Full - information transaction costs ∗

In a world with private information and learning on the part of the market participants, the (positive) difference between the observed transaction price of an asset and the corresponding unobserved full-information price (the price that reflects private and public information about the asset) represents an ideal measure of market quality. We call this difference “full-information transaction cost.” We propose a simple and robust methodology to evaluate full-information transaction costs. Its simplicity is due to reliance on sample moments of observed high-frequency transaction price data. Its robustness hinges on the fact that the deviations of the observed transaction prices from the unobserved full-information prices can be imputed to fairly unrestricted operating (order-processing and inventory keeping) costs, adverse-selection costs, and learning in the marketplace. We estimate full-information transaction costs for a sample of S&P100 stocks and find that, while closely related to existing measures of transaction costs, they differ in ways predicted by their theoretical construct. We show that our approach captures a large component of market quality that is missing from existing measures. JEL classification: G12, G19.