The Relative Contribution of Jumps to Total Price Variance
研究了基于渐近结果的跳跃检验方法，发现日度z统计量表现良好，但微观结构噪声会降低检验效力，采用滞后策略可纠正偏差。实证表明跳跃解释了股票市场价格方差的7%。
We examine tests for jumps based on recent asymptotic results; we interpret the tests as Hausman-type tests. Monte Carlo evidence suggests that the daily ratio z-statistic has appropriate size, good power, and good jump detection capabilities revealed by the confusion matrix comprised of jump classification probabilities. We identify a pitfall in applying the asymptotic approximation over an entire sample. Theoretical and Monte Carlo analysis indicates that microstructure noise biases the tests against detecting jumps, and that a simple lagging strategy corrects the bias. Empirical work documents evidence for jumps that account for 7% of stock market price variance.