The purpose of this article is to study serial correlations, allowing for unconditional heteroscedasticity and time-varying probabilities of zero financial returns. Depending on the set-up, we investigate how the standard autocorrelations can be accommodated to deliver an accurate representation of the serial correlations of stock price changes. We shed light on the properties of the different serial correlations measures by means of Monte Carlo experiments. Theoretical results are also illustrated on shares from the Chilean stock market and Facebook stock intraday data.

中文翻译：

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零收益股票的相关性分析

本文的目的是研究序列相关性，允许无条件异方差性和零财务回报的时变概率。根据设置，我们研究如何适应标准自相关性，以准确表示股票价格变化的序列相关性。我们通过蒙特卡罗实验阐明了不同序列相关性度量的属性。智利股市的股票和 Facebook 股票盘中数据也说明了理论结果。