Reinforcement Learning with Self-Attention Networks for Cryptocurrency Trading

Reinforcement Learning with Self-Attention Networks for Cryptocurrency Trading

This work presents an application of self-attention networks for cryptocurrency trading. Cryptocurrencies are extremely volatile and unpredictable. Thus, cryptocurrency trading is challenging and involves higher risks than trading traditional financial assets such as stocks. To overcome the aforemen...

Full description

Bibliographic Details
Main Authors: Carlos Betancourt, Wen-Hui Chen
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
deep reinforcement learning
self-attention networks
cryptocurrency trading
fee minimization
Online Access:https://www.mdpi.com/2076-3417/11/16/7377

Internet

https://www.mdpi.com/2076-3417/11/16/7377

Similar Items