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The Human Behavioral Response to Automated Trading
Abstract
The use of computer algorithms by human traders in markets has been steadily increasing. These electronic agents or proxies vary in terms of purpose and complexity, however, most of them first require some input on the part of the human trader and then perform the rest of the trading task autonomously. This paper proposes a theoretical model of human behavior that can be used to detect behavioral biases in commodity markets populated by humans and electronic proxies. The model's predictions are tested with the help of laboratory experiments with economically-motivated human subjects. Results suggests that the usefulness of automated trading is initially diminished by behavioral biases arising from attitudes towards technology. In some cases, the biases disappear with experience and in others they do not.
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