The pricing of anomalies using factor models: a test in Latin American markets

This article aimed to test the five-factor model in Latin American emerging markets. In order to verify which set of factors best fits the data, the three- and four-factor models were also estimated. Asset pricing models have been proposed within the context of developed markets, with few empirical tests of these models performed based on emerging markets' data. This study is based on the differences between the markets of developed and emerging countries, which affect the models' predictive power and, thus, the investors' decision-making process. The study also provides evidence that contributes to a more assertive decision-making by all financial market players. In addition, the study results suggest an opportunity to carry out tests with the inclusion of new factors in the models. The study sample included assets listed on stock exchanges in Brazil, Chile, Colombia, Mexico and Peru between June 1999 and June 2017. The building of the factors was based on the return differential between portfolios formed based on the characteristics of the assets, and the models were estimated using the two-step regression methodology. The results for the first- and second-step regressions indicated that the five-factor model had the best predictive power. However, in the second-step estimation, none of the models was able to fully explain the returns on the portfolios. Our conclusion is that the five-factor model showed the best performance for the sample, although there may be other relevant factors that could be incorporated into it. The main contribution of this article lies in the better knowledge it provides of the relevant factors for the asset pricing in emerging markets.