Morningstar Advisor - June/July 2010 - 50

Morningstar Conversation

Sam Savage

The thing about the mean-variance model is that it is a magnificent, simple theory, like Isaac Newton’s F 5 ma.

that there you have to Monte Carlo, and then you optimize.
Savage: What Harry just described is almost exactly what we did at Shell, except that we store thousands of finite samples in beer bottles. Markowitz: Yes, you have a tool kit full of techniques—optimization, Monte Carlo, present value, linear programming, quadratic programming, and so on. A person who only has one tool in his kit is a danger. You know the old saying, “If all you have is a hammer, everything looks like a nail.”

es that you and I encounter, like what is going to happen if my left foot trips over my right foot, I probably don’t have to use Einstein’s theory to figure out the result. So under certain conditions, and those are very broad, the Newton theory works wonderfully. Similarly, under certain conditions, mean-variance works perfectly well. What are those conditions? Well, they have to do with the probability distribution returns not being spread out too much, like Levy-Markowitz says.
Kaplan: This scenario-based approach that

Markowitz: I’ll try not to make it inflammatory. I do believe in scenarios and Monte Carlo. I like the way Sam packages them and makes them convenient. For situations where mean variance is applicable, I still would trace out mean-variance frontiers, but in deciding which point on the frontier one should recommend, I would use scenario or Monte Carlo for that.

So, I agree. We have many techniques, and we’ve have to decide where are they applicable.
Savage: I have a comment to put this

Sam and I have been working on we like to call Markowitz 2.0. Are you okay with that?
Markowitz: I’m fine with that. How can I refuse

Let me characterize Sam in my mind. There is a conversation we had that I think is prototypical Sam Savage. Sam has these wonderful ways of displaying things, of making things accessible to Excel users. He has this wonderful sense of humor. I think of him as sort of a graphical artist and the salesman of our field. One time, he told me what his Ph.D. dissertation was. I said, “That’s incredible. You could be proving great theorems like your father. Why aren’t you?” He replied, “Because I’m making more money and having more fun.” K
Paul D. Kaplan. Ph.D., CFA, is director of quantitative research with Morningstar Europe.

anything to a man who has named an important contribution the “Markowitzitron.”
Savage: I’m delighted, Harry. I started looking

in another perspective. The thing about the mean-variance model is that it is a magnificent, simple theory, like Isaac Newton’s F 5 ma. Oh, it doesn’t really equal ma because of Einstein’s theory of relativity. But do you know what? F 5 ma is a foundation on which we have built modern physics because it is a simple, beautiful model that is good in most real world situations. Another advantage of theory over computation is that it provides its own sorts of insights that foster further scientific thought. The mean-variance model did this in spades. It is a beautiful, simple theory.
Markowitz: Let’s take the universal theory of gravity of Sir Isaac Newton versus Einstein’s theory of gravity. Under almost all circumstanc-

at this stuff in the oil patch, where the distributions were incredibly far from normal—that is to say, there’s an 85% chance of getting zero and some tiny chance of getting big payoffs. And yet, using the scenario approach led to creating these distribution strings. Then, I met Harry Markowitz along the way, and that was a thrill. I’ve learned a tremendous amount from Harry over the years. But it’s a sweet irony that these distribution strings now are beginning to be used in finance, at least by you folks at Morningstar. It closes the loop for me, which is personally gratifying.
Kaplan: Harry, you have the last word.

50 Morningstar Advisor June/July 2010

Morningstar Advisor - June/July 2010

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