Abstract
Quant Investment research has become more active with the development of deep learning technology. In this paper, we propose an auto-selling model based on reinforcement learning higher returns using Bidirectional Long Short-Term Memory (Bi-LSTM) high-priced predictive models. The proposed model adjusts the immediate compensation and delay compensation values by applying the predicted high price to the compensation function. In addition, we compared the automatic trading model of the closing price with the automatic trading model applied with the auxiliary index value. As a result of the experiment, the maximum return of the proposed model was higher, and based on this, it was concluded that the expensive atuomatic trading model generates higher profits than the existing automatic trading model.
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