The cryptographic currency market is an emerging venue for traders looking to diversify their investments. We investigate the use of genetic programming (GP) for finding attractive technical patterns in a cryptocurrency market. We decompose the problem of automatic trading into two parts, mining useful signals and applying them to trading strategies, and focus our attention on the former. Extensive experiments are performed to analyze the factors that affect the quality of the solutions found by the proposed GP system. With the introduction of domain knowledge through extended function sets and the inclusion of diversity preserving mechanism, we show that the proposed GP system successfully finds attractive technical patterns. Out-of-sample performance of the patterns indicates that the GP consistently finds signals that are profitable and frequent. A trading simulation with the generated patterns suggests that the captured signals are indeed useful for portfolio optimization.

中文翻译：

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在加密货币市场中找到有吸引力的技术模式

加密货币市场是寻求多样化投资的交易者的新兴场所。我们调查了遗传编程（GP）在加密货币市场中寻找有吸引力的技术模式的使用。我们将自动交易的问题分解为两个部分：挖掘有用的信号并将其应用于交易策略，然后将注意力集中在前者上。进行了广泛的实验以分析影响提出的GP系统发现的解决方案质量的因素。通过扩展功能集引入领域知识并包括多样性保留机制，我们证明了所提出的GP系统成功地找到了有吸引力的技术模式。模式的样本外性能表明GP持续发现有利可图且频繁出现的信号。具有生成模式的交易模拟表明，捕获的信号确实对投资组合优化有用。