A closed-form quasi-maximum likelihood estimator of bid-ask spread

We propose a closed-form quasi-maiximum likelihood (QML) estimator of bid-ask spread from daily high-low ranges under both near-ideal and overnight theoretical frameworks. As is shown that the high-low spread estimator is more precise than that only using closing prices, we pay attention to investigating the statistical properties of such kind of range-based spread estimators, and further demonstrating that our estimator is free from overnight adjustment with higher estimation efficiency. Simulation studies show that the QML estimator has relatively lower bias and RMSE, compared with other prevalent low-frequency measures, and the results are more significant under overnight conditions.