Do Domestic Sentiment and the Spillover of US Investor Sentiment Impact Mexican Stock Market Returns?

Abstract

We examine the relationship between sentiment and Mexican stock market returns. Results suggest a positive dynamic relationship between rational Mexican sentiment and equity market returns. Results also reveal a spillover of US sentiment on the return-generating process of the Mexican stock market that is distinct from domestic sentiment. This effect may be attributed to close economic ties and ease of capital flows between the two countries. Additionally, we find that rational sentiment and market returns are inversely related to the Peso/US dollar exchange rate. Our findings suggest that sentiment is a significant risk factor in the Mexican stock market.

Keywords

Investor sentiment returns VAR Mexico spillover

1. Introduction

Financial theory is built on the assumption that individual investors are rational utility maximisers who are only concerned with the risks and returns of their investments, and that their expectations are solely based on economic fundamentals (Fama, 1970). In particular, any security mispricing is expected to be quickly eliminated by arbitrageurs who will push prices towards equilibrium. This implies that markets are efficient; therefore, a security’s intrinsic value consistently equals its observed market price. However, a growing body of literature has uncovered market irregularities which are inconsistent with the notion of market efficiency (e.g., Baker & Wurgler, 2007; De Bondt & Thaler, 1985; Lee, Jiang, & Indro, 2002; Lee, Shleifer & Thaler, 1991; Leroy & Porter, 1981; Loughran & Ritter, 1995; Shiller, 1981). These studies provide empirical evidence that challenge the assumption of investor rationality, which serves as one of the pillars of traditional finance. Behavioural finance suggests that security mispricing, due to investor sentiment, might be a market-wide phenomenon that can persist over short-, mid- or long-term periods, even in the presence of rational arbitrageurs (De Long, Shleifer, Summers & Waldmann, 1990).

Much of the literature on the effect of sentiment on stock returns focuses on the US market. However, there is a growing body of literature that studies the impact of investor sentiment on foreign stock markets. Sayim and Rahman (2015) argue that conducting research on how investor sentiment influences stock markets across the globe is relevant, given the cultural and societal differences across countries. Empirical findings for one country may not be generalisable to other countries; therefore, behavioural models should be tested for each individual country to determine whether these models are suitable in diverse social and cultural settings. Individuals’ behaviour, unlike rational choice, is society and culture specific, and researchers should independently examine the sentiment-return relationship for markets with particular characteristics (Sayim & Rahman, 2015).

Our study focuses on the Mexican stock market for a number of reasons. First, the size and relevance of the Mexican stock exchange to the global economy serve as a motivating factor to closely examine elements that impact its return-generating process. According to figures from World Bank cross-country data, Mexico’s stock market capitalisation was US$ 525 billion in 2013, which represented about 44.25 per cent of Mexican gross domestic product. The Bolsa Méxicana de Valores (BMV), or Mexican stock exchange, is the second largest stock exchange in Latin America, just below Brazil’s stock market. Second, given their geographical proximity and wealth of trade agreements, we recognise that Mexico and the US are important business partners that have closely linked economies. As a result, it is important to examine the dynamic relationship between Mexican and US investors and how they influence Mexican stock market returns. The Mexican stock market serves as an important and natural alternative for investors who seek to globally diversify their portfolios. Third, according to Hofstede (2001), Mexico is classified as a highly collectivistic society in which individuals may tend to display herd-like behaviour. This particular characteristic is observed to magnify investor overreaction to information, which leads to equity mispricing (Schmeling, 2009). This article fills a gap in the literature by exploring the impact of sentiment on stock market returns for a highly collectivistic country that is strongly influenced by the US market.

The vast majority of empirical research for the Mexican stock market ignores the role of investor sentiment (Curci, Grieb, & Reyes, 2003; Diamandis, 2008; Herrera & Lockwood, 1994; Lopez-Herrera & Ortiz, 2011; Lopez-Herrera, Ortiz, & de Jesus, 2012; Ortiz, Cabello, & de Jesús, 2006; Roden, Lizola-Margolis, & Salgado, 2012). To our knowledge, only Perez-Liston and Huerta (2012) take into account the influence of Mexican sentiment on Mexican stock market returns. As a result, this study attempts to fill this void and seeks to further our understanding of how sentiment influences the Mexican stock market. This study contributes to the literature in the following distinct ways. First, in a dynamic setting, we examine the role of rational and irrational Mexican sentiment on Mexican stock market returns. Empirical evidence suggests that sentiment and Mexican stock returns might behave as a dynamic system; therefore, our empirical approach avoids imposing a causal relationship between sentiment and returns (Brown & Cliff, 2004; Verma, Baklaci, & Soydemir, 2008). Second, we address a possible spillover effect of foreign investor sentiment on the Mexican stock market, thus, allowing for the influence of US investor sentiment on Mexican stock market returns. Third, we study how the Mexican peso/US dollar exchange rate and both rational and irrational sentiment might influence each other.¹ Fourth, we follow Schmeling (2009) and examine the correlation between unexpected Mexican stock market returns and sentiment innovations. This allows us to empirically test how waves of sudden optimism (pessimism) may lead to higher (lower) unexpected Mexican returns. Last, more awareness is drawn to Latin America’s second largest stock market, a market that plays an important role in the economic stability of the Western hemisphere.

Overall, our results show a dynamic relationship between Mexican sentiment and stock market returns. That is, we observe a dynamic feedback relationship between investor sentiment and stock market returns, which is mostly driven by rational sentiment. Furthermore, the peso/US dollar exchange rate has a significant impact on investor sentiment and stock market returns, indicating that the exchange rate should be taken into account when studying sentiment and returns. These findings are consistent with Ortiz et al. (2006) and Trevino (2011) who document exchange rates as a significant factor in modelling Mexican stock returns. Moreover, we find that US sentiment spills over to Mexico, thus influencing both Mexican sentiment and stock market returns. Specifically, results suggest a contagion of US institutional and individual investor sentiment that is positively related to Mexican stock market returns and to Mexican sentiment. Finally, we observe that sentiment innovations and unexpected returns have a positive and significant correlation. This correlation suggests a capacity to forecast Mexican stock market returns using sentiment as a signal as suggested by Schmeling (2009).

Implications derived from this study concern Mexican domestic investors and foreign investors who wish to diversify their portfolios using Mexican stocks. Investors should incorporate sentiment as a systemic risk factor when evaluating Mexican stock returns. Investors may use fluctuations in Mexican and US investor sentiment as a signal to allocate capital when investing in the BMV.

