A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices

We propose a new method to estimate the bid-ask spread when quote data are not available. Compared to other low-frequency estimates, it utilizes a wider information set, namely, close, high, and low prices, which are readily available. In the absence of end-of-day quote data, it generally provides the highest cross-sectional and average time-series correlations with the TAQ effective spread benchmark. Moreover, it delivers the most accurate estimates for less liquid stocks. Our estimator has many potential applications including an accurate measurement of transaction cost, systematic liquidity risk, and commonality in liquidity for U.S. stocks dating back almost one century.