Modelling time-varying asymmetric information component of transaction costs

Abstract

ABSTRACTThe main purpose of this paper is to model time-varying asymmetry information costs. To do this, first, we use two classical reduced-form microstructure models defined in a Bayesian hierarchical framework. In this scenario, we consider adverse selection as a random unobserved state variable and we use the Markov chain Monte Carlo (MCMC) estimator. And second, we evaluate whether time-varying asymmetric information cost estimates reflect the existence of periodicity (intraday patterns, time-of-day effects) and mean reversion in one stock. This procedure is applied to tick-by-tick quote and trade data on 15 SIBE-listed stocks over the 126 trading days since January–June 2005, estimating the unobserved time-varying costs for different hourly intervals. The main results indicate that our model captures periodicity between trading sessions and time-varying adverse selection costs showing the U-shape intraday pattern and mean reversion.