The remainder of this article is organised as follows: Section 2 presents a review of the relevant literature. Section 3 explains the methodology. Section 4 describes the data. Section 5 summarizes the empirical results and Section 6 concludes.

2. Literature Review

Over the last three decades, behavioural finance has gained momentum with both the academic and practitioner communities. It has become a plausible alternative to the efficient capital market theory, which is based on rational agents that maximise their utility with respect to expected returns and risk. Behavioural finance models propose that irrational sentiment’s influence on security prices may persist over prolonged periods of time, even in the presence of arbitrageurs. These behavioural models give impetus to use of behavioural risk factors—such as investor sentiment—when estimating asset pricing models. De Long et al. (1990) propose a theoretical framework in which irrational traders (investors who trade on pseudo-signals rather than fundamentals) may significantly push prices away from equilibrium for sustained periods of time. These price deviations are sufficiently persistent to consider sentiment as a risk factor in the formation of security prices. Price deviations from intrinsic values are believed to be determined by optimistic and pessimistic sentiments in the market. Lee et al. (2002) suggest that irrational traders will overreact to news and their trading behaviour will create waves of optimism (pessimism) that will generate overpricing (underpricing). That is, noise traders’ correlated trades are significant enough that arbitrageurs will not be able to correct prices in the short term as the efficient market hypothesis proposes. This systematic trading pattern among uninformed investors is documented by Barber, Odean and Zhu (2009), suggesting a significant relationship between irrational sentiment and pricing errors.

Extant empirical studies widely support the view of behavioural finance and the relationship between returns and sentiment. The vast majority of the evidence documents investor sentiment as a significant factor that shapes US market returns (Baker & Wurgler, 2006, 2007; Baker, Wurgler, & Yuan, 2012; Brown & Cliff, 2004; Ho & Hung, 2009; Lee et al., 1991, 2002; Saade, 2015). However, the influence of sentiment and other behavioural biases in foreign markets is understudied. Most of the research focuses on foreign developed markets, and only a handful of studies look at emerging markets (e.g., Canbaş & Kandir, 2009; Chan & Fong, 2004; Kling & Gao, 2008; Lux, 2011; Sayim & Rahman, 2015; Schmeling, 2009; Siriopoulos & Fassas, 2012; Zouaoui, Nouyrigat, & Beer, 2011). It is important to examine the role of investor sentiment independently for each country, given the distinct cultural, social and economic characteristics observed around the world (Sayim & Rahman, 2015). Investor behaviour and risk attitudes may differ across countries, even if they have similar market conditions (Apartsin, Maymon, Cohen, & Singer, 2013). This emphasises the importance of furthering international behavioural finance research for each country independently.

Studies suggest that investor sentiment for some emerging markets may be more pronounced than in developed markets (Chui, Titman, & Wei, 2010; Schmeling, 2009). This prevalence of sentiment may be attributed to the degree of collectivism for the country in question. Individualism may be defined as a behavioural characteristic that leads people to focus on their abilities and internal attributes to make decisions. On the other hand, collectivism is the degree to which people tend to follow the behaviour of others surrounding them (Chui et al., 2010). Hofstede (2001) classifies Mexico as a high collectivistic country. This could indicate that stock market participants may exhibit herd-like behaviour and thus magnify the effect of sentiment on equities. Schmeling (2009) argues that this inverse relationship of sentiment and subsequent returns is stronger for countries that are culturally prone to herd-like behaviour and overreaction.

Mexico’s geographic proximity and close economic ties with the US serve as reasons to hypothesise a spillover of US investor sentiment to both Mexican domestic sentiment and stock market returns. Contagion of market sentiment among closely related economies is well documented in the literature (Baker et al., 2012; Lee, Tucker, Wang, & Pao, 2014; Sayim & Rahman, 2015). For instance, Sayim and Rahman (2015) find that US institutional investor sentiment spills over to the Istanbul stock exchange. The contagion is so strong that sentiment can be considered a systemic risk factor for the Turkish market, even though the two markets reside in two completely different geographic locations (not even in the same continent). Similarly, Verma and Soydemir (2006) study the impact of US institutional and individual sentiments on various stock markets—UK, Brazil, Mexico and Chile. They find various degrees of contagion. Their findings suggest that the UK and Latin American markets respond to US investor sentiments according to the degree of each country’s respective trade ties with the USA. Furthermore, Heath and Kopchak (2015) document a significant relationship between Mexico’s equity markets and US monetary policy; they find that Mexican stock returns suffer more from US monetary surprises during cyclical downturns than during expansions. Findings from Heath and Kopchak (2015) provide further evidence on the close relationship between the Mexican and US economies and financial markets.

Previous research explored the impact of Mexican domestic sentiment on Mexican stock market returns and volatility. Perez-Liston and Huerta (2012) find a positive relationship between sentiment and returns and a negative relationship between sentiment and volatility. However, Perez-Liston and Huerta (2012) do not study the possible spillover effect of US investor sentiment to Mexican stock market returns. Furthermore, their model does not account for the possible dynamic feedback among the variables in question. In this study, we build on Verma and Soydemir (2006) and Perez-Liston and Huerta (2012) and control for a possible dynamic relationship among US investor sentiment, domestic Mexican sentiment, exchange rates and Mexican stock market returns using a vector autoregressive framework. Additionally, we test the degree to which innovations in sentiment may affect unexpected returns in the Mexican stock market portfolio following the method proposed by Schmeling (2009), who finds that sentiment negatively forecasts aggregate stock market returns and explains that this relationship is stronger for countries that are culturally prone to herd-like behaviour and overreaction.

3. Methodology

We begin by decomposing Mexican sentiment into two components—rational and irrational sentiments. Following the methods of Baker and Wurgler (2006) and Verma and Soydemir (2006), we regress Mexican sentiment on a vector of Mexican macroeconomic fundamentals. The model takes the following form:

Δ M e x S E N T_{t} = γ_{0} + {\sum^{​}}_{J}^{j = 1} γ_{j} F u n d_{j t} + ε_{t},

(1)

where ∆MexSENT_t is Mexican sentiment at time t, Fund_jt is a set of macro- economic variables which are expected to influence the stock market, and Ɛ_t is the residual term. γ₀ and γ_j are parameters to be estimated.

