Computational Intelligence for Evolving Trading Rules
本文描述了一个自适应计算智能系统，通过模糊逻辑规则库和人工演化过程学习交易规则，并在动态市场条件下表现良好，同时使用行业和学术界广泛接受的投资组合评估工具进行了全面分析。
This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.