Estimation of Stock Price Variances and Serial Covariances from Discrete Observations
股票价格离散性给价格序列带来噪声，导致标准方差和序列协方差估计量高估真实值。本文推导了近似公式来调整这些估计量，适用于日度数据。
Stock price discreteness adds noise to price series. The noise increases return variances and adds negative serial correlation to return series. Standard variance and serial covari? ance estimators therefore overestimate the variance and serial covariance of the under? lying stock values. Discreteness-induced variance and serial covariance depend on under? lying volatility and on the size of the bid/ask spread. Simple formulas for approximating the effects of discreteness on variance and serial correlation are derived and presented. The approximations, which are accurate in daily data, can be used to adjust the standard variance and serial covariance estimators.