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The impact of media coverage on investor trading behavior and stock returns
Abstract
The investor recognition hypothesis suggests that, when a firm is recognized by investors through the mass media, this helps to increase the firm's investor base and causes reactions in stock prices. Using a comprehensive database of media coverage on Taiwanese listed firms, this paper applies textual analysis to the news content and classifies it into ten news categories. Among them, seven news categories can be identified as conveying a positive or negative tone and the remaining three are news announcements. The empirical results show that investor trading behavior is affected not only by the quantity, but also the quality, of news announcements. Different types of investors have different responses to the tone of media coverage. The trading behavior of foreign institutional investors is consistent with the tone of media coverage. The results are robust after accounting for the effect of several firm risks, characteristics and investors' unobservable private information. In addition, the majority of the positive or negative media coverage classified in this paper is significantly related to the same sign of abnormal returns.
... Behaviorists offer underreaction and overreaction as an explanation for stock market mispricing. Baker and Wurgler [14], Boulland, Degeorge [15], and Wu and Lin [16] have also asserted that investor sentiment affects stock returns. For example, a proportion of investors may have biased expectations concerning market cash flows, which may lead to mispricing across stocks. ...
... This phenomenon is also in line with the disposition effect of investors when dealing with stocks [40,41]. This study supports the behavioral phenomenon of the investor recognition hypothesis through news sentiment that affects prices in financial markets [14,16,27,41]. ...
The primary source of investor interest that disrupts the financial markets is news that reflects the macroeconomy. This study intends to track changes in investors’ positive and negative market attention and their effects on stock market returns by examining the print media portrayal of the China–Pakistan economic corridor (CPEC). We access the daily and weekly coverage of the CPEC by national and international newspapers from the Bloomberg database over the period from January 2015 to December 2019. Using the Harvard psychological dictionary, we categorize the news headlines into positive and negative news sentiments. We then relate the news sentiment to the stock market returns, using quintile analysis, ordinary least squares (OLS), and vector autoregressive (VAR) models. The results show that investors react quickly and significantly to positive news. They pay more for the same stock if the positive news stream increases; hence, the stock market return also increases. In contrast, investors do not react with the same passion to an increase in negative news. These findings are in line with the theoretical rationale of the disposition effect. These outcomes may be useful for active investors and practitioners to devise investment strategies in the presence of the hype surrounding the CPEC in the print media.
... It is especially important to make people accept more easily curfews, lock-downs, and other mobility limitations and be prepared for the economic recovery from the Covid-19 slowdown. Behavioral finance literature provides multiple cases when the mass media tracking is used to gauge both, complex behavior of society and that of financial market ( [30,[51][52][53][54][55][56][57]; and the references therein). In general terms, all these studies agree that media tracking is a powerful mean allowing for data gathering, focused on less rational factors, e.g., market sentiments of investorsć ommunities, public mood at the level of a society, among many other behavioral drivers. ...
... In particular, [53], use an extensive dataset on the social media announcements about the companies, listed on Taiwan stock exchange. They find that investors´trades are influenced by count and by quality of the media publications. ...
This paper analyses the influence of the Covid-19 coverage by the social media upon the shape of the sovereign yield curves of the five major developing countries, namely Federative Republic of B razil, Russian Federation, Republic of India, People’s Republic of China, and the Republic of South Africa (BRICS). The coherenc e between the level, slope, and the curvature of the sovereign yield term structures and the Covid-19 medi a coverage is found to vary between low and high ranges, depending on the phases of the pandemic. The empirical estimations of the yield-curve factors a re performed by means of the Diebold–Li modified version of the Nelson–Siegel model. The intervals of low coherence reveal the capacity of the two latent factors, level and slope, to be used for creating cross-factor diversification strategies, workable under crisis conditions, as evidenced on the example of the ongoing pandemic. Diverse coherence patterns are reported on a per-country basis, highlighting a promising potential of sovereign debt investments for designing cross-country and cross-factor fixed-income strategies, capable of hedging downside risks.
