When I came to the University of Chicago in 1960, I was exposed to professors who were involved in the nascent subject of finance, which didn't exist as a discipline at the time. It was all being born, and it just happened that I had come to the place where that birth was happening. So I kind of got into it because everybody there was interested in it.
In my first year I took an intermediate statistics class with a professor named Harry Roberts. I was 21 at the time. He was very much like me -- he was into all kinds of sports, and he was a runner. I had done a lot of statistics work as an undergraduate and had already worked with data, so I was pretty advanced when I started. But what I learned from Harry was a philosophy. He gave me an attitude toward statistics that has stuck with me ever since.
With formal statistics, you say something -- a hypothesis -- and then you test it. Harry always said that your criterion should be not whether or not you can reject or accept the hypothesis, but what you can learn from the data. The best thing you can do is use the data to enhance your description of the world. That has been the guiding light of my research. You should use market data to understand markets better, not to say this or that hypothesis is literally true or false. No model is ever strictly true. The real criterion should be: Do I know more about markets when I'm finished than I did when I started? Harry's lesson is one that I've passed on to my students over the 49 years that I've been a teacher.
We went through our archives for nearly a decade of collected wisdom that still holds up.