Drexel LeBow Finance Professor Talks Bias at Philadelphia CFO Alliance

Story Highlights

  • Wes Gray, Ph.D., assistant professor of finance, speaks about decision-making biases at Philadelphia CFO Alliance.

  • Quotes research, which categorizes different types of bias.

Can CFOs overcome biases to reduce forecasting errors?

“Definitely yes!” Wes Gray, PhD, assistant professor of finance said at a Nov. 9 discussion at the CFO Alliance’s Philadelphia Chapter. “To accomplish this, CFOs need to institutionalize logical practices that minimize behavioral errors and rely less on their gut.”

In a discussion titled “Behavioral Finance and Decision Making: Lessons from/for CFOs,” Dr. Gray spoke about his research, which groups relevant biases into four categories: overconfidence; optimism (or wishful thinking); availability bias; and anchoring bias.

According to Gray, these biases cause many people to underestimate volatility and to assess themselves as better than average, while focusing more on recent events to anchor on arbitrary data.

During the event, CFO Alliance attendees discussed problems, solutions and challenges in implementing solutions that control for bias. Specifically, they discussed how the four relevant biases affect their roles as CFOs, how their firm can minimize behavioral errors and the challenges in implementing these changes.

Creating a culture that recognizes decision-making errors and facilitates the ability for subordinates to discuss bias issues with senior management without the threat of losing their job is the paramount challenge to successful implementation, Dr. Gray said.

Dr. Gray emphasized ways that firms can institutionalize processes to minimize bias, such as instituting a “lessons learned” continuous feedback process, or by simply keeping a list of biases visible to decision-makers as forecasts are being prepared.


Dr. Gray’s book, Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (John Wiley & Sons; 2012), discusses how value investors can improve their decision-making processes by employing systematic quantitative tools in their analysis.