Estimating the Volatility of Discrete Stock Prices
提出一种股票价格波动率估计方法，能消除观测价格离散性导致的偏差，在低中价股票中表现优于传统估计量，且对价格变动时间间隔的误设具有稳健性。
This paper introduces an estimator of stock price volatility that eliminates, at least asymptotically, the biases that are caused by the discreteness of observed stock prices. Assuming that the observed stock prices are continuously monitored, an estimator is constructed using the notion of how quickly the price changes rather than how much the price changes. It is shown that this estimator has desirable asymptotic properties, including consistency and asymptotic normality. Also, through a simulation study, the authors show that it outperforms natural estimators for the low- and middle-priced stocks. Furthermoret, he simulation study demonstratest hat the proposed estimator is robust to certain misspecifications in measuring the time between price changes.