... The mass media such as press circulates the information increasing investor base and price reactions (Wu & Lin, 2017). The information is flown from one place to another through printed or electronic format. ...
... The variation in stock prices are positively related to the "informational surprise" component contained in the news. Different types of investors use different media coverage to strategise their positions (Wu & Lin, 2017). ...
Behavioural finance is emerging field with wide scope. In the absence of enough of literature in Indian context, understanding of individual investor’s behaviour towards stock market by the policy makers, institutions, market infrastructure institutions, and companies find it challenging. The behaviour is caused by the reaction to different factors/attributes. In order to understand the factors that influence the investor’s investment decision a study was undertaken in Indian stock market consisting of 10 sectors with 30 companies listed on BSE-30 SENSEX. A research instrument consisting of 14 attributes was designed and sent to 2100 respondents. 467 responses were collected over a period of 6 months and KANO model was developed to classify the information into ‘must be’, ‘linear’, and ‘delight’ attributes. It was found that ‘must be’ attributes include condition of financial statements, current economic indicators, and the result of technical analysis and ‘insider information’ is a ‘delight’ attribute. The study revealed the factors are affecting the decision making of investors. The consideration of factors for investment decision making is sector specific and helps various parties in understanding the investment decision behaviour of investors’.
... These include the ranking in subscription-based newsletters (e.g., Copeland & Mayers, 1982), news story in business magazines (e.g., Desai & Jain, 1995), news articles and recommendations in columns of newspapers (e.g., Barber & Loeffler, 1993;Tetlock, Saar-Tsechansky, & Macskassy, 2008), segments or shows on television stations (e.g., Engelberg, Sasseville, & Williams, 2012;Busse & Green, 2002), analyst forecasts in financial databases (e.g., Womack, 1996;Loh, 2010), and posts on internet social media (e.g., Antweiler & Frank, 2004;Chen et al., 2014). There are also studies that provide evidence on Taiwan stock markets (e.g., Lin, Lin, & Wang, 2009) for newspaper; Chiao, Lin, and Lee (2017) for TV show; Wu and Lin (2017) for mass media). In general, there are three, main research issues in these studies. ...
... Chen et al. (2014) provide evidence that advices and comments in Seeking Alpha website provide useful information for predicting investment returns. Using a sample of media coverage on TWSE listing firms, Wu and Lin (2017) report that the tone of news or announcements in media coverage has a price impact, though the extent of response varies for different type of investors. Kearney and Liu (2014) provide a review of textual analysis in finance. ...
This study examines the cross-sectional determinants of the price reaction to analysts’ recommendations disseminated through various type of media and for firms listed in Taiwan stock markets. We measure abnormal returns using the market model of event study. Based on the type of media (traditional media/social media) and the type of exchange (Taiwan Stock Exchange (TWSE)/Taipei Exchange (TPEx)), we classify the combined sample observations into four samples and run quantile regressions to investigate whether the relation will be uniform across various quantile levels. Our results show that the relation between firm characteristics and cumulative abnormal returns is not homogeneous across various quantiles of abnormal returns. Our evidence indicates that in general the relation tends to be stronger for firms at higher performance quantile levels and tends to be more pronounced for TWSE firms. The strongest relation is found for the Traditional/TWSE sample, where the abnormal returns are positively related to insider ownership and prior-period earnings, and negatively related to institutional shareholding and price-to-book ratio for firms in the highest abnormal performance quantile.
... At the same time, the direct impact of investor attention on stock returns is a result of "over-attention underperformance" [57]. Firms frequently publish mandatory news announcements, and the business press reports firm-specific news and events through the news media [59]. When a firm is recognized by investors from a mass media report, the reactions of different types of investors to that media coverage will be reflected in both trading decisions and stock prices [60]. ...
