Opening the black boxes: financial algorithms and multi-paradigmatic research in information technology

Purpose: This paper aims to contribute to recent debates about financial knowledge by opening the black box of its algorithmization to understand how information systems can address the major challenges related to interactions between algorithmic trading and financial markets.

Design/methodology/approach: The paper analyses financial algorithms in three steps. First, the authors introduce the phenomenon of flash crash; second, the authors conduct an epistemological analysis of algorithmization and identify three epistemological regimes – epistemic, operational and authority – which differ in terms of how they deal with financial information. Third, the authors demonstrate that a flash crash emerges when there is a disconnection between these three regimes.

Findings: The authors open the black box of financial algorithms to understand why flash crashes occur and how information technology research can address the problem. A flash crash is a very rapid and deep fall in security prices in a very short time due to an algorithmic misunderstanding of the market. Thus, the authors investigate the problem and propose an interdisciplinary approach to clarify the scope of algorithmization of financial markets.

Originality/value: To manage the misalignment of information and potential disconnection between the three regimes, the authors suggest that information technology can embrace the complexity of the algorithmization of financial knowledge by diversifying its implementation through the development of a multi-sensorial platform. The authors propose sonification as a new mechanism for capturing and understanding financial information. This approach is then presented as a new research area that can contribute to the way financial innovations interact with information technology.