Rational sentiment (MexRAT_t) is captured by the fitted values from equation (1). The residual term (Ɛ_t) in equation (1) serves as our measure of irrational sentiment (MexIRR_t). These residuals cannot be explained by the set of macroeconomic fundamentals, and as a result, they may be considered noise.

Next, we estimate Sims’ (1980) vector autoregressive model to examine the dynamic linkages between Mexican stock returns, peso/US dollar exchange rate, US investor sentiment and both irrational and rational Mexican sentiment. This model allows for unconstrained causal relationships among the variables at hand. We estimate the following unrestricted VAR model:

y_{t} = A_{0} + A_{1} y_{t - 1} + \dots + A ​_{p} y_{t - p} + e_{t},

(2)

where y_t is a k vector of endogenous variables, A₁–A_p are matrices of coefficients to be estimated, A₀ is a vector of constants and e_t is a vector of innovations. The lag length in the VAR is determined using the Akaike information criterion (AIC).

Interpretation of VAR coefficients makes it difficult to determine the full impact of an independent variable on the dependent variable (Statman, Thorley, & Vorkink, 2006). Thus, after estimating the VAR, we plot the generalised impulse response functions (IRFs) which are used to interpret the results. The benefit of using generalised IRFs is that the ordering of the variables in the VAR does not influence the impulse responses, and that it allows for the examination of the effect of a shock over several periods. This permits us to observe not only the contemporaneous effect but also the intertemporal effect of shocks to the system (Pesaran & Shin, 1998).

3.1 Controlling for US Investor Sentiment Contagion

Baker et al. (2012) posit that sentiment spillover is closely linked to significant capital flows between the US and foreign countries. The proximity, close economic relationship and ease of capital flows between the USA and Mexico motivate us to control the contagion effect that US individual and institutional investor sentiment may have on Mexican market sentiment. Specifically, we seek to examine whether market- specific Mexican sentiment, that is, sentiment that is unaffected by US sentiment spillover, stands as a risk factor in the Mexican stock market return-generating process. To serve this purpose, we regress Mexican sentiment on both US institutional and individual investor sentiment using the following equation:

Δ M e x S E N T_{t} = α_{0} + ϕ_{1} Δ U S I n s t_{t} + ϕ_{2} Δ U S I n d v_{t} + ξ_{t},

(3)

where ∆MexSENT_t is Mexican sentiment at time t and ∆USInst_t and ∆USIndv_t are US institutional and individual sentiment at time t, respectively. ξ_t is the residual term that will serve as our orthogonalised measure of Mexican-specific sentiment.

We subsequently employ a VAR model and plot IRFs to examine the dynamic relationship among US individual, US institutional and Mexican market-specific sentiment and Mexican stock market returns.

3.2 Sentiment Innovations and Unexpected Returns

Following Schmeling (2009), we test for the effect of sentiment innovations on unexpected returns. We estimate regressions of the following form:

R m k t_{t + 1} = δ_{0} + δ_{1} Δ M e x S E N T_{t} + Y_{t} γ_{1}^{'} + ξ_{t + 1},

(4)

Δ M e x S E N T_{t + 1} = α_{0} + α_{1} Δ M e x S E N T_{t} + Y_{t} γ_{1}^{'} + η_{t + 1}

(5)

where Rmkt_t are the Mexican stock market portfolio returns at time t and ∆MexSENT_t is Mexican sentiment at time t. Y_t is a vector of Mexican macroeconomic fundamental variables, while ξ_t₊₁ and η_t₊₁ are the stochastic error terms that will serve as measures of unexpected returns and sentiment innovations, respectively. After estimating both equations, we calculate the correlation coefficient between unexpected returns (ξ_t₊₁) and sentiment innovations (η_t₊₁). A significant and positive correlation coefficient implies that prices are driven away from fundamentals due to investor sentiment (Schmeling, 2009).

4. Data and Descriptive Statistics

The sample spans from January 1998 to December 2014, for a total of 204 monthly observations.² We employ data from Thomson Reuters’ Datastream. Our measures for macroeconomic fundamentals in the Mexican market are as follows: the monthly percent change in the industrial production index (IPI_t), which proxies for economic growth; the Certificados de la Tesorería de la Federación (CETES)³ for 28 days (1Rf_t),⁴ which serves as the 1-month risk-free rate; the CETES for 91 days (3Rf_t), which serves as the 3-month risk-free rate; the exchange rate measured in pesos per US Dollar (EXCH_t) and the monthly percent change in the consumer price index, which measures inflation (INFL_t). Furthermore, we construct a proxy for the short-term economic risk premium by calculating the difference between the 91- and 28-day CETES government interest rates (HB3_t). The Mexican stock market returns are the monthly percent changes on the Morgan Stanley Capital International Mexico index (Rmkt_t).

Mexican sentiment (MexSENT_t) is proxied by the Mexican manufacturing business confidence index published by El Banco de México (Mexico’s Central Bank). An increase in the confidence index indicates that survey participants expect business conditions to improve. The manufacturing business confidence index is used as a common proxy for sentiment in international studies (Asem et al., 2016; Grisse, 2009; Perez-Liston & Huerta, 2012). We calculate the change in Mexican sentiment as the first difference in the confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). Previous research suggests that returns are affected by changes in sentiment rather than by the level of sentiment (De Long et al., 1990; Lee et al., 2002).

The US institutional (USInst_t) and individual investor (USInd_t) sentiments are proxied by survey results from Investors’ Intelligence and the American Association of Individual Investors, respectively (Brown & Cliff, 2004; Lee et al., 2002; Sayim & Rahman, 2015; Verma & Soydemir, 2006). We calculate bull-bear spreads for each measure of US sentiment. This consists of subtracting the percentage of bullish survey participants from the percentage of bearish survey participants. Then, we estimate changes in sentiment (ΔUSInst_t and ΔUSInd_t) by taking the first differences of each variable. One observation is lost when estimating the returns and the first differences. As a result, the sample consists of 203 usable observations.

