Adversarial trading

Alexandre Miot

Papers from arXiv.org

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.

Date: 2020-12
New Economics Papers: this item is included in nep-big
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2101.03128

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