... Tetlock [65] used daily content from the Wall Street Journal and found that high media pessimism predicted downward pressure on market prices followed by a reversion to fundamentals, and unusually high or low pessimism predicted high market trading volume. Wu and Lin [59] conducted a textual analysis of news content and found that positive news generated positive abnormal returns and negative news caused negative abnormal returns. Walker [66] found that there was a significant relationship between the total number of housing market articles published in the Financial Times and the return premium of companies involved in the housing market. ...
... Investors and analysts are increasingly relying on information from social media platforms to assess market sentiment and predict potential changes in stock movements. Literature [17] analyzed the information of listed companies reported in the media, and most of the news conveyed positive and negative content, and a small portion of the announcements had different levels of influence on investors' trading behavior. Literature [18] examines the relationship between media coverage and stock returns by collecting media coverage of listed firms over 15 years, and the results reflect the difference between stock returns with and without media coverage, with the latter having a higher base point than the former. ...
The rapid development of big data technology has led to a profound impact on the stock market from media reports, corporate announcements, and other public opinion data. To address this issue, after collecting relevant data, a panel regression model is used to analyze the specific mechanism of media attention on stock returns. Multiple regression models are also used to analyze the effect of corporate clarification announcements on their response to stock market returns. The value of Hauseman’s statistic for the panel data on stock returns and media attention is 0.964, and the probability is 0.67. The correlation between media attention and stock returns is positive. While media attention is significant at a 1% confidence level, every 1% increase in the stock attention index increases the stock return by 0.002%, keeping other variables constant. The overall significance of the regression results for the quality of clarification announcements and their effect is evident, with a R-square value ranging from 11% to 21%. This suggests a good fit between the regression equation and the credibility of the multiple regression results. The regression results show that the time lag, level of detail, and defense attitude of corporate clarification announcements influence their clarity effect, thereby significantly impacting stock market returns. The findings of this paper are significant in promoting the stable development of stock and capital markets.
... Scholarly investigations into the impact of media coverage on businesses have surged in recent years, reflecting the growing recognition of the media's influential role in shaping enterprise narratives. Research has focused on understanding the dynamics of media coverage, examining its role in shaping public opinion [12], influencing investor behavior [13], and affecting enterprise reputation [14]. With the advancement of digital technology, financial reporting is no longer confined to traditional mass media, and social media has emerged as an effective medium for stakeholders to access information [15]. ...
Based on panel data from 2011 to 2021 encompassing 390 listed enterprises in China, we investigate the potential influence of media coverage on the Environmental, Social, and Governance (ESG) performance of heavy-polluting enterprises. The study discerns that positive media coverage significantly contributes to an enhanced ESG performance among heavy-polluting enterprises, particularly those in eastern and western China and those entrenched within highly competitive industries. Positive media coverage predominantly amplifies these enterprises’ environmental and social performance dimensions, while intriguingly, negative media coverage unexpectedly positively impacts their environmental performance. Green total factor productivity and green innovation emerge as crucial facilitators in bolstering the relationship between positive media coverage and the ESG performance of these enterprises. Our research findings provide valuable insights into understanding enterprise ESG behavior and the role of media coverage.
... However, the average trading volume activity after the event declined, signaling that investors perceived the event as negative news, leading to reduced trading activity. This decline in trading volume suggests that investors choose to adopt a wait-and-see approach rather than make immediate trades (Wu & Lin, 2017). Additionally, reduced trading volume might reflect a period of uncertainty or reassessment of investment strategies in response to new information. ...
