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

ABSTRACT 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.摘要 本文旨在针对拉美新兴市场检验五因子模型（five-factor model）。为验证哪一组因子最适配该数据集，本文同时对三因子与四因子模型进行了估计。资产定价模型多是在发达市场语境下提出的，基于新兴市场数据对这类模型开展的实证检验相对匮乏。本研究立足发达与新兴国家市场间的差异——这类差异会影响模型的预测能力，进而影响投资者的决策流程。本研究亦提供相关实证证据，可助力各类金融市场参与者做出更具依据的决策。此外，本研究结果表明，可尝试在模型中纳入新因子以开展进一步检验。本研究的样本涵盖1999年6月至2017年6月期间在巴西、智利、哥伦比亚、墨西哥及秘鲁证券交易所上市的资产。因子构建基于依据资产特征构建的投资组合间的收益差额，模型估计则采用两步回归法（two-step regression methodology）。第一步与第二步回归的结果均显示，五因子模型具备最优的预测能力。但在第二步估计中，所有模型均未能完全解释投资组合的收益。综上，就本研究样本而言，五因子模型表现最优，尽管仍可纳入其他相关因子以优化模型。本文的核心贡献在于，增进了学界对新兴市场资产定价相关因子的认知。