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On the iterative plug-in algorithm for estimating diurnal patterns of financial trade durations

机译:关于迭代插件算法估计金融交易时间的日间模式

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This paper discusses the detailed performance of an iterative plug-in (IPI) bandwidth selector for estimating the diurnal duration pattern in a Semi-ACD (semiparametric autoregressive conditional duration) model. For this purpose a large simulation study was carried out. The effects of different factors, which affect the selected bandwidth are discussed in detail. The simulated results and data examples show that the proposed IPI algorithm works very well in practice and that the Semi-ACD model in general is clearly superior to the parametric ACD model, if there is a deterministic trend in the duration data. It is also shown that the bandwidth selection, and the estimation of the diurnal pattern and the model parameters will all be clearly improved, if the sample size is enlarged. According to the goodness-of-fit of the estimated diurnal pattern, a best combination of the above-mentioned factors is found. Moreover, a comparative study shows that our proposal usually outperforms the commonly used cubic spline.
机译:本文讨论了迭代插件(IPI)带宽选择器的详细性能,该带宽选择器用于估计Semi-ACD(半参数自回归条件持续时间)模型中的昼夜持续时间模式。为此,进行了大型仿真研究。详细讨论了影响所选带宽的不同因素的影响。仿真结果和数据示例表明,所提出的IPI算法在实践中效果很好,并且如果持续时间数据中存在确定性趋势,则Semi-ACD模型通常明显优于参数ACD模型。还表明,如果扩大样本大小,则带宽选择以及昼夜模式和模型参数的估计都将得到明显改善。根据估计的昼夜模式的拟合优度,找到上述因素的最佳组合。此外,一项比较研究表明,我们的建议通常优于常用的三次样条。

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