Purpose – This study examines the effect of Covid-19 in Indonesia on the value of abnormal returns, trading volume activity, and efficiency of the Jakarta Islamic Index (JII), the Indonesian Islamic stock market.Methodology – This study employed the event study model to measure the relationship between important events related to the Indonesian Covid-19 pandemic on stock returns and the stock trading volume of JII indexed companies. Using research analysis techniques in the form of a market-adjusted model, this study determines the period of events before, during, and after the event.Findings – This study found that the global Covid-19 announcement, announcement of the new normal, and announcement of the Covid-19 vaccination gave a significant abnormal return reaction to the JII index and did not provide a significant trading volume activity reaction. Implications – Indonesia's Islamic stock market, which falls into the semi-strong efficient category, responds quickly to important public information such as Covid-19-related announcements. Investors showed high sensitivity to major news, but trading volumes did not change significantly, indicating a cautious adjustment strategy. The different reactions across sectors, especially industry and energy, highlight the need for investor portfolio diversification. It is important for policymakers to provide clear and timely communication to maintain market stability during crises. Further research is required to understand the long-term impact and extend the coverage of international Islamic stock markets.Originality – This study examines several important Covid-19 events that occurred in Indonesia on stock returns and trading volumes in the Indonesian Islamic stock market.
... 1. SIZE is the logarithm of the company's total assets (Bartov et al., 2018). 2. TVA is a measurement of the company's stock liquidity obtained from calculating the number of shares traded (volume) divided by the number of shares outstanding (Chiu et al., 2018) 3. TURN is the ratio between trading and the number of outstanding shares (Wu & Lin, 2017). This study tested machine learning classification analysis to determine the positive or negative tone of tweets and ideas used by investor sentiment variables. ...
This study aims to examine the effect of social media and investor sentiment on the market reaction of the retail sector in Indonesia. Content analysis determines investor sentiment obtained from social media. Information related to the 2019 Indonesian presidential election was used for content analysis. The study results provide evidence that the information available on social media and online investor sentiment have a positive effect on the market reaction of the retail sector in Indonesia. This study also supports the use of signal theory to explain the effect of information available on social media on the capital market in Indonesia. A B S T R A K Penelitian ini bertujuan untuk menguji pengaruh media sosial dan sentimen investor terhadap reaksi pasar sektor retail di Indonesia. Analisis konten digunakan untuk penentuan sentimen investor yang diperoleh dari media sosial. Informasi terkait pemilihan umum presiden Indonesia tahun 2019 menjadi fokus analisis konten dalam penelitian ini. Hasil penelitian memberikan bukti bahwa informasi yang tersedia di dalam media sosial dan sentimen investor berpengaruh positif terhadap reaksi pasar sektor retail di Indonesia. Penelitian ini juga mendukung penggunaan teori sinyal untuk menjelaskan pengaruh informasi yang tersedia di media sosial terhadap pasar modal di Indonesia. This work is licensed under a Creative Commons Attribution 4.0 International License.
... However, the price reaction from news articles is not only larger but also significant. This again reflects findings from Wu and Lin (2017) that show that the majority of positive or negative media coverage is significantly related to similar signed abnormal returns. ...
Studies that quantify the price impact of the information in corporate press releases and news articles mainly focus on quantitative news, such as earnings announcements, dividends, and financial performance-related events, but leave out other corporate news events. Those that do so generally focus on one source of information and do not compare the price impacts from different information sources. Our study aimed to extend previous studies by quantifying and comparing market reactions to corporate press releases and news articles across different news categories. We classified and categorized 100,960 news items, encompassing 26,546 corporate press releases and 74,414 news articles, of 615 firms in the Stock Exchange of Thailand between 1 January 2017 and 31 December 2019. These news items were classified into categories based on the information contained in corporate press releases and news articles. We then studied the market reactions to these news categories. We found that the price impact from corporate releases is sustained for both positive and negative news categories. Our results also show that the positive price impact for news reported by the media tends to reverse, consistent with prior studies. In contrast, the negative price impact from news articles holds; this result differs from previous studies. Our data also show that managers tend to leak and recycle good news while the release of bad news is delayed.
