Detecting Abnormal Bid-Ask Spread: A Comparison of Event Study Methods

This study examines empirical issues associated with the use of bid-ask spreads in event studies. The simulation results indicate that the distribution of average standardized abnormal spread shows little deviation from normality. Simulation results also indicate that the widely used percent spread metric results in test statistics with low power. In contrast, use of a standardized raw spread metric and a simple mean-adjusted expectation model results in well specified and reasonably powerful Patell and Brown-Warner type test statistics. As the abnormal spread series is characterized by high first order serial correlation, it is important to adjust for this serial correlation when using multi-day event windows.     

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochasticdifferential equations are consistent and asymptotically efficient,but unfortunately difficult to obtain if a closed-form expressionfor the transitional probability density function of the processis not available. As a result, a large number of competing estimationprocedures have been proposed. This article provides a criticalevaluation of the various estimation techniques. Special attentionis given to the ease of implementation and comparative performanceof the procedures when estimating the parameters of the Cox–Ingersoll–Rossand Ornstein–Uhlenbeck equations respectively.