Mean-ETL Optimization in HorseRace Competition
Published on Jun 11, 2018in Frontiers in Applied Mathematics and Statistics
· DOI :10.3389/fams.2018.00020
In this paper, we present the methodology and results of the portfolios submitted to the HorseRace competition. The nine portfolios were constructed by applying the Mean-ETL optimization approach. The Mean-ETL optimization approach uses three fundamental variables (REG10, CTEF and MQ) and three stock universes (GL, XUS and EM), with each of the three fundamental variables applied one at a time to one of the three universes. This study assesses the return of the nine portfolios, and we report that all of these Mean-ETL portfolios produce positive active returns and most of them are statistically significant. Additionally, MQ variable is found to be the best among these three variables in the Mean-ETL portfolio construction.