... While impacts are notoriously difficult to measure, several studies have shown a correlation between media coverage and investment levels (c.f. Tetlock 2007;Engelberg and Parsons 2011;Wu and Lin 2017). Even during the COVID-19 pandemic, 'overwhelming panic generated by the news outlets are associated with increasing volatility in the equity markets' (Haroon and Rizvi 2020: 1). ...
Although some studies have previously indicated that the stereotypical western mainstream media narratives about Africa may be shifting, this Special Issue highlights the stickiness of the stereotypes, and some of the platforms on which they continue to be repeated. Some of these studies further show how African media are also responsible for ongoing circulation of the stereotypes. While the data are discouraging, there are pockets of hope on digital media (including social media), where women and youth are taking back the proverbial pen using storytelling and humour to show that Africa is neither monolithic, nor all doom and gloom. Even through the COVID-19 pandemic, Africans entertained the world with music, dancing and comedy, proving resilience and optimism, against Afro-pessimistic narratives
... , o Buy-and-Hold Return(Jiang, Lee, Martin & Zhou, 2019) e o retorno anormal estimado pelo modelo de mercado(Campbell, Cecchini, Cianci, Ehinger, & Werner, 2019;Wu & Lin, 2017).Foram encontrados, também, estudos que utilizaram o excesso de retorno obtido por meio do modelo de fatores de risco deCarhart (1997), como a pesquisa de Hillert, Jacobs e Müller(2018), ou pelos três fatores de risco de Fama e French (1993) e cinco fatores de risco de Fama e French (2015), nas pesquisas de Houlihan e Creamer (2017) e Buehlmaier e Whited (2018), respectivamente. A abordagem utilizada na pesquisa de Doukas, Guo, Lam e Xiao (2016) foi o retorno anormal ajustado pelo mercado para análise de curto prazo e o Buy-and-Hold Abnormal Return (BHAR) para o longo prazo; isso porque, com o BHAR, é possível calcular o retorno anormal de ações com volatilidade diferente e menor viés no longo prazo do que o CAR (Yan, Xiong, Meng, & Zou, 2019). ...
Objetivo: Analisar a evolução das pesquisas com a abordagem de análise textual como ferramenta de predição do retorno das ações no mercado de capitais.Método: Revisão sistemática auxiliada pelo software VosViewer, em que foram analisados 78 artigos empíricos da temática, publicados em inglês e indexados na Web of Science. Resultados: Os resultados aglutinam evidências de que o sentimento textual é capaz de prever o retorno das ações, sendo capturado em diversas fontes de informação. Na análise, emergiram quatro categorias que correspondem às fontes de informação para a análise textual: notícias financeiras (31), divulgações corporativas (29), mídias sociais (16) e outros documentos (8). Contribuições: Este trabalho contribui com a academia ao demonstrar os principais achados de pesquisas elaboradas sobre o assunto, além de sugerir tópicos para trabalhos futuros. No âmbito prático, as evidências transmitem aos investidores que informações textuais acerca das empresas também podem gerar reações no mercado.
... In this case, the financial markets are not efficient in a way that all available information is instantaneously integrated into prices as assumed by proponents of the EMH (Strycharz et al., 2018). For instance, studies have found that the media influences investing behavior (Tetlock, 2007;Fang and Peress, 2009;Jiao et al., 2020) as well as impacts asset prices through investors' reactions, sentiments, and attention (Peress, 2014;Wu and Lin, 2017;Liu and Han, 2020;. Others have shown that media attention on financial assets can affect their trading volume as well as drive their share price reactions (Engelberg and Parsons, 2011;Dougal et al., 2012;Fang and Peress, 2009). ...
... The authors (Sohn et al., 2012) who have assessed media as an agent of financial socialization have viewed it rather basically, i.e., only as a source of financial/economic knowledge. There are also some studies (Wu & Lin, 2017) that have evaluated the impact of media on an individual's financial behavior; however, they do not examine financial socialization. Additionally, there are a limited number of empirical studies that have evaluated financial socialization agents all together (Cho et al., 2012; Copur & Gutter, 2019) and assessed their complex effects. ...
