We develop a nonparametric test for the temporal dependence of jump occurrences in the population. The test is consistent against all pairwise serial dependence, and is robust to the jump activity level and the choice of sampling scheme. We establish asymptotic normality and local power property for a rich set of local alternatives, including both self-exciting and/or self-inhibitory jumps. Simulation study confirms the robustness of the test and reveals its competitive size and power performance over existing tests. In an empirical study on high-frequency stock returns, our procedure uncovers a wide array of autocorrelation profiles of jump occurrences for different stocks in different time periods.

中文翻译：

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自相关跳跃发生的一致且稳健的测试

我们开发了一种非参数检验，用于检验群体中跳跃事件的时间依赖性。该测试对所有成对的序列依赖性都是一致的，并且对跳跃活动水平和采样方案的选择具有鲁棒性。我们为一组丰富的局部替代方案建立渐近正态性和局部功率属性，包括自激和/或自抑制跳跃。仿真研究证实了测试的稳健性，并揭示了其与现有测试相比具有竞争力的尺寸和功率性能。在对高频股票收益的实证研究中，我们的程序揭示了不同时间段内不同股票跳跃发生的一系列自相关曲线。