Out of the Ordinary: Learning to Generate Abnormal Returns

More risk means more reward. It’s what finance students are taught from the beginning of their studies. Reward is the return that an investment generates to adequately compensate an investor for bearing the risk of the investment (But you already knew that). More importantly, what is risk? Is risk measured by a company’s equity Beta, standard deviation, likeliness of workplace accidents, or perhaps a credit rating? Furthermore, if we assume that the risk-reward parity holds in the real world, then how is it possible to generate higher returns when taking on less risk?
The curriculum of the Darwin Fenner Student Managed Fund sets out to answer that question. The course is focused on exposing students to investment research that has been proven capable of producing abnormal returns, that is higher investment returns on less risky investments (as measured by standard deviation and Beta). Well, if you ask the University of Chicago’s Eugene Fama, Nobel Prize winner and god-father of Efficient Market Theory, he would say that abnormal returns are not possible, because markets are efficient and that there is some risk that cannot be captured by a model that is driving higher returns. By contrast, most finance professionals and academics would probably tell you that Fama’s efficient market hypothesis is wrong and thanks to market inefficiencies there is money to be made if you look in the right places.
More Money. Ok, hopefully I have your attention again after all of the academic jargon. More money is better than less money. More money is what the Darwin Fenner Funds analysts are tasked with. Teams of three people have been selected to cover each sector of the S&P 400 Mid-Cap Index. Getting to know every company intimately is not a realistic goal for three people to do in only five months, but what Darwin Fenner is teaching us to do is to create models using spins on proven academic research that will help us identify companies that we will want to invest in. Most recently, we read a paper by Joseph Piotroski that introduced student-managers to a model of nine statistically significant accounting screens that are capable of recognizing financially strong companies that are severely undervalued by the market. This model sparked discussion amongst student as to how we could use some of these factors in our industry model. Every team has their own model and different indicators that they will use, but the ideas are starting to roll. Hopefully, the returns will start rolling in as well.
Tommy Milburn