you
00:30:07
could borrow and lend if you could
00:30:10
borrow all you want at the risk-free
00:30:11
rate then the only mean variance
00:30:15
efficient portfolios would be the market
00:30:17
plus or minus leveraging but it's not
00:30:20
true so where do you think the
00:30:23
investment management industry is is
00:30:25
going to go in the next 65 years right
00:30:27
now we've got Robo advisors which in
00:30:30
some senses is going back to the
00:30:33
beginnings and
00:30:34
looking at things in a systematic way
00:30:36
where do you think the industry is going
00:30:37
well I might mention that I have a
00:30:41
number of clients I work on retainers
00:30:45
and so somebody's paying me even now the
00:30:47
cookie of talking and a couple of my
00:30:53
clients are Robo advisors with different
00:30:55
one is acorns where they think takes
00:30:58
small change you know they round up the
00:31:00
they round up the bill and your tech to
00:31:04
your credit card bill and invested and
00:31:06
say and so so yeah I'm all for Robo
00:31:09
advisors they have to then make some
00:31:14
guess as to where you want to be on the
00:31:16
frontier or maybe just as fact that you
00:31:20
chose them this particular advisor Robo
00:31:24
advisor shows what kind of portfolio you
00:31:27
must be interested in the I think oh we
00:31:34
are now doing a very good job
00:31:39
increasingly good job of exploiting my
00:31:43
19:52 idea and not let me tell you the
00:31:47
idea that's in volume two of the four
00:31:51
volume book I'm currently writing
00:31:53
consciously way yeah yeah I got to plug
00:31:56
the book it's called risk return
00:31:58
analysis and the subtitle is that the
00:32:01
theory and practice of rational
00:32:03
investing and actually it's not about a
00:32:05
rational investing it's a rational
00:32:07
decision-making financial planning it's
00:32:09
not seven and volume two talks about
00:32:14
decision support systems so a 401k
00:32:17
advisory service or robots of is a
00:32:20
decision support you with the the better
00:32:25
one I mean the more flexible ones you
00:32:27
get to interact with the system and pick
00:32:32
what risk class you want to be in and
00:32:34
what savings Rachel need did have and so
00:32:36
on so you so it helps you it helps you
00:32:40
make the decision that it takes your
00:32:42
decision and implements it so it's a
00:32:44
decision support
00:32:46
a decision-maker it's a decision support
00:32:48
system and the investment decision I
00:32:52
think I view any of the way I view it is
00:32:55
part of a game which the family is
00:32:59
playing it and these are these are
00:33:03
financial this is the financial planning
00:33:05
game but it has to do with many things
00:33:08
like births and deaths and weddings and
00:33:11
people getting sick and flycatchers all
00:33:14
life life events it is the events and
00:33:18
decisions which have major impact on the
00:33:21
supply and demand of Natural Resources
00:33:23
and the just analyzing the portfolio
00:33:29
selection that decision in isolation is
00:33:32
like trying to decide how our bishops
00:33:36
should move in a chess game without
00:33:38
considering the chess game as a whole I
00:33:40
think the way I see the thing going in
00:33:44
the next 60 years it looks the way I'm
00:33:47
trying to push it in volume two is for
00:33:51
the the man-machine the human computer
00:33:56
division of labor to cover more fully
00:34:00
the various aspects of financial
00:34:03
planning well we wait anxiously for
00:34:07
volumes three and four and and on behalf
00:34:09
of all investors I want to thank you for
00:34:13
what you've contributed to to help help
00:34:17
us make better decisions more rational
00:34:20
decisions and I really appreciate you
00:34:23
taking the time it's been my pleasure
00:34:24
both both to to work at this field for
00:34:27
less which 65 years we've decided and
00:34:30
and your interview was very very
00:34:34
pleasant thank you very much thank you
00:34:35
[Music]
