Automated Stock Trading in PLAT
نویسنده
چکیده
This report documents the development of an autonomous stock trading agent within the framework of the Penn-Lehman Automated Trading (PLAT) simulator. The three approaches presented take inspiration from reinforcement learning, myopic trading using regression-based price prediction, and market making. The performance of these approaches is assessed separately using a fixed opponent strategy, SOBI. Controlled experiments are described that isolate the effects of individual parameters of each strategy. Finally, a comparative analysis of the strategies is presented and suggestions are discussed for future work.
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