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What Does the Volatility Risk Premium Say About Liquidity Provision and Demand for Hedging Tail Risk?

机译:波动性风险溢价对流动性准备金和对冲尾巴风险的需求有何看法?

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摘要

This article provides a data-driven analysis of the volatility risk premium, using tools from high-frequency finance and Big Data analytics. We argue that the volatility risk premium, loosely defined as the difference between realized and implied volatility, can best be understood when viewed as a systematically priced bias. We first use ultra-high-frequency transaction data on SPDRs and a novel approach for estimating integrated volatility on the frequency domain to compute realized volatility. From that we subtract the daily VIX, our measure of implied volatility, to construct a time series of the volatility risk premium. To identify the factors behind the volatility risk premium as a priced bias, we decompose it into magnitude and direction. We find compelling evidence that the magnitude of the deviation of the realized volatility from implied volatility represents supply and demand imbalances in the market for hedging tail risk. It is difficult to conclusively accept the hypothesis that the direction or sign of the volatility risk premium reflects expectations about future levels of volatility. However, evidence supports the hypothesis that the sign of the volatility risk premium is indicative of gains or losses on a delta-hedged portfolio.
机译:本文使用高频金融和大数据分析工具提供了数据驱动的波动率风险溢价分析。我们认为,将波动率风险溢价(宽松地定义为已实现波动率和隐含波动率之间的差额),最好是将其视为系统定价的偏差。我们首先使用SPDR上的超高频交易数据和一种新颖的方法来估算频域上的综合波动率,以计算实现的波动率。从中我们减去每日VIX(隐含波动率的量度)来构建波动率风险溢价的时间序列。为了将波动率风险溢价背后的因素识别为价格偏差,我们将其分解为大小和方向。我们发现令人信服的证据表明,已实现波动率与隐含波动率的偏差幅度代表着对冲尾部风险的市场供需失衡。很难最终接受以下假设,即波动率风险溢价的方向或信号反映了对未来波动率水平的预期。但是,证据支持以下假设,即波动风险溢价的迹象表明对冲组合中的收益或损失。

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