Realized Semi(co)variation: Signs That All Volatilities are Not Created Equal
综述了基于高频数据构建的“好”与“坏”波动率测度，涵盖单变量半方差、多变量半协方差和半贝塔，并讨论其在波动率预测和资产定价中的实证发现。
Abstract I provide a selective review of recent developments in financial econometrics related to measuring, modeling, forecasting, and pricing “good” and “bad” volatilities based on realized variation type measures constructed from high-frequency intraday data. An especially appealing feature of the different measures concerns the ease with which they may be calculated empirically, merely involving cross-products of signed, or thresholded, high-frequency returns. I begin by considering univariate semivariation measures, followed by multivariate semicovariation and semibeta measures, before briefly discussing even richer partial (co)variation measures. I focus my discussion on practical uses of the measures emphasizing what I consider to be the most noteworthy empirical findings to date pertaining to volatility forecasting and asset pricing.