摘要翻译：
本文利用27个股票市场的指数，实证研究了股票市场的有效程度是否与未来价格变化的预测能力有关。效率是指从过去的价格变动信息来看的弱形式有效市场假说(EMH)。预测功率与命中率相对应，命中率是利用样本外的最近邻预测法（NN法）计算出的实际价格变化方向与预测价格变化方向的一致性率。本文用Hurst指数和近似熵(ApEn)作为效率程度的定量度量。反映时间序列中各种时间相关性的Hurst指数与反映时间序列中随机性的ApEn值之间呈负相关关系。而对未来价格变动方向的平均预测力与Hurst指数呈强正相关，与APEN呈负相关。因此，当我们用过去的价格变化模式来分析市场时，市场效率较低的市场指数比市场效率较高的市场指数对未来价格变化的预测能力更强。此外，我们还证明了Hurst指数作为一种长期记忆性质的度量，在预测未来价格变化方面比ApEn和NN方法提供了更重要的信息。
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英文标题：
《Relationship between degree of efficiency and prediction in stock price
  changes》
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作者：
Cheoljun Eom, Gabjin Oh, Woo-Sung Jung
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最新提交年份：
2007
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
  This study investigates empirically whether the degree of stock market efficiency is related to the prediction power of future price change using the indices of twenty seven stock markets. Efficiency refers to weak-form efficient market hypothesis (EMH) in terms of the information of past price changes. The prediction power corresponds to the hit-rate, which is the rate of the consistency between the direction of actual price change and that of predicted one, calculated by the nearest neighbor prediction method (NN method) using the out-of-sample. In this manuscript, the Hurst exponent and the approximate entropy (ApEn) are used as the quantitative measurements of the degree of efficiency. The relationship between the Hurst exponent, reflecting the various time correlation property, and the ApEn value, reflecting the randomness in the time series, shows negative correlation. However, the average prediction power on the direction of future price change has the strongly positive correlation with the Hurst exponent, and the negative correlation with the ApEn. Therefore, the market index with less market efficiency has higher prediction power for future price change than one with higher market efficiency when we analyze the market using the past price change pattern. Furthermore, we show that the Hurst exponent, a measurement of the long-term memory property, provides more significant information in terms of prediction of future price changes than the ApEn and the NN method.
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PDF链接：
https://arxiv.org/pdf/0708.4178