Table 1 reports the descriptive statistics for the variables in this study. The mean change in Mexican sentiment is close to zero, which indicates that, on average, bullish and bearish shifts in sentiment are about equal during this time period. The first-order autocorrelation for sentiment (0.106) suggests that sentiment might have some persistence for 1 month but reverts after the second. The mean market return is about 0.010 or 1.00 per cent per month (12% annualised), while the standard deviation is about 0.065 or 6.5 per cent per month (6.5 $\sqrt{12}$ = 22.51% annualised). The means for US individual and institutional investor sentiments are also near zero. Serial correlations for US institutional investor sentiment suggest a strong persistence with ρ1–ρ4 all showing negative signs consistently. In the case of US individual sentiment, changes in sentiment appear to be more erratic, given a higher standard deviation (in comparison with US institutional investor sentiment) and inconsistent signs in the serial correlation coefficients.

Table 1.
Descriptive Statistics

Mean Std. Dev. Max. Min. ρ1 ρ2 ρ3 ρ4

ΔMexSENT_t 0.000 0.032 0.089 −0.142 0.106 −0.005 0.083 0.109

Rmkt_t 0.010 0.065 0.154 −0.275 −0.010 −0.046 0.092 0.083

IPI_t 0.001 0.008 0.028 −0.027 −0.172 0.043 0.010 0.242

1Rf_t 0.008 0.006 0.031 0.002 0.984 0.962 0.932 0.899

3Rf_t 0.007 0.005 0.031 0.002 0.977 0.945 0.907 0.868

HB3_t 0.000 0.000 0.002 0.000 0.732 0.635 0.539 0.505

INFL_t 0.005 0.003 0.016 0.002 0.995 0.986 0.975 0.963

EXCH_t 0.003 0.025 0.180 −0.085 0.280 −0.015 −0.018 0.031

ΔUSInst_t −0.000 0.092 0.220 −0.272 −0.255 −0.005 −0.153 −0.054

ΔUSInd_t 0.001 0.201 0.579 −0.502 −0.443 0.063 −0.069 −0.033

	Mean	Std. Dev.	Max.	Min.	ρ1	ρ2	ρ3	ρ4
ΔMexSENT_t	0.000	0.032	0.089	−0.142	0.106	−0.005	0.083	0.109
Rmkt_t	0.010	0.065	0.154	−0.275	−0.010	−0.046	0.092	0.083
IPI_t	0.001	0.008	0.028	−0.027	−0.172	0.043	0.010	0.242
1Rf_t	0.008	0.006	0.031	0.002	0.984	0.962	0.932	0.899
3Rf_t	0.007	0.005	0.031	0.002	0.977	0.945	0.907	0.868
HB3_t	0.000	0.000	0.002	0.000	0.732	0.635	0.539	0.505
INFL_t	0.005	0.003	0.016	0.002	0.995	0.986	0.975	0.963
EXCH_t	0.003	0.025	0.180	−0.085	0.280	−0.015	−0.018	0.031
ΔUSInst_t	−0.000	0.092	0.220	−0.272	−0.255	−0.005	−0.153	−0.054
ΔUSInd_t	0.001	0.201	0.579	−0.502	−0.443	0.063	−0.069	−0.033

Source: Authors’ own elaboration.

Notes: This table reports the descriptive statistics for the variables employed in this study. Mexican stock market returns are the percent change on the Morgan Stanley Capital International Mexico index (Rmkt_t). The percent change in the industrial production index (IPI_t) proxies for economic growth, the CETES 28 days (1Rf_t) serves as the 1-month risk-free rate, the CETES 91 days (3Rf_t) serves as the 3-month risk-free rate, the exchange rate is measured in pesos per US Dollar (EXCH_t) and the percent change in the consumer price index measures inflation (INFL_t). We construct a proxy for the short-term economic risk premium by calculating the difference in the 91- and 28-day CETES government interest rates (HB3_t). Mexican sentiment is the first difference in the Mexican manufacturing business confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). Changes in US institutional (ΔUSInst_t) and individual investor (ΔUSInd_t) sentiments are computed from survey results from Investors’ Intelligence and the American Association of Individual Investors, respectively. This study is conducted using monthly data obtained from DataStream. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. One observation is lost when estimating the returns and the first differences; as a result, the sample consists of 203 usable observations.

Table 2 reports the correlation coefficients for the variables in the study. The correlation coefficient (0.30) between stock returns and Mexican sentiment is positive and significant at the 1 per cent level. The coefficient (−0.13) between Mexican sentiment and the economic risks variable (HB3_t) is negative and significant at the 10 per cent level. Furthermore, the correlation coefficient for Mexican sentiment and exchange rates (−0.44) is negative and significant at the 1 per cent level. This could indicate that as the peso gains value (relative to the dollar), Mexican investors become more optimistic. Various studies highlight the importance of the exchange rate in Mexico’s economy and its correlation with stock market returns (Ortiz et al., 2006; Tovar-Silos, 2012; Trevino, 2011). Notice that the exchange rate is also significantly correlated with Mexican stock market returns (−0.40), suggesting that there is an important relation between the Mexican peso and the Mexican stock market. It is interesting to observe that changes in both US institutional and individual investor sentiments are positively and significantly correlated with Mexican stock market returns; the correlation coefficients are 0.29 and 0.23, respectively. This serves as an early indication of a spillover effect of US investor sentiment on the Mexican stock market. Furthermore, changes in US institutional investor sentiment are positively and significantly correlated (0.16) with changes in Mexican sentiment. However, the correlation (0.11) between US individual investor sentiment and Mexican sentiment is positive but statistically insignificant.

Table 2.

Correlation Matrix

	ΔMexSENT_t	Rmkt_t	IPI_t	1Rf_t	HB3_t	INFL_t	EXCH_t	ΔUSInst_t	ΔUSInd_t
ΔMexSENT_t	1.00
	–
Rmkt_t	0.30***	1.00
	(4.50)	–
IPI_t	0.09	0.09	1.00
	(1.22)	(1.21)	–
1Rf_t	−0.04	−0.02	0.00	1.00
	−(0.50)	−(0.27)	−(0.01)	–
HB3_t	−0.13*	−0.10	0.05	0.69***	1.00
	−(1.87)	−(1.41)	(0.66)	(13.60)	–
INFL_t	−0.01	−0.04	0.01	0.92***	0.70***	1.00
	−(0.11)	−(0.52)	(0.11)	(33.98)	(13.93)	–
EXCH_t	−0.44***	−0.40***	0.00	0.01	0.07	0.04	1.00
	−(6.99)	−(6.13)	(0.00)	(0.16)	(0.98)	(0.50)	–
ΔUSInst_t	0.166**	0.29***	−0.07	0.02	0.03	0.01	−0.19***	1.00
	(2.39)	(4.41)	(−1.07)	(0.41)	(0.43)	(0.20)	(−2.88)	–
ΔUSInd_t	0.11	0.23***	−0.05	0.00	0.09	0.01	−0.20***	0.32***	1.00
	(1.51)	(3.40)	(−0.80)	(014)	(1.28)	(0.17)	(−2.94)	(4.94)	–

Source: Authors’ own elaboration.

