【摘要】 研究一种可由投资者依据其经验与直觉,从股票时间序列中挖掘交易决策规则的方法。它根据投资 者事先确定的相似偏好以及设定的买卖序列模板从历史价格序列中识别出与模板相似的形态;按相似度大 小划分不同交易决策区间,反映交易决策时机;然后计算各策略组合的收益,构造t统计量在统计显著性基础 上获取交易规则。该系统也能用于检验一些已有形态操作方法的有效性。更多还原

【Abstract】 This paper proposes a method by which investors can acquire some trading rules from stock time series based on their experience and intuition. It can recognize similar chart from history price series via pre-defined chart pattern and similarity preference. Partitioning similarity value into several intervals, and computing the return of each buy & sell interval pair, some trading rules are obtained based on statistical hypothesis tests. This system can also be used to verify the validity of some technical chart patterns.更多还原