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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