Investor attention and stock market activity: Evidence from France (original) (raw)
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Investor Attention: Can Google Search Volumes Predict Stock Returns?
Brazilian Business Review
This paper investigates the role of investor attention in predicting future stock market returns for Brazilian stocks using Google Search Volume (GSV). We tested whether lagged variations in GSV are followed by changes in excess returns by testing 57 stocks from the Ibovespa using weekly search data from Google Brazil from 2014 to 2018. Similar to previous research on the U.S. market, we found that increases in GSV are followed by lower excess returns. Additionally, we show that the more traded a stock is, the higher the effect. This is consistent with the hypothesis that higher individual investor attention leads to lower subsequent returns, suggesting that increasing popularity causes stock prices to deviate from their fundamental value.
Stock Prices, Attention, and Google Searches
Proceedings of the International Conference on Economics and Social Sciences
With the increasing availability of data and the expanded use of digital trading platforms, the behaviour of individual investors actively involved in trading has a greater impact on stock returns on capital markets. Traditional models assume that investors are perfectly rational economic agents, but, as prior research has shown, this constraint is not fully honoured in the actual world most of the time. Our paper investigates the dynamics of the relationship of investors' attention and its impact on the stock market for an institutional investor-dominated stock exchange. The research was centred on the FTSE 100 Index of London Stock Exchange (LSE), and we constructed an investor's attention indicator based on the Google Search Index, which measures in real-time the information with whom individuals come into contact daily. We introduced the indicator in the Fama and French 3-factor model. To explore the association between investors' cognitive limitations and stock prices, we used weekly data for five years, from the beginning of 2015 to the end of 2019. We then used multiple and panel regression to categorise quintile portfolios according to market capitalization levels. Despite the minimal presence of private investors on the LSE, our findings show that there is a positive correlation between the volume of Google searches and stock prices. Furthermore, there is a positive effect of attention on the portfolio of companies with the smallest market capitalization. Our findings have implications for investment approaches and, specifically, for active portfolio management strategies.
The influence of Google search index on stock markets: an analysis of causality in-mean and variance
Review of Behavioral Finance, 2020
PurposeThis empirical work studies the influence of investors’ Internet searches on financial markets.Design/methodology/approachIn this study, an asset pricing model with six factors is used, and autoregression, heteroscedasticity and moving average are taken into account to extract the independent shocks of each variable. Subsequently, a causality in-mean and in-variance analysis is performed to test the influence of Google searches on financial market variables, specifically, to test whether there is an influence on the idiosyncratic returns of financial assets.FindingsUnlike most of the literature, the results show that Google searches on the name of listed companies have little influence on the trend and volatility of asset returns. On the contrary, these searches are shown to have a significant influence on trading volumes in the following week.Practical implicationsWhen analyzing specific effects, such as the influence of Internet searches, on financial markets, it is necessa...
This research observes a time varying relationship between stock returns, volatilities and the online search volume in regard to selected CESEE (Central, Eastern and SouthEastern European) stock markets. The main hypothesis of the research assumes that a feedback relationship exists between stock returns, volatilities and the investor's attention variable (captured by the online search volume). Moreover, the relationship is assumed to be time varying due to changing market conditions. Previous research does not deal with the time-varying multi-directional relationship. Thus, the contribution to existing research consists of estimating the aforementioned relationship between return, volatility and the search volume series for selected CESEE countries by using a novel approach of spillover indices within the VAR (Vector AutoRegression) model framework. The results indicate that the Google search volume affects the risk series more than the return series on the selected markets.
Review of Education, Administration & LAW
The aim of this study is to examine whether google search volume index (GSVI) as a tool of investor’s attentions can be of great used to forecast stock returns. In this paper we answer the question whether “price pressure hypothesis “would hold true for Pakistan stock markets. The nature of current study is quantitative in nature and research design is used to test the hypothesis developed to examine google search volume index and stocks return behavior. We used balanced panel data for the period from 2003 to 2019 for companies listed in Pakistan stock exchange. In this paper, we use regression technique for econometrics estimation. The results showed that high and a positive return is associated with high google search volume. To be more accurate, we can say that a google search volume index is an important and useful predictor for both the directions and magnitude of excess returns. We suggest that, this study will be helpful for the information of profitable trading strategies. W...
Investor Attention and Stock Market Activities: New Evidence from Panel Data
International Journal of Financial Studies
Using the panel vector autoregression (VAR) method, this paper documents relationships between investor attention and stock market activities; i.e., return, volatility, and trading volume, respectively. In sum, bidirectional dynamic interdependence of the SVI–stock market activities relationship exists, in which the SVI–trading volume relationship shows the strongest evidence. This is consistent with prior literature using trading volume as a proxy of investor attention. However, the relationships in the developed and developing markets are statistically significantly different. The stock markets in the developed markets over-react more to the search volume than those in the developing markets. We postulate that investor attention is one of the key elements in asset pricing in stock markets.
Web Search Queries Can Predict Stock Market Volumes
We live in a computerized and networked society where many of our actions leave a digital trace and affect other people's actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.
Investors’ attention: does it impact the Nigerian stock market activities?
Journal of Economics and Development
PurposeThe author investigates whether investors’ online information demand measured by Google search query and the changes in the numbers of Wikipedia page view can explain and predict stock return, trading volume and volatility dynamics of companies listed on the Nigerian Stock Exchange.Design/methodology/approachThe multiple regression model which encompasses both the univariate and multivariate regression framework was employed as the research methodology. As part of our pre-analysis, we test for multicollinearity and applied the Wu/Hausman specification test to detect whether endogeneity exist in the regression model.FindingsWe provide novel and robust evidence that Google searches neither explain the contemporaneous nor predict stock return, trading volume and volatility dynamics. Similarly, results also indicate that trading volume and volatility dynamics have no relationship with changes in the numbers of Wikipedia pages view related to stock activities.Originality/valueThis...
Does investor attention affect trading volume in the Brazilian stock market?
Research in International Business and Finance, 2017
Given the large amount of information available about companies and stocks, investors have to be selective about the information they process. This behavior is related to the attention effect, which comes from the natural human incapacity to process all existing information. The aim of this paper is to investigate the relationship between a proxy of attention effect, media coverage, and trading volume in the Brazilian stock market. Media coverage may attract unsophisticated investors. The results suggest that, in periods with high stock index level, there is a strong positive reaction of the trading volume on the same day of the news release in printed newspapers. Moreover, this relation occurs only if the news is negative for the firm. In addition, less visible companies in the media are more susceptible to the attention effect when news is more widespread.
Stock return and volatility reactions to information demand and supply
Research in International Business and Finance, 2017
The objective of this paper is to evaluate the impact of information demand and supply on stock market return and volatility. In this study we employ a proxy for information demand which is derived from weekly internet search volume. The latest is drawn from Google Trends database, for 25 of the largest stocks traded on CAC40 index, between April 2007 and March 2014. We use news headlines as a proxy for information supply. Our empirical findings suggest: First public information has an impact on stock returns but its impact on the volatility is much more important. Second, the influence of specific information demand to the company persists even by adding market information demand and firm/market information supply. Finally, by applying MCA to results found, it could be concluded that the impact of public information on stock return and volatility is conditioned by two elements: The company and market news disclosure, and the second element relates to the characteristics of the market participants, more precisely their news interpretations and their risk aversion.