Article ID: CBB890038954

Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets (April 2022)

unapi

This article examines algorithmic trading and some key failures and risks associated with it, including so-called algorithmic ‘flash crashes’. Drawing on documentary sources, 189 interviews with market participants, and fieldwork conducted at an algorithmic trading firm, we argue that automated markets are characterized by tight coupling and complex interactions, which render them prone to large-scale technological accidents, according to Perrow’s normal accident theory. We suggest that the implementation of ideas from research into high-reliability organizations offers a way for trading firms to curb some of the technological risk associated with algorithmic trading. Paradoxically, however, certain systemic conditions in markets can allow individual firms’ high-reliability practices to exacerbate market instability, rather than reduce it. We therefore conclude that in order to make automated markets more stable (and curb the impact of failures), it is important to both widely implement reliability-enhancing practices in trading firms and address the systemic risks that follow from the tight coupling and complex interactions of markets.

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https://data.isiscb.org/isis/citation/CBB890038954/

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Authors & Contributors
deVries, Karen
Cech, Erin A.
Kellie Owens
Louise Amoore
Ziewitz, Malte
Davis, Veronica O.
Concepts
Technoscience; science and technology studies
Technology and society
Algorithms
Interviews
Information technology
Risk
Time Periods
21st century
20th century
20th century, late
Places
United States
Japan
Israel
Institutions
United States. Securities and Exchange Commission
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