Notes: This table reports the correlation matrix for the variables employed in this article. Mexican stock market returns are the percent change on the Morgan Stanley Capital International Mexico index (Rmkt_t). The percent change in the industrial production index (IPI_t) proxies for economic growth; the CETES 28 days (1Rf_t) serves as the 1-month risk-free rate; the CETES 91 days (3Rf_t) serves as the 3-month risk-free rate, the exchange rate is measured in pesos per US Dollar (EXCH_t) and the percent change in the consumer price index measures inflation (INFL_t). We construct a proxy for the short-term economic risk premium by calculating the difference in the 91- and 28-day CETES government interest rates (HB3_t). Mexican sentiment is the first difference in the Mexican manufacturing business confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). Changes in US institutional (ΔUSInst_t) and individual investor (ΔUSInd_t) sentiments are computed from survey results from Investors’ Intelligence and the American Association of Individual Investors, respectively. This study is conducted using monthly data obtained from DataStream. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. One observation is lost when estimating the returns and the first differences; as a result, the sample consists of 203 usable observations. T-statistics are reported in parentheses. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

5. Estimation Results

We begin by checking the data for non-stationarity. Table 3 shows the results of Augmented Dickey–Fuller (1979; ADF) tests. The results indicate that the variables do not contain unit roots (with the exception of the risk-free rate).⁵

Table 3.
Augmented Dickey–Fuller Unit Root Tests

ADF Test Results

ΔMexSENT_t −12.62***

Rmkt_t −14.33***

IPI_t −17.04***

1Rf_t −1.76

HB3_t −5.85***

INFL_t −5.38***

EXCH_t −10.47***

ΔUSInst_t −18.36***

ΔUSInd_t −9.70*

Test’s critical values

1% level (*) −3.46

5% level (**) −2.88

10% level (*) −2.57

	ADF Test Results
ΔMexSENT_t	−12.62***
Rmkt_t	−14.33***
IPI_t	−17.04***
1Rf_t	−1.76
HB3_t	−5.85***
INFL_t	−5.38***
EXCH_t	−10.47***
ΔUSInst_t	−18.36***
ΔUSInd_t	−9.70***
Test’s critical values
1% level (***)	−3.46
5% level (**)	−2.88
10% level (*)	−2.57

Source: Authors’ own elaboration.

Notes: This table reports the Augmented Dickey–Fuller unit root tests for the variables employed in the study. Mexican stock market returns are the percent change on the Morgan Stanley Capital International Mexico index (Rmkt_t). The percent change in the industrial production index (IPI_t) proxies for economic growth; the CETES 28 days (1Rf_t) serves as the one-month risk-free rate; the CETES 91 days (3Rf_t) serves as the three-month risk-free rate; the exchange rate is measured in pesos per US Dollar (EXCH_t) and the percent change in the consumer price index measures inflation (INFL_t). We construct a proxy for the short-term economic risk premium by calculating the difference in the 91- and 28-day CETES government interest rates (HB3_t). Mexican sentiment is the first difference in the Mexican manufacturing business confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). Changes in US institutional (ΔUSInst_t) and individual investor (ΔUSInd_t) sentiment are computed from survey results from Investors’ Intelligence and the American Association of Individual Investors, respectively. This study is conducted using monthly data obtained from DataStream. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. One observation is lost when estimating the returns and the first differences; as a result, the sample consists of 203 usable observations. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Table 4 presents the results of regressing Mexican sentiment on a set of macroeconomic fundamentals. The coefficients for Mexican stock market returns (Rmkt_t), short-term interest risk premium (HB3_t), inflation (INFL_t) and exchange rates (EXCH_t) are statistically significant. However, the coefficients on the risk-free rate (Rf_t) and the industrial production index (IPI_t) are not statistically different from zero. More importantly, the constant in the equation is statistically insignificant and close to zero (−0.00), suggesting that the variables in the regression adequately capture the variation in sentiment. From this regression, we split Mexican sentiment into two components—Mexican rational sentiment (MexRAT_t), which is captured by the fitted values from the regression, and Mexican irrational sentiment (MexIRR_t), which is proxied by the estimated residuals.

Table 4.

Rational and Irrational Mexican Sentiment

	Coefficient	Std. Error	t-statistic	p-value
Rmkt_t	0.0644**	0.0325	1.98	0.0488
Rf_t	−1.1161	0.8955	−1.25	0.2141
HB3_t	−14.7775**	6.3584	−2.32	0.0211
INFL_t	3.0539**	1.4288	2.14	0.0338
EXCH_t	−0.4905***	0.1210	−4.05	0.0001
IPI_t	0.3054	0.2923	1.05	0.2973
Constant	−0.0026	0.0036	−0.73	0.4651

R-squared	0.2457
S.E. of regression	0.0281
Sum-squared resid.	0.1552
Log likelihood	440.3453
F-statistic	10.6412
Durbin-Watson stat.	2.1434

Source: Authors’ own elaboration.

Notes: We regress Mexican sentiment on a set of macroeconomic variables to estimate rational and irrational Mexican sentiment. We estimate the following equation:

Δ M e x S E N T_{t} = γ_{0} + {\sum^{​}}_{J}^{j = 1} γ_{j} F u n d_{j t} + ε_{t}

The variables are as follows: Mexican stock market returns are the percent change on the Morgan Stanley Capital International Mexico index (Rmkt_t). The percent change in the industrial production index (IPI_t) proxies for economic growth; the CETES 28 days (1Rf_t) serves as the one-month risk-free rate; the exchange rate is measured in pesos per US Dollar (EXCH_t) and the percent change in the consumer price index measures inflation (INFL_t). We construct a proxy for the short-term economic risk premium by calculating the difference in the 91- and 28-day CETES government interest rates (HB3_t). Mexican sentiment is the first difference in the Mexican manufacturing business confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). This study is conducted using monthly data obtained from Datastream. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. One observation is lost when estimating the returns and the first-differences; as a result, the sample consists of 203 usable observations. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Table 5 shows the results of the base VAR model in which we estimate the dynamic relationship between Mexican market portfolio returns and rational and irrational Mexican sentiment.⁶ In the third column, results of the Wald Block Exogeneity test (χ² = 22.64) indicate that lagged values of both rational and irrational sentiment have a significant influence on Mexican stock market returns. In the fourth column, the chi-squared value of 3.37 suggests we cannot reject the null hypothesis that lagged values of the market portfolio, and rational sentiment does not influence irrational sentiment. In the last column, the Wald Block Exogeneity test results (χ² = 22.36) suggest that lagged values of the market portfolio and irrational sentiment have a significant influence on rational sentiment. Overall, the results of the base VAR model indicate that all of these variables exhibit a complex dynamic feedback relationship.

