El componente de selección adversa de la horquilla de precios cotizada: una revisión de los modelos de estimación

Abstract

One of the main interests of market microstructure is the estimation of the bid–ask spread components from financial data, specially the adverse selection component given the implications of its own existence. As a result, several empirical models based on price time–series statistical properties have been developed in order to estimate them. Recent greater financial data availability has allowed the development of models that focus on price discovery and use more statistical complex methodologies like GMM or VAR. This paper analyses this set of models that allows the estimation of the bid–ask spread components from price dynamics, specifically, the estimation of the adverse selection component in time series. Actually, this sort of models are a powerful tool to investigate how information is incorporated into quotes.