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The purpose of this paper is to test whether investor sentiment is a significant predictor of future Mexican stock market returns. It also estimates the dynamic correlation between investor sentiment and equity returns. Finally, it examines if investor sentiment innovations impact unexpected returns for a variety of portfolios.

This study utilizes predictive regressions to determine if sentiment can predict Mexican equity returns. Multivariate GARCH models are estimated to examine the time-varying correlations between investor sentiment and equity returns.

The results show that Mexican investor sentiment is a significant predictor of Mexican equity returns for up to 24 months ahead. The findings show that high levels of sentiment today are associated with lower equity returns over the near term. Furthermore, multivariate GARCH estimations indicate that the correlation between investor sentiment and equity returns is not static and varies considerably over time. Finally, the findings indicate that sentiment innovations are significantly correlated with unexpected returns, reinforcing the notion that unexplained sentiment fluctuations lead to unexplained changes in stock market returns. Overall, these results suggest that investor sentiment is a significant source of risk for the Mexican stock market.

This study seeks to further our understanding of how behavioral factors influence and predict Mexican equity returns.

Fama–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.

The 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.

Results 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.

The 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.

The 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.

An extended version of the FFM can be helpful to investors to make better decisions when they try to predict performance in the stock market.

To the best of our knowledge there are no more studies in the literature of the Mexican financial market that apply the same methodology.

This paper focuses on the role of sentiment and monetary policy (both domestic and the United States (US)) in explaining the changes in the Mexican tourism firms' stock returns for the period 1998M03–2019M12.

The authors conducted the ordinary least square regression estimations using various models to investigate the impact of sentiment and monetary policy changes on tourism firms' stock returns. Furthermore, to provide a robust check, the authors run all regression models based on the capital asset pricing model by regressing the excess returns of tourism firms' stocks on all independent variables.

Empirical findings reveal that the changes in Mexican consumer sentiment have a stronger positive effect on tourism firms' stock returns than Mexican business sentiment changes. However, the US consumer and business sentiment are irrelevant to tourism firms' stock returns. Moreover, this study’s results indicate that changes in the US interest rates positively influence tourism firms' stock returns. This study’s findings show that as the monetary divergence between Mexico and the US (differential real interest rates) widens, the lower is the tourism firms' stock returns.

This study is the first to extend the prior studies by examining the effects of sentiment and monetary policy (both domestic and US role) on Mexican tourism stock return.

Purpose – This chapter aims to investigate the stock market comovements between Mexico and the world capital market using nonlinear modeling tools.

Methodology/approach – We apply recent nonlinear cointegration and nonlinear error correction models (NECMs) to investigate the comovements between stock prices over the recent period.

Findings – While the previous literature only highlights some evidence of time-varying comovements, our chapter aims to specify the mechanism characterizing the comovement process through the comparison of two nonlinear error correction models (NECMs). It shows a nonlinear relationship between stock prices that are activated per regime.

Originality – Studying the integration hypothesis between stock markets over the recent financial crisis, our findings highlight strong evidence of significant comovements that explain the global collapse of stock markets in 2008–2009.

This chapter simultaneously investigates the most important calendar anomalies in stock returns: day of the week, turn of the month, turn of the year and holiday periods, in four of the most important Latin American stock markets: Argentina, Brazil, Mexico and Chile. Previous evidence available for these countries is very limited. Our results indicate that the three markets show a rather similar pattern regarding return seasonality. A day of the week effect, consisting in negative returns on Mondays, is reported for all the stock markets but the Mexican. The turn of the year effect is observed only in Argentina, and moderate holiday and turn of the month effects are reported in the Brazilian and the Mexican markets, respectively. In addition, significant levels of first-order return autocorrelation are reported for the four stock markets. The contemporary financial crisis has dramatically affected the behaviour of stock prices worldwide, causing, among other effects, a huge increase in price volatility and probably changing the behaviour of participants in financial markets. We have also investigated to what extent our results have been affected by the current abnormal situation.

The purpose of this paper is to examine the factors that affect the likelihood of being public using a comprehensive database of private and public companies in Mexico, from all sectors, during 2006-2014.

The authors estimate a longitudinal probit model to identify the ex ante characteristics of public Mexican firms that differentiate them from those Mexican firms that continue to remain private.

The authors find that larger, younger and less levered Mexican firms are more likely to be public in Mexico. They additionally test the influence of market conditions and location on the probability of being public. They find that location matters but they find no evidence that initial public offerings (IPOs) are driven by favorable Mexican market conditions.

This paper contributes to the Mexican and international literature on IPOs because it uses an original database built from information of private and public Mexican firms. The study contributes to a better understanding of the determinants of the decision of going public in Mexico.

En este artículo se examinan los factores que afectan la probabilidad de que una empresa salga a Bolsa, utilizando una base de datos integral de empresas privadas y públicas en México, de todos los sectores, durante 2006-2014.

Se estima un modelo probit longitudinal para identificar las características ex-ante de las empresas mexicanas listadas en bolsa que las diferencian de aquellas que siguen siendo privadas.

Los autores encuentran que las empresas mexicanas más grandes, jóvenes y menos apalancadas tienen más probabilidades de estar listadas en la bolsa mexicana. Además, prueban si hay influencia de las condiciones del mercado y la ubicación en la probabilidad de listarse. Ellos encuentran que la ubicación de las empresas importa, pero no encuentran evidencia de que las OPIs sean impulsadas por condiciones favorables del mercado mexicano.

Este trabajo de investigación contribuye a la literatura mexicana e internacional sobre OPIs, ya que utiliza una base de datos original construida a partir de información de empresas mexicanas privadas y públicas. El estudio contribuye a una mejor comprensión de los determinantes de la decisión de listar una empresa en bolsa en México.

This paper tests for the existence of a long-run co-movement between the three North American stock markets of Canada, Mexico, and the U.S. and examines whether or not the implementation of the North American Free Trade Agreement (NAFTA) has led to more integrated equity markets. Application of the Johansen and Juselius (1990) cointegration procedure indicates a long-term relationship. A vector error-correction (VEC) model establishes that all three markets are involved in the long-run adjustment toward equilibrium. Overall, the results suggest that the implementation of NAFTA has promoted greater economic integration between the three North American countries.

This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies.

In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets.

All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries.

The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.

Significant structural changes of the Mexican banking industry have resulted in greater concentration: first, the 1982 expropriation and government control; later on, in 1990, the decision to re-privatize it. In addition, when the economy turned around in 1994–1995, the financial health of several banks rapidly deteriorated and ended in one of the most critical financial crisis the country has experienced. Among the bold measures taken to rescue the system, the banking industry was fully open to foreign investment. At the time of this writing, more than 80% of the banking industry in Mexico is controlled by foreign world class banks.

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead to instability of emerging markets. The study covers a sample of five geographical areas of emerging economies, including Mexico, Korea, South Africa, Turkey, and Malaysia. It used the backward multiple‐regression technique to examine the relationship between monthly changes of stock price indices as dependent variable and the associated predicting local as well as international variables, which represent possible causes of increasing price volatility and initiating crises in emerging stock markets. The study covered monthly data for a period of forty‐eight months from January 1997 to December 2000. The study revealed that stock trading volume and currency exchange rate respectively represent the highest positive correlation to the emerging stock price changes; thus represent the most predicting variables of increasing price volatility. International stock price index, deposit interest rate, and bond trading volume were moderate predicting variables for emerging stock price volatility. While changes in inflation rate showed the least positive correlation to stock price volatility, thus represents the least predicting variable.