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Measuring High-Frequency Causality Between Returns, Realized Volatility and Implied Volatility

机译:衡量收益,实际波动率和隐含波动率之间的高频因果关系

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摘要

In this paper, we provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility, and find that implied volatilities are essential for assessing the volatility feedback effect. The leverage hypothesis asserts that return shocks lead to changes in conditional volatility, while the volatility feedback effect theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On observing that a central difference between these alternative explanations lies in the direction of causality, we consider vector autoregressive models of returns and realized volatility and we measure these effects along with the time lags involved through short-run and long-run causality measures proposed in Dufour and Taamouti (2010), as opposed to simple correlations. We analyze 5-minute observations on S&P 500 Index futures contracts, the associated realized volatilities (before and after filtering jumps through the bispectrum) and implied volatilities. Using only returns and realized volatility, we find a strong dynamic leverage effect over the first three days. The volatility feedback effect appears to be negligible at all horizons. By contrast, when implied volatility is considered, a volatility feedback becomes apparent, whereas the leverage effect is almost the same. These results can be explained by the fact that volatility feedback effect works through implied volatility which contains important information on future volatility, through its nonlinear relation with option prices which are themselves forward-looking. In addition, we study the dynamic impact of news on returns and volatility. First, to detect possible dynamic asymmetry, we separate good from bad return news and find a much stronger impact of bad return news (as opposed to good return news) on volatility. Second, we introduce a concept of news based on the difference between implied and realized volatilities (the variance risk premium) and we find that a positive variance risk premium (an anticipated increase in variance) has more impact on returns than a negative variance risk premium.
机译:在本文中,我们提供了关于收益与波动率之间相互作用的两种替代机制的证据:杠杆效应和波动率反馈效应。我们强调区分实际波动率和隐含波动率的重要性,并发现隐含波动率对于评估波动率反馈效应至关重要。杠杆率假设断言,回报冲击会导致条件波动率的变化,而波动率反馈效应理论则认为回报冲击可能是由于条件波动率随时间的风险溢价而引起的。在观察到这些替代解释之间的主要区别在于因果关系的方向时,我们考虑了收益和实现的波动率的矢量自回归模型,并通过提出的短期和长期因果关系措施来衡量这些影响以及时滞。 Dufour和Taamouti(2010),与简单的相关性相反。我们分析了对S&P 500指数期货合约的5分钟观察,相关的已实现波动率(在通过双谱过滤跳跃之前和之后)和隐含波动率。仅使用收益和已实现的波动率,我们发现前三天有很强的动态杠杆效应。波动性反馈效应似乎在所有情况下都可以忽略不计。相反,当考虑隐含波动率时,波动率反馈变得明显,而杠杆效应几乎相同。可以通过以下事实来解释这些结果:波动率反馈效应通过隐含波动率起作用,其中隐含波动率包含有关未来波动率的重要信息,通过其与本身具有前瞻性的期权价格之间的非线性关系来实现。此外,我们研究了新闻对收益和波动性的动态影响。首先,为了检测可能的动态不对称性,我们将不良收益消息与不良收益消息分开,并发现不良收益消息(相对于不良收益消息)对波动性的影响更大。其次,我们基于隐含波动率和实际波动率之间的差异(方差风险溢价)引入新闻概念,并且发现正方差风险溢价(方差的预期增加)对收益的影响要大于负方差风险溢价。 。

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