Trading Beyond Understanding

Nyhet

Machine Learning, Risk, and Markets

Inbunden, Engelska, 2026

2 249 kr

Kommande

Machine learning is fundamentally transforming financial markets. Where trading strategies were once crafted by human experts—executed manually or through pre-coded rules—firms now build models that generate the strategies themselves. These are not just tools but trading automatons: semi-independent systems designed to learn from markets and act on their own. Drawing on over a decade of fieldwork in financial markets, Christian Borch offers a rare inside look at how these systems are built, the risks they pose, and how they challenge our understanding of markets and decision-making. As trading automatons grow more complex and opaque—even to their designers—new sociological questions emerge: What happens when machines become the primary agents in markets? And how should we understand economic action when human judgment is no longer at the center? Trading Beyond Understanding is a powerful investigation of machine agency, market transformation, and the shifting boundaries between technological systems and social life.

Produktinformation

Utgivningsdatum2026-03-10
Mått152 x 229 x undefined mm
FormatInbunden
SpråkEngelska
SerieCurrencies: New Thinking for Financial Times
Antal sidor256
FörlagStanford University Press
ISBN9781503636804

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"Borch's interviews and observations root the book firmly in the everyday life of algorithmic finance. What he writes is always sober, clear and well-informed; there is no directly competing work. This is, in short, scholarship of the highest order. An important, influential book." - Donald MacKenzie, University of Edinburgh "The book is a first in offering a comprehensive, empirical analysis of the rapid internal development of automated trading in trading firms from an economic sociology perspective. Theorists will love the book too for its deep cutting questions about the central notion of agency and actorhood in social science. The book is written in a pleasantly narrative style, an enormous plus when the subject matter is technical and as cut off from public view and scientific understanding as in ML." - Karin Knorr Cetina, University of Chicago