Adversarial trading

• URL: http://arxiv.org/abs/2101.03128v1
• Date: Wed, 16 Dec 2020 16:08:22 GMT
• Title: Adversarial trading
• Authors: Alexandre Miot
• Abstract summary: We show that adversarial samples can be implemented in a trading environment and have a negative impact on certain market participants. This could have far reaching implications for financial markets either from a trading or a regulatory point of view.
• Score: 91.3755431537592
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Adversarial samples have drawn a lot of attention from the Machine Learning community in the past few years. An adverse sample is an artificial data point coming from an imperceptible modification of a sample point aiming at misleading. Surprisingly, in financial research, little has been done in relation to this topic from a concrete trading point of view. We show that those adversarial samples can be implemented in a trading environment and have a negative impact on certain market participants. This could have far reaching implications for financial markets either from a trading or a regulatory point of view.

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