Econometric approach for forecasting stock indices price

Abstract

This work proposes to build a profitable dynamic trading strategy. In order to do that it is necessary to forecast the future stock indices prices. First we exploit the forecast power of stock indices assuming that they follow a Geometric Brownian motion. Next, we present an alternative forecasting model that involves cross sectional regression between indices. The latter proves to be more profitable on average than the former.