Investor Sentiment and Attention in Capital Markets - A (Social) Media Perspective

Field: Economics, Econometrics and Finance (Social Sciences)

This dissertation examines the impact of social and traditional media on capital markets. The empirical tests focus on investor sentiment which, for example, can be captured by postings on social media platforms, innovative news databases and the textual analysis of traditional media press. The research direction of this dissertation implicitly questions the assumptions stated by the traditional finance theory. Our new empirical findings and their explanations are, hence, closely linked with the behavioral finance theory. The Efficient Market Hypothesis constitutes one of the fundamental pillars of the traditional finance theory. In this concept, the availability of information is the basic requirement for the functionality of efficient capital markets. New information is quickly and correctly incorporated into an asset’s price. The new price of an asset, therefore, immediately reflects the updated fundamental value (Fama, 1969; 1970). However, various studies have recently shown that stock market movements are not always associated with rational information about an asset’s value. The observation of over- and underreaction of asset prices to news signals or distinctive return patterns gave reason for the gaining importance of the behavioral finance theory since the 1990’s. The changing availability and the easier access to information for institutional and individual investors play an important role in this recent development. For example, Figure 1 1 (p. 3) depicts the circulation of US newspapers between 1970 and 2017. The number of households covered by traditional media press decreased from more than 60 million to around 30 million households in 2017. The establishment of the internet, on the other hand, parallelly accelerated the digital development in the media landscape. Figure 1 3 (p. 5) describes the global development of social media users since 2010. The number of social media users is expected to increase from 1 billion users in 2010 to around 3 billion users in 2021. This development not only affects the society but also a specific focus group of this dissertation: the financial investors. The way investors gather, process, and disseminate information also experienced a significant change in recent decades (Puppis et al., 2017). In this connection, the development of investor attention and sentiment for individual assets is sustainably impacted by the digitalization of media channels. Consequently, we derive four fundamental research questions, which accompany the empirical analyses of this dissertation: 1. What role does investor sentiment play in financial markets? Do investors solely follow the market, or do beliefs of investors predict future returns or other market variables? 2. How does (social) media relate to financial markets in the general daily context and specifically around news events, such as earnings or M&A announcements? 3. What kind of firms are more sensitive to investor sentiment than others? 4. Does arbitrage stabilize financial markets against noise traders? The following structure of this dissertation aims to answer these questions in the best possible way: The first chapter introduces the reader to the relevance of the topic and the leading research questions of the dissertation. The second chapter lays the theoretical foundation and describes the fundamental concepts of the traditional and also the behavioral finance theory, which aims to comprehensively explain selected market anomalies. Also, we summarize selected psychological concepts that help to explain irrational actions of investors, which potentially cause market volatility and asset prices to deviate from their fundamental value. Literature reviews on investor sentiment in close relationship with traditional and social media complete the second chapter. The third chapter encompasses the first empirical work of this dissertation and primarily explores the impact of social media on capital markets. The empirical analysis falls back to more than 4.5 million posts on the leading Australian financial internet message board HotCopper between January 2008 and May 2016. The findings suggest that social media activity is price relevant for capital markets. Positive investor sentiment, for example, is in this connection contemporaneously and significantly correlated with a stock’s abnormal return. However, the effect diminishes after one month. Arbitrage of presumably informed investors only partially countervail this effect. Postings by individual investors on social media, hence, cause capital markets to overreact to potentially non-relevant information in the short-term. However, negative investor sentiment expressed in internet message boards provides a differentiated picture. Negative investor sentiment is significantly related with the next month’s abnormal returns. Also, an increasing rate of agreement on negative investor sentiment before earnings announcements forecasts negative earnings surprises. Both findings support the information hypothesis that negative internet message board postings contain value-relevant information. The question whether social media activity induces market volatility remains ambiguous. The Granger-tests and the reactions of the impulse-response functions show a bilateral relationship between return volatility and the number of internet message board postings. However, we find in this context that individual investors react more sensitive to market volatility on social media than the other way around. In summary, the results of the first empirical work provide evidence for the economic significance of investor sentiment measured on social media and its asymmetric role in capital markets. We extend the empirical analysis in the fourth chapter of this dissertation and investigate the impact of traditional and social media on target price run-ups before bid announcements. The literature previously documented an increase in the target stock price two months prior to the official bid announcement (e.g., Keown and Pinkerton, 1981). This phenomenon is also referred to as the target run-up. One group of researchers find explanations within the insider hypothesis (leakage of insider information prior to the bid announcement). Another group argues based on the market expectation hypothesis (the market anticipates publicly available information to predict upcoming mergers). Our second empirical work considers 2,765 bid announcements in Australia between January 2008 and August 2015. We use more than 15 thousand news articles, more than 80 thousand posts on the internet message board HotCopper, analyst recommendations, and Google search queries to analyze their relationship with target run-ups before official bid announcements. Thus, we specifically examine the varying impact of investor attention of different investor groups (institutional and individual investors) on target run-ups. The results let us conclude that target run-ups of smaller, unprofitable, and growth firms are significantly related with social media coverage on HotCopper. On the contrary, similar firms that lack media coverage do not experience a significant target run-up prior to a bid announcement. Target run-ups of larger capitalization stocks are, on the other hand, more sensitive to analyst recommendations. The results are consistent with the anecdotal evidence that smaller firms are usually less covered by analysts. Social media closes the information gap for small firms in this perspective. Google search inquiries for target firms are not found to be significantly related to target run-ups. The overall findings of the second empirical work support the market expectation hypothesis. In this regard, social media contributes to the increase of market efficiency and partially closes informational blind spots for smaller firms which might exist due to inefficient allocations of resources or costly information sourcing for smaller firms. The fifth chapter comprises the last empirical work of this dissertation and explores the relationship between media press sentiment and capital markets. We specifically examine the im-pact of aggregated news sentiment indices on the cross-section of returns in the asset pricing context. The literature around asset pricing especially focuses on the determination of risk premia that help to explain stock returns. A central question of our third empirical work is, therefore, whether stock returns are associated with their underlying risk or whether these returns are just a result of irrational market movements in the spirit of the behavioral finance theory. We calculate monthly aggregated news sentiment indices based on more than 120 million unique classified news articles from the Ravenpack News Analytics database between 2000 and 2017. Thus, we construct monthly zero-investment portfolios that go long on (sell) stocks which exhibit on average positive (negative) news sentiment in the previous month. The portfolio yields an annual return of 7.5% even if we control for widely-accepted risk fac-tors, such as market, size, momentum, liquidity, profitability, and investments. The results are mainly driven by positive news sentiment. Hence, we refer this premium to the “premium on optimism”. One possible explanation could be the persistent positive news coverage in the respective time period. The probability of the publication of good news is in particularly high-er if a firm experienced positive news in the prior months. The total results of our third empirical work support the view that news sentiment reflects a risk factor. The overall results of this dissertation have several implications for firms, investors, regulators and researchers in the field of behavioral finance. Firms must learn today to early anticipate crowd movements on (social) media and to deal with putatively fake news. The investor relations department of a firm must engage in this topic more sophistically co