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In response to the flash crashes and market manipulations blamed on high-frequency trading (HFT), algorithms have been brought inside the regulatory perimeter. This paper focuses on the most ambitious regulation directed at the practice: the algorithm-tagging rule in the German High-Frequency Trading Act. Fifteen interviews with stakeholders in the Act’s implementation serve to reconstruct how regulators defined an algorithm and help pose the question of to what extent regulatory definitions and data need accurately to represent financial practices to be useful. Although tentative in its findings, the research suggests that the algorithm-tagging rule may be providing valuable signals in the noise to trade surveillance officers and having virtuous effects on the cultures of trading firms. The conclusion argues that sociologists of finance should adopt a more balanced approach when evaluating regulatory technologies and heed MacKenzie’s 2005 call to open up their black boxes.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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