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Validity of Edgeworth expansions for realized volatility estimators

机译:Edgeworth展开对于已实现波动率估计的有效性

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Themain contribution of this paper is to establish the formal validity of Edgeworth expansions for realized volatility estimators. First, in the context of no microstructure effects, our results rigorously justify the Edgeworth expansions for realized volatility derived in Gonc, alves andMeddahi (2009, Econometrica 77, 283-306). Second, we show that the validity of the Edgeworth expansions for realized volatility might not cover the optimal two-point distribution wild bootstrap proposed by Gonc, alves and Meddahi. Then, we propose a new optimal nonlattice distribution, which ensures the second-order correctness of the bootstrap. Third, in the presence of microstructure noise, based on our Edgeworth expansions, we show that the new optimal choice proposed in the absence of noise is still valid in noisy data for the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009, Bernoulli 15, 634-658). Finally, we show how confidence intervals for integrated volatility can be constructed using these Edgeworth expansions for noisy data. Our Monte Carlo simulations show that the intervals based on the Edgeworth corrections have improved the finite sample properties relatively to the conventional intervals based on the normal approximation.
机译:本文的主要贡献在于建立Edgeworth展开对于已实现波动率估计的形式有效性。首先,在没有微观结构影响的情况下,我们的结果严格证明了Edgeworth扩展对于从Gonc,alves和Medahi(2009,Econometrica 77,283-306)得出的已实现波动率的合理性。其次,我们表明Edgeworth展开对于已实现波动率的有效性可能无法涵盖Gonc,alves和Meddahi提出的最优两点分布野生自举。然后,我们提出了一个新的最优非晶格分布,该分布可确保自举的二阶正确性。第三,在存在微结构噪声的情况下,基于Edgeworth展开,我们表明,对于有噪声的数据,对于Podolskij和Vetter(2009,伯努利15,634-658)。最后,我们展示了如何使用这些Edgeworth扩展为嘈杂数据构建积分波动率的置信区间。我们的蒙特卡洛模拟显示,基于Edgeworth校正的区间相对于基于法线逼近的常规区间改善了有限样本属性。

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