Table 5.

VAR: Mexican Stock Market Returns and Sentiment

Independent Variable Lag		Dependent Variable
Independent Variable Lag		Rmkt_t	ΔMexIRR_t	ΔMexRAT_t
Rmkt_t	1	−0.2016	0.0644	−0.0612
		(−2.3959)	(1.7219)	(−3.2124)
ΔMexIRR_t	1	0.4641	−0.0710	0.1248
		(2.9390)	(−1.0106)	(3.4909)
ΔMexRAT_t	1	1.3242	−0.2423	0.5080
		(3.7693)	(−1.5496)	(6.3837)
Constant		0.0119	−0.0014	0.0008
		(2.6970)	(−0.7218)	(0.8246)

Block Exogeneity		22.64	3.37	22.36
Adj. R-squared		0.0891	0.0067	0.1998

Source: Authors’ own elaboration.

Notes: This table reports the coefficients for the VAR estimation results. The variables employed in the model are the change in irrational sentiment (ΔMexIRR_t), the change in rational sentiment (ΔMexRAT_t) and the returns on the Morgan Stanley Capital International Mexico index (Rmkt_t). We report the chi-squared value for the Block Exogeneity χ² (Wald) test. The null hypothesis for this test is that the coefficients on all lags of all independent variables (other than the own lags of the endogenous variable) are jointly zero. The sample consists of 204 monthly observations starting in January 1998 and ending in December 2014. The t-statistics are in parentheses. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Given the difficulty in interpreting individual coefficients in a VAR system, we rely on the IRFs plotted in Figure 1 to interpret VAR estimation results. The IRFs represent the behaviour of a series in response to a shock in an independent variable while keeping the effect of other variables constant (Sayim & Rahman, 2015). In the graphs, the solid line represents the dynamic behaviour of the response variable (the impulse response) to a one-time shock, while the dashed lines represent the Monte Carlo simulation constructed confidence bands.⁷ In order for a shock to be considered statistically significant at the 95 per cent level, the upper and lower confident bands must carry the same sign. Figure 1ashows that a shock (one standard deviation innovation) in irrational sentiment has an insignificant influence on Mexican stock market returns during the first month but then becomes significant in the second month. This result indicates that an increase in irrational sentiment today will lead to an increase in stock returns 2 months into the future. In Figure 1b, the IRF shows that higher stock market returns do not significantly influence irrational sentiment.

Figure 1cshows a significant impact of a shock in Mexican rational sentiment on stock market returns. It takes up to 3 months for the shock to work its way through the system, until it eventually becomes statistically insignificant. Interestingly, Figure 1dshows that rational sentiment responds positively to increases in stock market returns. The results in Figure 1 are qualitatively similar to those found for the US stock market (Verma et al., 2008). Our findings suggest that waves of rational and irrational sentiment influence the data-generating process for equity returns in Mexico. However, rational sentiment that is driven by macroeconomic fundamentals plays a stronger role compared to irrational sentiment in the Mexican market. Overall, the results presented in Figure 1 suggest a significant dynamic feedback among all three variables:—stock market returns, irrational and rational sentiments.

Figure 1.

Source: Authors’ own elaboration.

5.1 Exchange Rates, Investor sentiment and Stock Market Returns

Ortiz et al. (2006) and Trevino (2011) highlight the significant relationship between exchange rate fluctuations and Mexican stock market returns. Therefore, we add the peso/US dollar exchange rate to our empirical specification and test whether exchange rates influence Mexican sentiment and stock market returns. Table 6 shows the results for this augmented VAR model.⁸ Block Exogeneity tests suggest that there is a strong co-dependence among all the variables in the system. Figure 2ashows that a positive shock to the exchange rate (i.e., the peso loses value relative to the dollar) has a significantly negative impact on Mexican stock market returns. The impact lasts up to 3 months. In Figure 2b, we can observe that an increase in stock market returns leads to a decrease in the exchange rate (an appreciation of the peso relative to the dollar).

Table 6.
VAR: Mexican Stock Market Returns, Sentiment and Exchange Rates

Independent Variable Lag Dependent Variable

Rmkt_t ΔMexIRR_t ΔMexRAT_t EXCH_t

Rmkt_t 1 −0.2501 0.0342 −0.0577 0.0694

(−2.4811) (0.7553) (−2.5324) (1.7865)

2 −0.2057 0.0574 −0.0245 0.0046

(−2.0799) (1.2909) (−1.0983) (0.1216)

3 0.3329 0.1102 0.0900 −0.1261

(3.4614) (2.5485) (4.1446) (−3.4040)

ΔMexIRR_t 1 0.4651 −0.1268 0.1051 −0.1228

(2.9272) (−1.7742) (2.9283) (−2.0063)

2 0.1246 −0.0926 −0.0138 0.0841

(0.7640) (−1.2619) (−0.3763) (1.3379)

3 −0.0511 0.0147 0.0213 −0.0607

(−0.3125) (0.1999) (0.5774) (−0.9636)

ΔMexRAT_t 1 1.7098 0.5651 0.5713 −0.3230

(1.6836 ) (1.2371) (2.4893) (−0.8253)

2 1.5415 0.0646 0.5844 −0.4026

(1.5426) (0.1438) (2.5880) (−1.0454)

3 −4.0155 −1.0482 −0.7313 0.9229

(−4.1388) (−2.4016) (−3.3355) (2.4683)

EXCH_t 1 0.2002 0.3749 0.0410 0.2288

(0.3788) (1.5767) (0.3432) (1.1235)

2 0.3491 0.2234 0.3008 −0.2898

(0.6716) (0.9556) (2.5609) (−1.4468)

