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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Systemic failures and organizational risk management in algorithmic trading : Normal accidents and high reliability in financial markets. / Min, Bo Hee; Borch, Christian.

In: Social Studies of Science, Vol. 52, No. 2, 01.04.2022, p. 277-302.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Min, BH & Borch, C 2022, 'Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets', Social Studies of Science, vol. 52, no. 2, pp. 277-302. https://doi.org/10.1177/03063127211048515

APA

Min, B. H., & Borch, C. (2022). Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets. Social Studies of Science, 52(2), 277-302. https://doi.org/10.1177/03063127211048515

Vancouver

Min BH, Borch C. Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets. Social Studies of Science. 2022 Apr 1;52(2):277-302. https://doi.org/10.1177/03063127211048515

Author

Min, Bo Hee ; Borch, Christian. / Systemic failures and organizational risk management in algorithmic trading : Normal accidents and high reliability in financial markets. In: Social Studies of Science. 2022 ; Vol. 52, No. 2. pp. 277-302.

Bibtex

@article{d9ce7c8939a84fb083d408f7f2ba0d59,
title = "Systemic failures and organizational risk management in algorithmic trading: Normal accidents and high reliability in financial markets",
abstract = "This article examines algorithmic trading and some key failures and risks associated with it, including so-called algorithmic {\textquoteleft}flash crashes{\textquoteright}. 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{\textquoteright}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{\textquoteright} 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.",
keywords = "Faculty of Social Sciences, algorithmic trading, financial regulation, flash crash, high-reliability organizations, normal accidents theory, risk",
author = "Min, {Bo Hee} and Christian Borch",
year = "2022",
month = apr,
day = "1",
doi = "10.1177/03063127211048515",
language = "English",
volume = "52",
pages = "277--302",
journal = "Social Studies of Science",
issn = "0306-3127",
publisher = "SAGE Publications",
number = "2",

}

RIS

TY - JOUR

T1 - Systemic failures and organizational risk management in algorithmic trading

T2 - Normal accidents and high reliability in financial markets

AU - Min, Bo Hee

AU - Borch, Christian

PY - 2022/4/1

Y1 - 2022/4/1

N2 - 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.

AB - 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.

KW - Faculty of Social Sciences

KW - algorithmic trading

KW - financial regulation

KW - flash crash

KW - high-reliability organizations

KW - normal accidents theory

KW - risk

U2 - 10.1177/03063127211048515

DO - 10.1177/03063127211048515

M3 - Journal article

C2 - 34612758

VL - 52

SP - 277

EP - 302

JO - Social Studies of Science

JF - Social Studies of Science

SN - 0306-3127

IS - 2

ER -

ID: 319888665