Cryptocurrency Trading Agent Using Deep Reinforcement Learning

– The paper presents a deep reinforcement learning algorithm for cryptocurrency .
– The algorithm's performance was outperformed by the -and-hold benchmark.

– The paper presents a deep reinforcement learning algorithm for cryptocurrency trading.
– The algorithm was tested with Bitcoin, Ethereum, and Litecoin.

The paper presents a deep reinforcement learning algorithm, Duelling DQN, for trading in cryptocurrency markets. However, the algorithm's performance was outperformed by the buy-and-hold strategy.

– The proposed algorithm underperformed compared to the buy-and-hold benchmark.
– No other limitations are mentioned in the given information.

– Deep reinforcement learning algorithm (Duelling DQN)
– Buy-and-hold benchmark

– The proposed algorithm did not outperform the buy-and-hold benchmark.
– Traders may not achieve short-term profit maximization using the Duelling DQN agent.

– Duelling DQN agent underperformed the buy-and-hold benchmark.
– No specific details about the performance metrics provided.

– Deep reinforcement learning algorithm used for cryptocurrency trading.
– Algorithm tested with Bitcoin, Ethereum, and Litecoin, but underperformed buy-and-hold strategy.

– Paper focuses on short-term profit maximization in cryptocurrency trading.
– Presents a deep reinforcement learning algorithm, Duelling DQN, for trading.

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