This study explores survey data of investors in peer-to-peer (P2P) lending aiming to assess their investment literacy, how this literacy is affected by their financial socialization and the strength of their social ties, and whether this effect differs among investors’ sociodemographic groups. Our research model was built based on Gudmunson and Danes (2011), Gudmunson et al. (2016) and Potrich et al. (2016). It measured investment literacy, assessing three components — knowledge, skills and attitudes; included multiple socialization agents; and investigated both direct and indirect effects of financial socialization. Descriptive and reliability analysis, confirmatory factor analysis (CFA), t-tests, analysis of variance (ANOVA) and second-order structural equation modeling (SEM) analysis were employed. The results indicate that the investment literacy of P2P lending investors is high. The compound direct effect of financial socialization on the overall level of investment literacy was found to be positive and stronger than on its individual components. Although the strength of social ties had a strong influence on financial socialization, its indirect effect on investment literacy was rather weak. Peers proved to be the main socialization agent and exhibited the strongest social ties with the respondents. The strongest effect of financial socialization on the investment literacy was identified for P2P lending investors in 18–34 years group working in the financial sector with a net monthly income below 1500 euros. The research contributes to the existing literature by providing the methodology and valuable insights into the level of financial literacy among P2P investors and how investment literacy is or is not formed under social interaction in a close social environment.
... In this case, the financial markets are not efficient in a way that all available information is instantaneously integrated into prices as assumed by proponents of the EMH (Strycharz et al., 2018). For instance, studies have found that the media influences investing behavior (Tetlock, 2007;Fang and Peress, 2009;Jiao et al., 2020) as well as impacts asset prices through investors' reactions, sentiments, and attention (Peress, 2014;Wu and Lin, 2017;Liu and Han, 2020;. Others have shown that media attention on financial assets can affect their trading volume as well as drive their share price reactions (Engelberg and Parsons, 2011;Dougal et al., 2012;Fang and Peress, 2009). ...
... Klibanoff, Lamont, and Wizman (1998) and Tetlock (2007) argued that important media pessimism leads to downward pressure on market prices, as pessimistic news affects investor sentiment. Wu and Lin's (2017) empirical results show that both the positive and negative tone of media coverage justify abnormal returns. Dang et al. (2020) indicated that media coverage is negatively correlated with stock price synchronization. ...
We provide the first empirical study on the role of panic and stress related to the COVID-19 pandemic, including six uncertainties and the four most traded cryptocurrencies, on three green bond market volatilities. Based on daily data covering the period from January 1, 2020 to January 31, 2022, we combine Diebold and Yilmaz's (2012, 2014) time domain spillover approach and Ando et al.'s (2022) quantile regression framework to investigate the time-frequency spillover connectedness among markets and measure the direction and intensity of the net transmission effect under extreme negative and positive event conditions, and normal states. We further provide novel insights into the green finance literature by examining sensitivity to quantile analysis of the net transfer mechanism between green bonds, cryptocurrencies, and pandemic uncertainty. Regarding the network connectedness analysis, the results reveal strong net information spillover transmission among markets under the bearish market. In extremely negative event circumstances, the MSCI Euro green bond acts as the leading net shock receiver in the system, whereas COVID-19 fake news appears as the largest net shock contributor, followed by BTC. According to sensitivity to quantile analysis, the net dynamic shock transfer mechanism is time-varying and quantile-dependent. Overall, our work uncovers crucial implications for investors and policymakers.
... Apparently, once the pandemic was controlled, the country started to prioritize economic recovery, which also corroborates studies that suggest that the behavior of investors is affected by the tone of media coverage [C.-H. Wu & Lin, 2017]. In the story Xi: Balance epidemic, economy (02/04/2020), China Daily reports that President Xi Jinping has instructed government officials to take more measures to coordinate disease prevention and the resumption of economic production, in an effort to meet the development goals for that year. ...
