TY - JOUR
T1 - Machines that make and keep promises - Lessons for contract automation from algorithmic trading on financial markets
AU - Schmidt-Kessen, Maria José
AU - Eenmaa, Helen
AU - Mitre, Maya
N1 - Publisher Copyright:
© 2022 Maria José Schmidt-Kessen, Helen Eenmaa, Maya Mitre
PY - 2022/9
Y1 - 2022/9
N2 - An important part of the criticism raised against the adoption of advanced contract automation relates to the inflexibility of automated contracts. Drawing on rational choice theory, we explain why inflexibility, when seen as a constraint, can ultimately not only enhance welfare but also enable cooperation on algorithmic markets. This illuminates the need to address the inflexibility of contracting algorithms in a nuanced manner, distinguishing between inflexibility as a potentially beneficial constraint on the level of transactions, and inflexibility as a set of systemic risks and changes arising in markets employing inflexible contracting algorithms. Using algorithmic trading in financial markets as an example, we show how the automation of finance has brought about institutional changes in the form of new regulation to hedge against systemic risks from inflexibility. Analyzing the findings through the lens of new institutional economics, we explain how widespread adoption of contract automation can put pressure on institutions to change. We conclude with possible lessons that algorithmic finance can teach to markets deploying algorithmic contracting.
AB - An important part of the criticism raised against the adoption of advanced contract automation relates to the inflexibility of automated contracts. Drawing on rational choice theory, we explain why inflexibility, when seen as a constraint, can ultimately not only enhance welfare but also enable cooperation on algorithmic markets. This illuminates the need to address the inflexibility of contracting algorithms in a nuanced manner, distinguishing between inflexibility as a potentially beneficial constraint on the level of transactions, and inflexibility as a set of systemic risks and changes arising in markets employing inflexible contracting algorithms. Using algorithmic trading in financial markets as an example, we show how the automation of finance has brought about institutional changes in the form of new regulation to hedge against systemic risks from inflexibility. Analyzing the findings through the lens of new institutional economics, we explain how widespread adoption of contract automation can put pressure on institutions to change. We conclude with possible lessons that algorithmic finance can teach to markets deploying algorithmic contracting.
KW - Algorithmic contracts
KW - Algorithmic trading
KW - Computable contracts
KW - Constrained maximization
KW - Constraints
KW - Contract law values
KW - Financial markets
KW - Inflexibility
KW - New institutional economics
KW - Smart contracts
UR - http://www.scopus.com/inward/record.url?scp=85133456653&partnerID=8YFLogxK
U2 - 10.1016/j.clsr.2022.105717
DO - 10.1016/j.clsr.2022.105717
M3 - Article
AN - SCOPUS:85133456653
SN - 0267-3649
VL - 46
JO - Computer Law and Security Review
JF - Computer Law and Security Review
M1 - 105717
ER -