Speaker: Mauricio Enrique Elizalde Mejía from Universidad Autónoma de Madrid
Date and Time: 04/06/2020
Abstract: We consider the case in which a trader has anticipative information about the value of a stock assumed to be driven by a Brownian motion. We show the usage of two different ways to model the problem; the first one with forward integration and the second one with Skorohod integration. Both of them are generalizations of Itô’s integration, which we cannot apply in this scope because, in principle, we do not have integrands adapted to the natural filtration of the Brownian motion unless we use suitable restrictions. We offer a simulation of the models in the real stock market when the price updates are daily. We also discuss how to get anticipative information in the scope of high-frequency trading (HFT). In this case, latency is the mean factor, and we can exploit it in macroeconomic announcements.