In this paper we apply Random Matrix Theory (RMT) to study daily return correlations of 83 companies that are part of the Chilean stock market during the period 2000 to 2011. We find that using RMT to identify statistically significant correlations within our sample of stocks significantly improves the efficiency of a family of Markowitz Portfolios. Moreover, by using Vector Autoregressive analysis we identify global risk aversion as the main driver of the Chilean equity market returns followed in importance by shocks to the monthly rate of inflation and the country's monetary policy rate. By studying the effects of macroeconomic variables on the constructed portfolio returns we reach a better understanding of the true risks involved in an emerging market portfolio. © 2013 Elsevier B.V.