The Behavioral Frontier of Active Investment Management

I’m sure many of you are familiar with the 2011 hit movie Moneyball, featuring superstars Brad Pitt and Jonah Hill. The film, centering around the Oakland Athletics baseball team, gives an account of how manager Billy Beane transforms the team’s performance, despite having the lowest payroll in the major leagues.

Moneyball tells the tale of an underdog's rise to glory using data analytics, now a multimillion-dollar industry that has revolutionized sports. More recently, data analytics is proving its worth once again, this time within the investment management industry. Behavioral data analytics is helping portfolio managers to fine-tune their decision-making process, giving them a vital competitive advantage. This is done with the help of machine-learning algorithms that can analyze large data sets of historical investment data to detect behavioral patterns that are either adding or destroying value within a portfolio.

Why investment managers need to up their game

Following a surge in the popularity of low-fee index funds, the active management industry has been feeling the pressure. To justify the fees that investment managers charge, they must outperform the index net of fees — i.e., they must earn the same return as the index plus the cost of the fees they charge. 

This is where behavioral data analytics can help. Decision-making in such a high-stake industry can have huge monetary consequences. By treating the decision-making process of PMs (portfolio managers) as a set of skills that can be analyzed and refined, data analytics can aid behavior change to boost a portfolio’s “behavioral alpha” — the excess investment return that results from mitigating the cognitive biases hidden in the investor’s decision-making process. This combination of behavioral science and data analytics can pinpoint value-destroying behavior and provide portfolio managers with the information and tools needed to enhance their decision-making process.