applied sciences Article Recommending Cryptocurrency Trading Points with Deep Reinforcement Learning Approach Otabek Sattarov 1 , Azamjon Muminov 1 , Cheol Won Lee 1, Hyun Kyu Kang 1, Ryumduck Oh 2, Junho Ahn 2, Hyung Jun Oh 3 and Heung Seok Jeon 1,* 1 Department of Software Technology, Konkuk University, Chungju 27478, Korea;
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[email protected]; Tel.: +82-43-840-3621 Received: 15 January 2020; Accepted: 19 February 2020; Published: 22 February 2020 Abstract: The net profit of investors can rapidly increase if they correctly decide to take one of these three actions: buying, selling, or holding the stocks. The right action is related to massive stock market measurements. Therefore, defining the right action requires specific knowledge from investors. The economy scientists, following their research, have suggested several strategies and indicating factors that serve to find the best option for trading in a stock market. However, several investors’ capital decreased when they tried to trade the basis of the recommendation of these strategies. That means the stock market needs more satisfactory research, which can give more guarantee of success for investors. To address this challenge, we tried to apply one of the machine learning algorithms, which is called deep reinforcement learning (DRL) on the stock market.