Abductive Reasoning in Quantitative Finance

In a relentless search for low-risk edge in the financial markets, investment management and proprietary trading firms invest heavily in technology, data and manpower in the form of software developers, quantitative analysts and researchers. Drawing on interviews with 90 market professionals, this paper explores ways in which ‘quants’ (quantitative analysts, developers and researchers) deal with the intricate problems they are faced with in their daily work. It is argued that the way quants reflect and decide upon what model to use, what algorithm to scrap, what type of data to churn and so forth, is akin to the abductive reasoning process as described by the American logician Charles Sanders Peirce. Instead of pursuing finite answers to questions regarding a highly complex and dynamic systems such as the financial markets, quants – in accordance with abductive reasoning – tend to search for the best possible hypothetical explanation using the knowledge, data and technology they have at hand. While there has been a recent revival in research drawing on Peirce’s concept of abduction within the field of organisation studies, only a few of these studies are empirical. The present study contributes to the sparse existing empirical research on abductive reasoning in organisations, but more importantly it reports how highly skilled professionals reflect upon, break down and try to solve problems in an industry where an increasing number of processes are being automated.