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

Perez-Liston, Daniel; Huerta, Daniel; Gutierrez, Juan Pablo

doi:10.1177/0972652718777062

Cited by 16 publications

(15 citation statements)

References 49 publications

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“…Based on this study several similar studies have been conducted by other researchers, but there are differences ofopinion with the results obtained. Previous research on investor sentiment and market reaction or stock performance, namelyReference, [16][17][18][19] research shows that investor sentiment affects stock returns or market reactions in the stock market.Reference [10] suggested that the overconfidence of investors significantly affected the return of shares on the Tehran Stock Exchange.…”

Section: Introductionmentioning

confidence: 99%

The Investor Sentiment and Market Reaction Before and During The Covid-19 Pandemic on Indonesia Stock Exchange

Ernawati¹,

Nugraha²,

Waspada³

et al. 2022

Proceedings of the 6th Global Conference on Business, Management, and Entrepreneurship (GCBME 2021)

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This research was conducted to analyze investor sentiment on market reactions over two different periods. The analysis was conducted before and during the covid-19 pandemic on the Indonesia Stock Exchange. Investor sentiment uses trading volume proxies and consumer confidence indexes while market reactions use The Composite Stock Price Index (IHSG) proxy. Data collection with documentation and using a quantitative approach. The results prove that before the covid-19 pandemic investor sentiment did not influence the market reaction. On the contrary, during the covid-19 pandemic investor sentiment influenced the market reaction. Trading volume is a variable that has a positive and significant effect on IHSG, otherwise, the consumer confidence index does not affect IHSG. During the pandemic, the share price was at a low point and consumer confidence dropped to pessimistic. At short-selling, irrational investors will tend to make transactions, when their pessimistic investors buy falling stocks in the hope of higher returns after the pandemic. Investor sentiment causes a difference in stock price sensitivity patterns. Investor sentiment produced by trading volume is a source of positive risk caused by information that existed during the Covid 19 pandemic.

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Section: Introductionmentioning

confidence: 99%

The Investor Sentiment and Market Reaction Before and During The Covid-19 Pandemic on Indonesia Stock Exchange

Ernawati¹,

Nugraha²,

Waspada³

et al. 2022

Proceedings of the 6th Global Conference on Business, Management, and Entrepreneurship (GCBME 2021)

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“…This study finds a relationship between investor sentiment and exchange rate return and shows that investor sentiment has the ability to predict exchange rate returns. Using the VAR model, Perez-Liston et al (2018) come to the same conclusion. The authors find a negative relationship between the peso/US dollar exchange rate and investor sentiment.…”

Section: Related Research Overviewmentioning

confidence: 70%

“…The authors proved the determinant role of investor sentiment in forecasting future returns and volatility by the intense spillover of volatility from investor sentiment to returns. Perez-Liston et al (2018) find a significant relationship between sentiment and stock returns for the Mexican stock market in the period from January 1998 to December 2014. Also, using the VAR model, the authors address the spillover effect from US investor sentiment on Mexican stock market returns; and on Mexican sentiment.…”

Section: Related Research Overviewmentioning

confidence: 88%

Empirical analysis of dynamic spillovers between exchange rate return, return volatility and investor sentiment

Škrinjarić

Golubić

Orlović

2020

SEF

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Purpose This paper aims to analyze the effects of investors’ sentiment, return and risk series on one to another of selected exchange rates. The empirical analysis consists of a time-varying inter-dependence between the observed variables, with the focus on spillovers between the variables. Design/methodology/approach Monthly data on the index Sentix, exchange rates EUR–USD, EUR–CHF and EUR–JPY are analyzed from February 2003 to December 2019. The applied methodology consists of vector autoregression models (VAR) with Diebold and Yilmaz (2009, 2011) spillover indices. Findings The results of the empirical research indicate that using static analysis could result in misleading conclusions, with dynamic analysis indicating that the financial of 2007-2008 and specific negative events increase the spillovers of shock between the observed variables for all three exchange rates. The sources of shocks in the model change over time because of variables changing their positions being net emitters and net receivers of shocks. Research limitations/implications The shortfalls of this study include using the monthly data frequency, as this was available for the authors, namely, investors are interested to obtain new information on a weekly and daily basis, not only monthly. However, at the time of writing this research, we could obtain only monthly data. Practical implications As the obtained results are in line with previous literature and were found to be robust, there exists the potential to use such analysis in the future when forecasting risk and return series for portfolio management purposes. Thus, a basic comparison was made regarding the investment strategies, which were based on the results from the estimation. It was shown that using information about shock spillovers could result in strategies that can obtain better portfolio value over time compared to basic benchmark strategies. Originality/value First, this paper allows for the spillovers of shocks in variables within the VAR models in all directions. Second, a dynamic analysis is included in the study. Third, the mentioned spillover indices are included in the study as well.

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“…Last but not least, Huang et al (2014) employed a combination of the wild-bootstrap technique and the mARM model of Amihud et al (2009) to address both problems. Finally, there are also a number of studies which did not focus on persistent regressors, small-sample bias, or the problem of overlapping periods at all -see, for example, Perez-liston et al (2018) and Concetto and Ravazzolo (2019) as the most recent examples. 22 Given the bootstrap simulation design (see Appendix B), it is not possible to make a proper inference about the return predictability of variables other than sentiment.…”

Section: Results Of the H-period Average Return Regressionsmentioning

confidence: 99%

“…To underline the degree of improvement achieved by combining several survey-based measures into one composite sentiment indicator, I decided to compare the out-of-sample capacity to predict future returns of the composite index sent with the capacity of the Consumer Confidence Indicator (CCI) calculated for Germany by DG ECFIN. The CCI was selected as the benchmark for the evaluation of forecasting performance because it is a popular proxy measure in academic circles and there are several studies that show that consumer confidence is a significant predictor of future stock market returns (Lemmon and Portniaguina, 2006;Schmeling, 2009;Chang et al, 2011;Corredor and Santamaria, 2015;Perez-liston et al, 2018). Prior to the analysis, the CCI measure was transformed to have a zero mean and unit variance.…”

Section: Comparison Of the Composite Survey-based Sentiment Indicatormentioning

confidence: 99%

Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices

Rakovská

2021

International Review of Economics & Finance

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The Working Paper Series of the Czech National Bank (CNB) is intended to disseminate the results of the CNB's research projects as well as the other research activities of both the staff of the CNB and collaborating outside contributors, including invited speakers. The Series aims to present original research contributions relevant to central banks. It is refereed internationally. The referee process is managed by the CNB Economic Research Division. The working papers are circulated to stimulate discussion. The views expressed are those of the authors and do not necessarily reflect the official views of the CNB.

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

Cited by 16 publications

References 49 publications

The Investor Sentiment and Market Reaction Before and During The Covid-19 Pandemic on Indonesia Stock Exchange

The Investor Sentiment and Market Reaction Before and During The Covid-19 Pandemic on Indonesia Stock Exchange

Empirical analysis of dynamic spillovers between exchange rate return, return volatility and investor sentiment

Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices

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