Robust Technical Trading with Fuzzy Knowledge-Based Systems
Robust Technical Trading with Fuzzy Knowledge-Based Systems
复制标题
DOI：
10.2139/ssrn.2996303
复制
发表时间：
2017-07
期刊：
影响因子：
--
通讯作者：
M. Nakano;Akihiko Takahashi;Soichiro Takahashi
中科院分区：
文献类型：
--
作者：
M. Nakano;Akihiko Takahashi;Soichiro Takahashi
本文提出了一个基于模糊知识系统（KBS）的稳健技术交易框架。特别是，我们的框架由两个模块组成，即（i）用于准备候选投资建议的模块和（ii）用于评估以构建表现良好的投资组合的模块。此外，我们的框架有效地利用模糊KBS来表示人类专家知识：准确地说，在第一个模块中，三组模糊IF-THEN规则实现了语言技术交易规则，这些规则是专门为在不同市场阶段获得良好表现而设计的。另一方面，第二个模块利用模糊逻辑根据实践中经常使用的多边绩效衡量标准来评估准备好的投资候选者。在样本外数值实验中，我们的框架成功生成了一系列投资组合，这些投资组合在长期低迷的日本股市中显示出长期令人满意的记录。
This paper proposes a framework of robust technical trading with fuzzy knowledge-based systems (KBSs). Particularly, our framework consists of two modules, i.e., (i) a module for preparing candidate investment proposals and (ii) a module for their evaluation to construct a well-performed portfolio. Moreover, our framework effectively utilizes fuzzy KBSs for representation of human expert knowledge: Precisely, in the 1st module, three sets of fuzzy IF-THEN rules implement linguistic technical trading rules, which are designed speci cally for getting well performance in different market phases. On the other hand, the 2nd module exploits fuzzy logic to evaluate the prepared investment candidates in terms of multilateral performance measures frequently used in practice. In an out-of-sample numerical experiment, our framework successfully generates a series of portfolios, which show long-term satisfactory records in the prolonged slumping Japanese stock market.