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摘要翻译：
我们证明了在序列数据中，当前结果对过去结果条纹的条件依赖性的一个常见测度中存在一个微妙但实质性的偏差。这种条纹选择偏差的大小通常随着序列变长而减小，但条纹长度增加，并且在经验工作中经常使用的序列长度范围内仍然很大。我们观察到有影响力的热手谬误文献中的规范研究，以及复制，容易受到偏见的影响。在纠正偏差后，我们发现规范研究的长期结论是颠倒的。
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英文标题：
《Surprised by the Hot Hand Fallacy? A Truth in the Law of Small Numbers》
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作者：
Joshua B. Miller, Adam Sanjurjo
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最新提交年份：
2019
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分类信息：
一级分类：Economics 经济学
二级分类：General Economics 一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
We prove that a subtle but substantial bias exists in a common measure of the conditional dependence of present outcomes on streaks of past outcomes in sequential data. The magnitude of this streak selection bias generally decreases as the sequence gets longer, but increases in streak length, and remains substantial for a range of sequence lengths often used in empirical work. We observe that the canonical study in the influential hot hand fallacy literature, along with replications, are vulnerable to the bias. Upon correcting for the bias we find that the long-standing conclusions of the canonical study are reversed.
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PDF链接：
https://arxiv.org/pdf/1902.01265
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