TraderNet-CRv2
Unverified ML strategy on Crypto by kochlisGit. BotFinder score 18 out of 100.
TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets
Source: github
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TraderNet-CRv2
TraderNet-CRv2 TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets Description This system architecture is an extended version of the original TraderNet-CR architecture, which is described by this paper: https://link.springer.com/chapter/10.1007/978-3-031-08333-425. In this work, we combine Proximal Policy Optimization algorithm (PPO), which is a DRL learning algorithm, with 2 rule-based safety mechanisms: N-Consecutive & Smurfing. Our experiments on 5 popular cryptocurrencies show very promising results. Technical Indicators Technical analysis has been applied on market data in order to train TraderNet. The following popular technical indicators have been used: EMA (Exponential Moving Average) DEMA (Double-Exponential Moving Average) MACD (Moving Average Convergence/Divergenc) AROON CCI (Commodity Channel Inde) ADX (Average Directional Inde) STOCH (Stochastic Oscillator) RSI (Relative Strength Index) OBV (On-Balance Volume) BBANDS (Bolliger Bands) VWAP (Volume-Weighted Average Pric) ADL (Accumulation/Distribut
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