Before revision:  With the development combination of quantitative trading and reinforcement learning, more trading algorithms have achieved significant gains beyond the benchmark model Buy Hold (B H) . There is a certain gap between these algorithms and the real trading decision making scenarios. On the one hand, they only consider trading signals while ignoring the number of transactions. On the other hand, the information level considered by these algorithms is not rich enough, which limits the performance of these algorithms.
After revision:  With the development combination of quantitative trading and reinforcement learning, more trading algorithms have achieved significant gains beyond the benchmark model Buy Hold (B \&H) has been oversteped by many artificial intelligence trading algorithms. However, the information and process are not enough, which limits the performance of these algorithms.