Daniel Djupsjobacka
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引用次数: 3

摘要

本研究的目的是衡量和表征一天和一周的波动率和相关性的一些德国股票。为此,我们通过汇总短期收益的平方来衡量逐点数据的已实现波动率。成交量加权平均价格被用来过滤价格序列。按已实现波动率标准化的收益的分布性质显示为高斯分布或接近高斯分布。根据文献,我们还发现周收益比日收益更符合正态分布。此外,按已实现波动率标准化的周收益比每日标准化收益更符合正态分布。与对美国股票数据的类似研究相比,我们可以得出结论,回报率和已实现波动率的分布特性是相似的。在检验了已实现波动率的记忆后,我们发现它是高度不稳定的,这意味着参数波动率模型的预测性能很差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Properties of Realized Volatility and Correlation
The aim of this study is to measure and characterize one-day and one-week volatility and correlation on a number of German equities. For this purpose we measure the realized volatility from tick-by-tick data by summing up short term squared returns. Volume weighted average prices are used to filter the price series. The distributional properties of returns standardized by realized volatility are shown to be gaussian or close to gaussian. In accordance with the literature we also find that weekly returns are more normally distributed than daily returns. Also, weekly returns standardized by realized volatilities are found to be more normally distributed than daily standardized returns. In comparison to similar studies on U.S. equity data we can conclude that the distributional properties of returns and realized volatilities are alike. After examining the memory of realized volatility we find that it is highly unstable implying poor forecasting performance of parametric volatility models.
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