Abstract

PurposeFama–French model (FFM) has been successful in helping to predict the financial markets, but investors have been interested in creating more sophisticated models to better predict the performance of the stock market. The objective of the extended version is to create a more robust econometric model to better predict the performance of the Mexican Stock Market.Design/methodology/approachThe study divides the Mexican Stock Market into six different portfolios. The criteria to build those portfolios are the same one used in Fama–French (1992). The study comprises 78 stocks listed in the Mexican Stock Market that are analyzed monthly during 1997–2018. The study analyzes the period before and after the 2008–2009 financial crisis to identify whether there are important changes. The estimation applies the traditional and an extended version of the FFM that include macroeconomic variables such as country risk, economic activity, inflation rate, and exchange rate and some financial variables recommended in the literature.FindingsResults indicate that classic FFM variables are statistically significant in most cases, but relevant macroeconomic variables such as the interest rate, exchange rate and country risk stand out for being weakly relevant in most of the portfolios. However, it is noticed that some of these macroeconomic variables became relevant for different portfolios only after the 2008–2009 crisis, especially in portfolios which include small market capitalization firms.Research limitations/implicationsThe study includes the stocks listed in the Mexican Stock Market. One limitation is the small number of stocks available, which reduces the possibility of creating well diversified portfolios. This study includes 78 stocks. The stocks removed from the sample are from firms that were not listed during six consecutive months or whose market capitalization did not change in the same period. Outlier data were removed from the sample to capture in better way the general performance of the stock market.Practical implicationsThe objective of the extended version is to create a more robust econometric model than the traditional model. It is expected that such estimations can be helpful to investors to make better decisions when they try to predict performance in the stock market.Social implicationsAn extended version of the FFM can be helpful to investors to make better decisions when they try to predict performance in the stock market.Originality/valueTo the best of our knowledge there are no more studies in the literature of the Mexican financial market that apply the same methodology.

Highlights

  • The Fama–French Model (1992) (FFM) is a well-known asset pricing model in finance that uses size, book-to-market equity and other variables such as beta, leverage and earning-price ratios to capture the stock return of different companies

  • Besides the traditional variables included in the FFM, Fama–French extensions comprise the inclusion of variables related to either macroeconomic conditions or firm performance, such as momentum, profitability, dividends, fundamentals, etc

  • This study includes 78 stocks [1], a number obtained after eliminating financial stocks, as well as the least liquid stocks listed in the stock market [2]

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Summary

Introduction

The Fama–French Model (1992) (FFM) is a well-known asset pricing model in finance that uses size, book-to-market equity and other variables such as beta (market size), leverage and earning-price ratios to capture the stock return of different companies. Besides the traditional variables included in the FFM, Fama–French extensions comprise the inclusion of variables related to either macroeconomic conditions or firm performance, such as momentum, profitability, dividends, fundamentals, etc. Studies by Bali et al (2015), Aretz et al (2005), Adcock et al (2019) and Bergbrant and Kelly (2016) are good examples of Fama–French extensions that include macroeconomic conditions, while studies by Roy and Shijin (2018) and Djamaluddin and Roffi (2017) are extensions that include variables related to firm performance

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