3 −1.7147 −0.4590 −0.3074 0.3933

(−3.3572) (−1.9980) (−2.6641) (1.9983)

Constant 0.0149 −0.0028 0.0000 0.0024

(3.1085) (−1.3173) (−0.0700) (1.3395)

Block Exogeneity 46.31* 18.79 47.36* 27.35*

Adj. R-squared 0.2067 0.1017 0.3028 0.2045

Independent Variable Lag	Dependent Variable
Rmkt_t	1	−0.2501	0.0342	−0.0577	0.0694
		(−2.4811)	(0.7553)	(−2.5324)	(1.7865)
	2	−0.2057	0.0574	−0.0245	0.0046
		(−2.0799)	(1.2909)	(−1.0983)	(0.1216)
	3	0.3329	0.1102	0.0900	−0.1261
		(3.4614)	(2.5485)	(4.1446)	(−3.4040)
ΔMexIRR_t	1	0.4651	−0.1268	0.1051	−0.1228
		(2.9272)	(−1.7742)	(2.9283)	(−2.0063)
	2	0.1246	−0.0926	−0.0138	0.0841
		(0.7640)	(−1.2619)	(−0.3763)	(1.3379)
	3	−0.0511	0.0147	0.0213	−0.0607
		(−0.3125)	(0.1999)	(0.5774)	(−0.9636)
ΔMexRAT_t	1	1.7098	0.5651	0.5713	−0.3230
		(1.6836 )	(1.2371)	(2.4893)	(−0.8253)
	2	1.5415	0.0646	0.5844	−0.4026
		(1.5426)	(0.1438)	(2.5880)	(−1.0454)
	3	−4.0155	−1.0482	−0.7313	0.9229
		(−4.1388)	(−2.4016)	(−3.3355)	(2.4683)
EXCH_t	1	0.2002	0.3749	0.0410	0.2288
		(0.3788)	(1.5767)	(0.3432)	(1.1235)
	2	0.3491	0.2234	0.3008	−0.2898
		(0.6716)	(0.9556)	(2.5609)	(−1.4468)
	3	−1.7147	−0.4590	−0.3074	0.3933
		(−3.3572)	(−1.9980)	(−2.6641)	(1.9983)
Constant		0.0149	−0.0028	0.0000	0.0024
		(3.1085)	(−1.3173)	(−0.0700)	(1.3395)

Block Exogeneity		46.31***	18.79**	47.36***	27.35***
Adj. R-squared		0.2067	0.1017	0.3028	0.2045

Source: Authors’ own elaboration.

Notes: This table reports the coefficients for the VAR estimation. The variables employed in the model are the change in irrational sentiment (ΔMexIRR_t), the change in rational sentiment (ΔMexRAT_t), the returns on the Morgan Stanley Capital International Mexico index (Rmkt_t) and the monthly percent change in the exchange rate measured in pesos per US dollar (EXCH_t). We report the chi-squared value for the Block Exogeneity χ² (Wald) test. The null hypothesis for this test is that the coefficients on all lags of all independent variables (other than the own lags of the endogenous variable) are jointly zero. The sample consists of 204 monthly observations starting in January 1998 and ending in December 2014. The t-statistics are in parentheses. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Figures 2cand 2d indicate that irrational sentiment does not have a significant relationship with the exchange rate. However, Figures 2eand 2f suggest that there is a significant and reciprocal relationship between exchange rates and Mexican rational sentiment. Figure 2eshows that a currency depreciation leads to lower stock market returns. Figure 2fshows that a positive shock to rational sentiment leads to a currency appreciation that lasts up to 3 months. Overall, the results from this augmented VAR model suggest that rational sentiment, Mexican stock market and the peso/US dollar exchange rate are all interrelated.

Figure 2.

Source: Authors’ own elaboration.

5.2 Spillover of US Investor Sentiment on the Mexican Market

Table 7 presents the results where we regress changes in Mexican sentiment on both US institutional and individual sentiments (i.e., we orthogonalise Mexican sentiment). Results show a significant relationship between US institutional sentiment and Mexican sentiment (p-value = 0.0289). However, no significant relationship between US individual investor sentiment and Mexican sentiment is observed. We employ the error term from this regression as Mexican market-specific sentiment, that is, sentiment that is specific to the Mexican market after controlling for the possible spillover effect of US investor sentiments.

Table 7.
Mexican-Specific Sentiment

Coefficient Std. Error t-statistic p-value

ΔUSInst_t 0.0512** 0.0233 2.20 0.0289

ΔUSInd_t 0.0092 0.0116 0.79 0.4315

Constant −0.0005 0.0025 −0.19 0.8486

R-squared 0.0308

S.E. of regression 0.0316

Sum-squared resid. 0.1994

Log likelihood 414.89

F-statistic 3.1735**

Durbin–Watson stat. 1.7713

	Coefficient	Std. Error	t-statistic	p-value
ΔUSInst_t	0.0512**	0.0233	2.20	0.0289
ΔUSInd_t	0.0092	0.0116	0.79	0.4315
Constant	−0.0005	0.0025	−0.19	0.8486
R-squared	0.0308
S.E. of regression	0.0316
Sum-squared resid.	0.1994
Log likelihood	414.89
F-statistic	3.1735**
Durbin–Watson stat.	1.7713

Source: Authors’ own elaboration.

Notes: We orthogonalise Mexican sentiment by regressing it on both US institutional and individual investor sentiment:

Δ M e x S E N T_{t} = α_{0} + ϕ_{1} Δ U S I n s t_{t} + ϕ_{2} Δ U S I n d v_{t} + ξ_{t}

