相互关联证券的波动率发现

Christian Nguenang
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引用次数: 0

摘要

在许多国家上市的证券的波动率中,新的波动率在哪里?虽然文献关注的是信息进入价格的位置,但我开发了一个框架来研究每个市场的波动如何对资产的永久波动做出贡献。我建立了一个VECM与自回归随机波动(ASV)框架估计使用MCMC方法和贝叶斯推理。该规范允许定义市场对波动性发现的贡献的度量。在申请中,我研究了在伦敦金属交易所交易的一些金属的现金和3个月期货市场。我还研究了欧洲斯托克50指数及其期货。我发现,对于大多数证券,价格发现发生在现货市场,而波动性发现主要发生在期货市场。总体而言,结果表明信息发现和波动性发现不一定具有相同的决定因素。
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Volatility Discovery across Interlinked Securities
Where does new volatility enter the volatility of securities listed in many countries? While literature has focused on where information enters the price, I develop a framework to study how each market’s volatility contributes to the permanent volatility of the Asset. I build a VECM with an Autoregressive Stochastic Volatility (ASV) framework estimated using the MCMC method and Bayesian inference. This specification allows defining the measures of a market’s contribution to volatility discovery. In the application, I study cash and 3-months futures markets of some metals traded on the London Metals Exchange. I also study the EURO STOXX 50 Index and its futures. I find that for most the securities, while price discovery happens on the cash market, the volatility discovery mostly happens in the futures market. Overall, the results suggest that information discovery and volatility discovery do not necessarily have the same determinants.
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