Reinforcement learning crypto trading

reinforcement learning crypto trading

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Crypto Trading Using FinRL
In this work Deep Reinforcement Learning is applied to trade bitcoin. More precisely, Double and Dueling Double Deep Q-learning Networks are compared over a. In this paper, we propose a practical approach to address backtest overfitting for cryptocurrency trading using deep reinforcement learning. This research produces a deep reinforcement learning model for algorithmic trading of cryptocurrencies. The model aims to help traders earn greater profits.
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  • reinforcement learning crypto trading
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    calendar_month 15.01.2022
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    calendar_month 19.01.2022
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    calendar_month 21.01.2022
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Abstract The Bitcoin market has experienced unprecedented growth, attracting financial traders seeking to capitalize on its potential. For that reason, we further improve the reward function by transforming PNL percentages to natural logarithmic returns. Volume-Weighted Average price or VWAP is a volume technical analysis tool, which as the name suggests, is the average price of an asset weighted by the total trading volume, over a period of time [ 14 ]. These tools enhance the performance of trading strategies and accuracy of price prediction