Increasingly autonomous algorithmic agents in financial trading may
involve significant risks to market integrity. This study explores
how such algorithmic traders may independently exploit manipulative
and collusive tactics. Using the proprietary trading industry as a
case study, we explore new emerging threats to the application of
established legal concepts of liability for algorithmic market
abuse, taking an interdisciplinary stance between financial
regulation, law & economics, and computational finance. We show
how the ‘black box’ nature of specific artificial intelligence (AI)
trading systems can subvert existing market abuse laws, which are
based upon traditional liability concepts and tests such as ‘intent’
and ‘causation’. To address the shortcomings of the present legal
framework, we develop a number of guiding principles for legal
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