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Long memory in volatility and trading volume

机译:对波动率和交易量记忆犹新

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We use fractionally-integrated time-series models to investigate the joint dynamics of equity trading volume and volatility. Bollerslev and Jubinski (1999) show that volume and volatility have a similar degree of fractional integration, and they argue that this evidence supports a long-run view of the mixture-of-distributions hypothesis. We examine this issue using more precise volatility estimates obtained using high-frequency returns (i.e., realized volatilities). Our results indicate that volume and volatility both display long memory, but we can reject the hypothesis that the two series share a common order of fractional integration for a fifth of the firms in our sample. Moreover, we find a strong correlation between the innovations to volume and volatility, which suggests that trading volume can be used to obtain more precise estimates of daily volatility for cases in which high-frequency returns are unavailable.
机译:我们使用分数积分时间序列模型来研究股票交易量和波动率的联合动态。 Bollerslev和Jubinski(1999)表明,数量和波动率具有相似程度的分数积分,他们认为,这一证据支持对分布混合假设的长期观点。我们使用高频回报率(即已实现的波动率)获得的更精确的波动率估算来研究此问题。我们的结果表明,数量和波动率都显示出较长的记忆力,但是我们可以拒绝以下假设:对于我们样本中五分之一的公司,两个系列具有相同的分数积分阶数。此外,我们发现交易量和波动率之间的创新密切相关,这表明在无法获得高频收益的情况下,交易量可用于获得每日波动率的更精确估计。

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