Things I’ve Learned from Gene

Gene Fama has taught us a lot over the last 50 years. The other presentations today focus on his contributions to asset pricing, corporate finance, and banking. I take a broader perspective and describe some of the things Gene has taught me about doing research, writing papers, and life in general.

Gene is a wonderful mentor who has extraordinary insights and shares them generously. Some of the lessons I describe are clearly things he meant to teach. Others, however, are inferences I have drawn from our interactions. Since these inferences may be wrong, I worry that Gene will deny or even vehemently disagree with what I say. I am usually surprised and often dismayed when I hear students summarize what they learned in my Investments class. I hope Gene does not have the same reaction to my comments.

Many of us know Gene’s first recommendation about time management: If you are not willing to do something now, don’t agree to do it later. The logic is straightforward. You will probably be as busy later as you are now so unless the benefits will be substantially higher in the future, if you don’t want to do something now you will probably regret having to do it later.

Gene’s second recommendation is less well-known: Resist deadlines. Obviously, this advice is not intended for those who need deadlines to get anything done. But for the rest of us, there is no reason to let deadlines determine our priorities or make us work harder than we want.

Gene typically gives students and colleagues detailed comments on their papers a day or two after he is asked. He does referees reports almost as quickly. Together, Gene’s first two time management recommendations explain this peculiar behavior. Assume you will actually do everything you plan to do and you set your own priorities. Then the benefit of immediacy should determine what you do today. Start with the task whose payoff per hour of labor declines most quickly. In Gene’s case, quick feedback enhances a colleague’s productivity and sends a strong signal about the value Gene places on the colleague’s research. Similarly, a quick referee’s report improves the author’s productivity and the reputation of the journal. If the benefit of immediacy is highest for these tasks, they should be at the top of the stack—and that is where Gene puts them.

Many years ago, while trying to convince Gene that a marginal candidate deserved tenure, I compared the candidate to one of our less productive tenured colleagues. His response destroyed my argument, “You make enough mistakes by mistake, don’t make one on purpose.”

This is one of my favorite Fama quotes. Gene was making a specific point—don’t let a bad draw reduce your standard for future decisions—but I interpret his statement more broadly: Even with unbiased forecasts, the effect of uncertainty can be asymmetric. This is obvious when we consider things like risk aversion and option pricing, but it may not be so obvious in other contexts.

While preparing this talk, I finally figured out why my life always seems more frenetic than Gene’s. I have been ignoring estimation error when deciding what I should agree to do. Whenever it looks like I’ll have some slack in my schedule, I commit to do more and, if things turn out better than expected, I add even more. Unfortunately, this strategy leaves no room for tasks that take longer than expected. Even ignoring the optimism in my forecasts, my approach ensures that if anything goes wrong I am screwed.

Gene has trained himself to make good statistical inferences, both professionally and in more general settings. When I was about 40, a younger friend passed away. While chatting with Gene about the tragedy, I said it bothered me not only because had I lost a friend, but also because his death at a young age caused me to reassess my own mortality. Without a pause, Gene replied, “That’s OK. I saw a 94 year old yesterday.”

Gene’s ability to avoid statistical traps probably contributes to his skepticism about behavioral finance. Many of us read research about flawed decision making and say, “Sure, that seems like a plausible description of people’s behavior.” Gene looks at the same research and thinks, “Why would anyone do that?”

Gene is arguably the best empiricist in finance. Although there are lots of reasons for his success, three of the most important are easy to describe. First, his empirical approach fully embraces the fact that models simplify the world. This insight implies that all interesting models are false and that most of the hypotheses people test in finance are also false. For example, no continuous random variable actually has an expected value of zero. With enough data we will always reject such a precise null.

Gene’s goal when doing empirical work is to improve our understanding of important real world phenomena. He is not interested in testing models he knows are false. When presenting results, he emphasizes parameter estimates and the precision of the estimates, not formal tests. This emphasis explains why he says, for example, an estimate is reliably different from zero, not significantly different from zero. It also explains his aversion to papers that focus only on test statistics or, even worse, p-values.

When asked to describe my research, a colleague who does theoretical work once said, “All Ken does is calculate averages ... but he does it very well.” I’m not sure whether that was meant as a compliment, but after working with Gene for 30 years, I view it as high praise. Simplicity is a hallmark of Gene’s research. When writing papers, he works hard to make his logical arguments and statistical tests as simple as possible. He rarely uses a formal model to motivate his empirical work and when he turns to the data he says, “If you can’t see it in the averages, it’s probably not there.”

One of the most important reasons for Gene’s success as an empiricist is his investment in the data. It is obvious that anyone who hopes to do good empirical work must pay attention to the data. But Gene’s commitment goes far beyond that. When he begins working with new data, he spends days simply getting familiar with them. When he looks at empirical tests, he pores over the output, memorizing the central results and developing a thorough understanding of the rest. And when Gene considers someone else’s work, he usually starts with the tables and then decides whether to read the text.

I try to replicate Gene’s commitment, studying each new database and poring over test results. What I cannot replicate is his amazing memory. While I struggle to remember the paper we just finished, he can describe the evidence from ancillary tests we did 25 years ago. After five decades of study, Gene knows more about financial data than Google. The value of this is apparent not only in his own research, but also in his advice to students, his suggestions in seminars, and his comments on colleagues’ papers.

