What Finance Can Learn from Computer Scientists

The realization that economics is not a hard science because it is unable to describe the real-world economy, is not a new claim. Presenting an “economically rational” world has failed to describe the real-world economy, and therefore has been under attack by behavioural economists for quite some time. In an interview, Frank Fabozzi opines that in order to stop the study of finance from stagnating and facing irrelevancy, the way finance is taught in school and accepted by academics needs to be radically overhauled. While the interview may seem like an attack on using calculus as an effective way to describe financial phenomena, it argues for a more innovative approach – by combining higher-level mathematics with data science techniques, it will be greatly beneficial for processing large amounts of data, while still using logical thinking. Currently, Fabozzi believes that, “computer scientists may be better trained to deal with problems in finance than finance students,” likely because of their exposure to data science techniques like machine learning.