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The Harry Markowitz Interview, Part 1: Portfolio Selection

At the 2013 Research Affiliates Advisory Panel meeting in San Diego, I interviewed one of the doyens of the wealth management industry, the 1990 Nobel Prize Winner, Harry Markowitz. His 1952 seminal paper Portfolio Selection pioneered our understanding of risk, return and correlation in investment portfolios. His Efficient Frontier and Modern Portfolio Theory ideas are still taught in universities and business schools.

Harry Markowitz was born on August 24, 1927 in Chicago. He studied economics at the University of Chicago under important economists, including Milton Friedman. While still a student, he was invited to become a member of the prestigious Cowles Commission for Research in Economics, leading to his 1952 breakthrough work.

Markowitz now divides his time between teaching (he is an adjunct professor at the Rady School of Management at the University of California at San Diego) and consulting (out of his Harry Markowitz Company offices). He is co-founder and Chief Architect of GuidedChoice, a managed accounts provider and investment advisor. Markowitz’s more recent work has included designing the software analytics for the GuidedChoice investment solution and heading the GuidedChoice Investment Committee.

One amusing moment from the Conference shows how competitive and bright the 85-year-old Markowitz still is. The 2011 Nobel Prize winner, Chris Sims, had just finished a highly technical presentation on how fiscal policy affects inflation. As he paused for questions, Harry was first in. “Now we know how you got your Nobel Prize, let me show you how I got mine.” And he gave his critique of the presentation as if giving a lecture in his university.

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Graham Hand: I'd like to start by going back to 1952 and your seminal paper, Portfolio Selection. Did the idea of mean variance and efficient frontier and risk reward come to you while you were having a shower, or was it more systematic that that?

Harry Markowitz: There was a moment of truth, a ‘ah ha’ moment. Let me give you some background. I was a PhD candidate at the University of Chicago and had to choose a topic, so I went to see my supervisor, Professor Jacob Marschak. He was busy so I sat in this ante room, and another man was there who was a broker. He suggested a dissertation on the stock market. That's the best advice a broker has ever given me.

I suggested this to Marschak, and he said Alfred Cowles (who set up the Cowles Commission at the University) had always hoped people would do that. Cowles was one of the first to study how successful stock pickers were (and he found they weren’t), his work became part of the development of the S&P500 index, but he was also a scholar. Marschak did not know the relevant literature so he sent me over to Professor Marshall Ketchum. He was Dean of the Business School at the time. He gave me a reading list which included Graham and Dodd, Weisenberg and John Burr Williams, The Theory of Investment Value, from 1939.

So I'm in the Business School Library, and Williams says the value of a stock should be the present value of its future dividends. I thought to myself, dividends are uncertain, so he must mean the expected value. So I thought if we’re only interested in the expected value of a stock, we must be only interested in the expected value of a portfolio, but to maximise the expected value of the portfolio, you must put all your money into the one stock with the highest expected return.

But that can't be right, everyone knows you should not put all your eggs in one basket, Weisenberg had shown people are willing to pay for diversification. So people diversify to reduce risk and volatility, and standard deviation is a measure of risk.

GH: So you knew statistical theory, you had that background?

HM: Yes, I had the usual courses you’d expect from an economics major in the leading econometrics school. So I visualised the returns on the securities as random variables, so that means the return on the portfolio is the weighted sum of the returns on those random variables. I know what the expected value of a weighted sum is, but I don't know off hand what the variance of a weighted sum is. So I get a book off the library shelf, Introduction to Mathematical Probability. I look up the formula for the variance of a weighted sum and there it is, covariance. Not only does the volatility of the portfolio depend on volatility of the individual securities, but the extent to which they go up and down together.

GH: That was the magic moment.

HM: That was the moment. So now I have two quantities, risk and return, and I know economics so I draw a trade-off curve. I’d heard of efficient and inefficient allocation of resources, Pareto optimums and so on. So I now had efficient and inefficient portfolios. In that flash, in that moment, much of Markowitz 1952 came together.

GH. So although there was this moment, there was a massive body of knowledge already built up.

HM. Sir Isaac Newton said, “I saw so far because I stood on the shoulders of giants.”

GH: Also in your career, you are credited with running one of the first hedge funds, doing arbitrage.

HM. No, a long way from the first. A bit of history. My first job out of college was with the Rand Corporation, where I developed a programming language called SIMSCRIPT, for simulation. The guy who wrote the manual was an entrepreneurial-type, he said, “Harry, let’s form a company.” We founded CACI in 1962, it still exists, it’s a big company now. Then UCLA invited me to be a full professor, full tenure, and another entrepreneur decided to form a hedge fund called Arbitrage Management, based on Thorp and Kassouf’s book, Beat the Market, doing all sorts of arbitrages. I was a consultant, then the portfolio manager. We made a decent return for clients but not really for us, we were generating a lot of brokerage, so we became a wholly owned subsidiary of a brokerage house before I left.

GH: Given it’s now 60 years since Portfolio Selection was published, do you feel any sense of disappointment about our profession, we haven’t really had any major breakthrough theory of investing since the 1950’s.

HM: A lot has happened. We have a lot of data now. In 1952, we hired a student to collect data on securities. But between the top down view, knowledge of data, and our experience, we are better now. When I was at Rand in 1950, I just did 50/50. That’s all I knew then, it’s not what I would do now and it’s not what I would recommend to a 25 year old. My profession and I have learned a lot.

GH: I don’t like how so many investment discussions end up talking in generalisations.

HM: It’s a good point. There’s a big difference between my article of 1952 and book of 1959. In chapter 13, I talk about the division of labour between the computational part and the intuitive part. Computational part can show probability distributions of returns you can have at your disposal, we can tilt them so they’re correlated with inflation or whatever. But which particular probability distribution you want to have at this time of your life, for this year – you know, your kids go to college, you’re not feeling well, people might be dying in your family, etc - is beyond any model. We don’t understand all that goes on. If we could understand it, we couldn’t model it. If we could model it, we couldn’t estimate it. This year is different from next year.

Next week: Harry Markowitz on providing retail financial advice.

 


 

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