An Econometric Analysis of Volatility Discovery
研究了股票波动率随机过程中的信息处理，利用分数协整技术分解市场特定积分方差，提出波动率发现度量，并建立其极限分布，实证显示交易场所对波动率信息处理存在差异。
We investigate information processing in the stochastic process driving stock's volatility (volatility discovery).We apply fractionally cointegration techniques to decompose the estimates of the market-specific integrated variances into an estimate of the common integrated variance of the efficient price and a transitory component.The market weights on the common integrated variance of the efficient price are the volatility discovery measures.We relate the volatility discovery measure to the price discovery framework and formally show their roles on the identification of the integrated variance of the efficient price.We establish the limiting distribution of the volatility discovery measures by resorting to both long span and in-fill asymptotics.The empirical application is in line with our theoretical results, as it reveals that trading venues incorporate new information into the stochastic volatility process in an individual manner and that the volatility discovery analysis identifies a distinct information process than that based on the price discovery analysis.