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About Application of Deep Reinforcement Learning To Algo Trading
This paper presents a novel approach using deep reinforcement learning (DRL) to solve the algorithmic trading problem of determining optimal trading positions over time. It proposes a new DRL trading algorithm called TDQN to maximize performance on stock markets. Promising results are reported for TDQN following a new performance assessment methodology.
Detailed Information
| Author: | ['Alfred Huang'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 19 |
| Language: | English |
| Format: | |
| Price: | FREE |
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