How can those of us without Gene’s memory compete? They are not perfect substitutes, but I replace his facts with rules of thumb. The annual U.S. equity premium for 1926 to 2013 is roughly 8% and the annual volatility is about 20%. The autocorrelations in equity returns are small and can often be ignored. The slopes in most regressions to explain U.S. stock returns don’t change a lot if we switch from nominal to real returns, but nominal or real does matter for bonds, especially short-term bonds. And so on. Obviously, these rules are not as good as Gene’s detailed knowledge, but they usually provide the perspective I need.

Mike Jensen, one of Gene’s earliest students, once told me, “Our job is not to write papers, our job is to get people to read papers.” That summarizes Gene’s attitude toward writing. After hundreds, if not thousands, of arguments with Gene about the best word and the appropriate use of a comma, I can attest that he cares passionately about the quality of everything he writes. I can also attest that he works hard to deliver that quality. Because even the best colleagues rarely read anything more than once, Gene will not circulate a paper until it is as good as he can make it. As a result, most of his papers go through at least five and sometimes more than ten full revisions before he distributes them.

Gene tries to be clear, succinct, and precise. He can usually have all three, but when there is a conflict he sacrifices clarity and brevity for precision. His emphasis on communication affects even his research design. When choosing between two sensible empirical tests, the easier to explain has the inside track.

Finally, Gene rarely uses footnotes. Most are distractions that sidetrack the reader and expose a lazy writer. If the content is important, Gene includes it in the text. If the content is not worth space in the text, how can it justify a footnote that interrupts the reader’s focus and train of thought?

I am tempted to say I have never seen Gene be rude or unkind, but I can already hear Sally saying, “Geesh French, I didn’t realize you’re blind.” So to be precise, in over 30 years of close observation, I recall Gene being discourteous only three times. Once a decade is a good record. (He is blunt occasionally, but that is efficient, not rude.)

Gene’s behavior had a big impact on the level of collegiality at the Booth School when I was on the faculty and I assume it still does. Given his prominence in the field and the hundreds of former colleagues and students he has around the world, I think Gene’s example has also had a big impact on the behavior of finance faculty more broadly. In other areas of economics, intellectual disagreements often lead to personal animosity. This rarely happens in finance. Gene’s friendship with Dick Thaler illustrates the point. A sociologist could probably identify many contributing factors for the cultural norms in finance, but the example Gene sets must be important.

Gene’s collegiality is not an accident. Soon after we started working together, we were talking about people the business school might hire. When I suggested one of the top researchers in finance, Gene said hiring him would be a mistake because he does not treat his colleagues with respect. Since that exchange, I have spent a lot of time trying to figure out what behavior contributes the most to a productive academic environment. I’ve concluded that, at least for business school faculty, Gene’s behavior is a pretty good model.

Gene once said a former colleague had won lots of arguments he should have lost. Non-academics might be puzzled to discover that Gene meant this as strong criticism. His point was simple. Using sarcasm or a sharp wit to undermine those who disagree with you poisons the intellectual environment. Gene rejects all ad hominem attacks. He consistently focuses on the idea he is arguing about, not the person he is arguing with. For example, he says a reporter’s question doesn’t make sense, not that the reporter is a pompous, arrogant fool.

The first time I saw Gene insulted in an academic discussion—by a visiting accounting professor!—I was surprised by his response: He simply ignored the attack. Because of his prominence and outspoken views about market efficiency and monetary policy, Gene has been the victim of many personal attacks since then and, as far as I know, he has ignored them all. He argues that his behavior is optimal, but doing is harder than knowing. Gene’s ability to consistently remain on the intellectual high ground demonstrates remarkable emotional discipline.

No one likes to hear that his or her child is not perfect. Most academics experience something like this every time we get a referee’s report. My solution is to skim the report when it arrives and then put it away. Twenty-four hours later I am ready to be constructive. Gene’s response is more mature. He reads the report and immediately starts thinking about the most productive way to address the referee’s concerns. I stopped complaining about referees’ mistakes a long time ago because I know what Gene will say, “It’s our fault if a smart, careful reader does not understand the paper.” He does not always agree with the referee, and he will not make significant changes that reduce the quality of the paper, but he always assumes the referee is acting in good faith and he always starts with the presumption that the referee is right.

Gene also does not complain when there is a mistake in the editorial process – and by mistake I mean rejection. He argues it is better to move on to another journal than to make the editor’s difficult job even harder. As a result, he has not appealed an editorial decision in over 50 years of rejections.

Gene Fama has made remarkable contributions to our understanding of finance and economics for over 50 years, but you don’t need me to tell you that. Gene’s insights about research and the broader production function of academics, and his disciplined implementation of those insights are equally remarkable. The goal of all this analysis and discipline is to maximize his contribution to the intellectual environment of the University of Chicago while reserving the time he needs to play sports, enjoy his grandchildren, and eat Sally’s pasta. The big beneficiaries are the colleagues and students Gene has worked with over the years, especially me.