Mexican sentiment is the first difference in the Mexican manufacturing business confidence index (ΔMexSENT_t = MexSENT_t−MexSENT_t−1). Changes in US institutional (ΔUSInst_t) and individual investor (ΔUSInd_t) sentiments are computed from survey results from Investors’ Intelligence and the American Association of Individual Investors, respectively. This study is conducted using monthly data from DataStream. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. One observation is lost when estimating the returns and the first differences; as a result, the sample consists of 203 usable observations. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Figure 3 shows the IRFs for the VAR model that includes the Mexican equity market portfolio, Mexican orthogonalised sentiment and both US institutional and individual investor sentiments. Consistent with our previously reported results, we observe a positive feedback relationship between Mexican sentiment and stock market returns. Figure 3ashows a positive response for Mexican stock returns to a one-time shock in Mexican-specific sentiment (i.e., orthogonalised sentiment). The response is significant and lasts up to two months. Figure 3bshows a significant response for Mexican-specific sentiment to a shock in stock market returns. Interestingly, Figure 3csuggests that a shock in US institutional investor sentiment has a significant impact on Mexican stock returns that appears to last for 1 month. Figure 3dshows that shocks in US institutional investor sentiment have a positive influence on Mexican-specific sentiment that is lagged 4 months. Moreover, Figure 3eshows that a shock in US individual investor sentiment also significantly impacts Mexican stock market returns. Figure 3fshows the response of Mexican-specific sentiment to a shock in US individual sentiment—the results are insignificant. In general, our results suggest that not only does Mexican-specific sentiment play a significant role in the Mexican equities market, but that there is also a significant spillover of US investor sentiment to the Mexican equities market. These findings are consistent with Verma and Soydemir (2006) which find a similar relationship between Mexican market returns and US sentiment although they do not consider Mexican-specific sentiment.

Figure 3.

Source: Authors’ own elaboration.

5.3 Sentiment Innovations and Unexpected Returns

Table 8 reports the correlation coefficient between sentiment innovations and unexpected returns (both variables were derived using the residuals from estimating equations (4) and (5) from the text). Results show that sentiment innovations and unexpected returns in the Mexican stock market are positively and significantly correlated (0.2868) at the 1 per cent level. These results suggest that irrational noise trader sentiment may push security prices away from fundamental values. Overall, our results support the hypothesis that sentiment is a significant risk factor that must be adequately considered when evaluating Mexican stock returns. Moreover, our findings suggest a capacity to use sentiment as a significant predictor of expected returns.

Table 8.
Correlation between Mexican Sentiment Innovations and Unexpected Returns

Unexpected Returns

Sentiment Innovations 0.2868***

(0.0000)

	Unexpected Returns
Sentiment Innovations	0.2868***
	(0.0000)

Source: Authors’ own elaboration.

Notes: This table reports the correlation between sentiment innovations and unexpected returns. The two variables are derived from the following equations:

R m k t_{t + 1} = δ_{0} + δ_{1} Δ M e x S E N T_{t} + Y_{t} γ_{1}^{'} + ξ_{t + 1}

Δ M e x S E N T_{t + 1} = α_{0} + α_{1} Δ M e x S E N T_{t} + Y_{t} γ_{1}^{'} + η_{t + 1}

where Rmkt_t+1 are the Mexican stock market portfolio returns at t+1 and ΔMexSENT_t and ΔMexSENT_t+1 are Mexican sentiment at time t and t+1, respectively. Y_t is a vector of Mexican macroeconomic fundamental variables and ξ_t₊₁ and η_t₊₁ are the stochastic error terms that will serve as measures of unexpected returns and sentiment innovations, respectively. The sample spans from January 1998 to December 2014, for a total of 204 monthly observations. P-value in parentheses. *, ** and *** denotes significance at the 10%, 5% and 1% levels, respectively.

6. Conclusion

Despite the importance of the Mexican stock market in Latin America, asset pricing literature for Mexican stocks has widely ignored the potential role of sentiment as a risk factor (Curci et al., 2003; Diamandis, 2008; Herrera & Lockwood, 1994; Lopez-Herrera & Ortiz, 2011; Lopez-Herrera et al., 2012; Ortiz et al., 2006; Roden et al., 2012). Behavioral finance models posit that security prices can deviate significantly from fundamentals in the presence of persistent irrational sentiment despite the force of arbitrage (De Long et al., 1990). Moreover, research finds that sentiment is often more pronounced in emerging economies compared to their developed counterparts. Sentiment in emerging markets is often attributed to the degree of collectivism observed in its society (Chui et al., 2010); the higher the degree of collectivism, the higher the likelihood of herd-like behaviour among market participants as in the case of Mexico. This article contributes to the literature by addressing the relationship between Mexican stock returns and sentiment and the spillover effect of US investor sentiment on the returns of the Mexican equity market.

We estimate VAR models that examine the dynamic linkages between sentiment, stock market returns and exchange rates, with unconstrained casual relationships among the variables. Estimations suggest a reciprocal relationship between Mexican sentiment and stock market returns that is primarily driven by rational sentiment. Closer examination suggests that the peso/US dollar exchange rate is a significant factor that plays an important role in the sentiment–return relationship in the Mexican market. Our findings are consistent with prior studies that highlight the significance of the exchange rate on Mexican market returns (Ortiz et al., 2006; Trevino, 2011). Furthermore, we document a significant spillover effect from both US institutional and individual investor sentiments on Mexican stock returns and on the formation of Mexican sentiment. Our findings additionally suggest a potential capacity to forecast Mexican expected returns using sentiment as a signal. A positive and significant correlation between sentiment innovations and unexpected returns hint that waves of sentiment may serve as a predictor for expected returns.

Overall, our results suggest that the traditional view of finance (i.e., models that rely on the premise of rational expectations and only include expected returns and risk in the utility function) cannot fully account for the variation observed in Mexican stock market returns. As a consequence, portfolio managers and investment professionals should take into account the role that waves of optimism (pessimism) play in determining Mexican stock market returns. Our findings have important implications for Mexican and foreign investors who seek to diversify into the Mexican market. Market participants must be aware of the effect of behavioural biases on the return-generating process of the Mexican stock market to make informed investment transactions. More scrutiny on the return forecasting power of sentiment in the Mexican stock market remains as an open avenue for future research.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is partially funded by the College of Charleston’s School of Business 2015 summer research grant.

Footnotes

Acknowledgements

We thank the participants of the 2015 Academy of Behavioural Finance and Economics meeting for their insightful comments.

Notes

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Do Domestic Sentiment and the Spillover of US Investor Sentiment Impact Mexican Stock Market Returns?

Abstract

Keywords

1. Introduction

2. Literature Review

3. Methodology

Table 8. Correlation between Mexican Sentiment Innovations and Unexpected Returns Unexpected Returns Sentiment Innovations 0.2868*** (0.0000)

Declaration of Conflicting Interests

Funding

Footnotes

Acknowledgements

Notes

References

Table 8.
Correlation between Mexican Sentiment Innovations and Unexpected Returns

Unexpected Returns

Sentiment Innovations 0.2868***

(0.0000)