使用体积时间平均法重新审视Epps效应：R中的练习
Revisiting the Epps effect using volume time averaging: An exercise in R
摘要：
我们重新审视并证明了埃普斯效应使用两个著名的非参数协方差估计; Malliavin和Mancino（MM），和Hayashi和Yoshida（HY）估计。通过对约翰内斯堡证券交易所的交易和报价数据进行统计分析，发现在约翰内斯堡证券交易所的前10名股票中存在Epps效应。具体地说，我们比较日历时间采样与两个体积时间采样方法：资产内在体积时间平均，和体积时间平均同步的体积时间在资产相对于最少和最流动的资产时钟。我们重申了在许多文献中提出的论点，即MM估计量更能代表交易时间的现实，因为它不会高估异步事件驱动世界中的短期相关性。我们确认了众所周知的市场现象，目的是提供一些标准化的基于R的仿真工具。
英文摘要：
We revisit and demonstrate the Epps effect using two well-known non-parametric covariance estimators; the Malliavin and Mancino (MM), and Hayashi and Yoshida (HY) estimators. We show the existence of the Epps effect in the top 10 stocks from the Johannesburg Stock Exchange (JSE) by various methods of aggregating Trade and Quote (TAQ) data. Concretely, we compare calendar time sampling with two volume time sampling methods: asset intrinsic volume time averaging, and volume time averaging synchronised in volume time across assets relative to the least and most liquid asset clocks. We reaffirm the argument made in much of the literature that the MM estimator is more representative of trade time reality because it does not over-estimate short-term correlations in an asynchronous event driven world. We confirm well known market phenomenology with the aim of providing some standardised R based simulation tools.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