We analyzed 95,970 stories on COVID-19 published in 2020 by newspapers in US, UK, China and Brazil — countries marked by controversial management of the crisis. Through a text mining approach, we identified main topics, subjects, actors and the level of attention. The coverage was politicized in “The New York Times” and “Folha de S. Paulo”; focused on health aspects in “The Guardian”; and emphasized the economic situation in “China Daily”. In this sense, the pandemic has motivated a deeper approach to the multiple dimensions of science and health, pointing to a broader perspective of science communication.
... In the information era, media-from social media to mainstream media, such as news media-plays a vital role in building investors' attitudes and shaping their investing behavior (Fang & Peress, 2009;Tetlock, 2007). Such "media-driven investment behavior" impacts asset prices through investors' reactions, sentiments, and attention (Aman, 2013;Hayo & Neuenkirch, 2012;Liu & Han, 2020;Sun et al., 2021;Wu & Lin, 2017;Zhao, 2020). Recently, public attention has received much importance in the asset pricing literature, e.g., stocks (El Ouadghiri et al., 2021;Wen et al., 2019;Xu et al., 2021), agricultural commodities (Mišečka et al., 2019), and Bitcoin (Dastgir et al., 2019;Philippas et al., 2019). ...
We analyze the dynamic spillover impact of cryptocurrency environmental attention (ICEA) on three asset classes: commodities, green bonds (GBs), and environment-related stocks. Our wavelet-based analysis suggests that ICEA sharply escalated after the first quarter of 2021. During this period of intense attention, only the soybean commodity and Solactive GB tend to move positively and negatively with ICEA, respectively. Accordingly, the clean energy, sustainability, and Environmental, Social, and Governance (ESG) stock indices are positively associated with ICEA during 2018-2019 at the medium frequency bands. In most periods and frequency domains, most commodities, GBs, and environment-related stocks are not strongly linked to ICEA. Moreover, Diebold and Yilmaz's (2014) spillover estimations signify no strong spillover effect of ICEA on the asset classes considered in this study. These findings are further corroborated by the wavelet-based Granger causality analysis. Moreover, our quantile regression (QR) estimations suggest that most assets are adversely influenced by ICEA, depending on the market conditions. Our research conveys some novel and vital policy ramifications to both investors and policymakers.
... Investors largely rely on the media press to gather information related to climate change with relatively lower costs, which helps the spread of information in a wider range. Furthermore, in addition to its information disseminating role, the media can also create information with its own judgments (Wu and Lin 2017). News media might provide investors with new information indicating whether the climate-related information of the firm is good or bad news. ...
This study aims to enrich our understanding of the valuation consequence of climate risk in financial markets. The primary focus of our study is on the stock price reaction to firms’ climate-risk-related information. We employ transcripts of Chinese listed firms’ performance briefings to capture the climate risk at the firm level. Using a sample of Chinese listed firms between 2009 and 2021, we find that greater corporate climate risks lead to negative market reactions over a short time window, consistent with the market quickly comprehending corporate climate risks. This result holds for a series of robustness checks. We further find that the negative impact of corporate climate risk on the stock price reaction operates through the increased market trading activities, greater investor attention, and reduced positive media coverage. Finally, we demonstrate that industry carbon emission, local abnormal temperature, state ownership, institutional shareholding, and dividend payout are important moderators that shape the association of the corporate climate risk and the adverse market reaction. Our evidence suggests that disclosures of climate-related information can help the stock market to price climate risk more efficiently.
... From the conclusion of the model in Table 4, we find that CSR can significantly improve the social media slant to acquirers. Our finding is consistent with conclusions of Gurun and Butler [8], Solomon [9], Tetlock [12], and Tetlock et al. [13] for US, Aman [14] for Japan, Kim et al. [15] for China, Wu and Lin [18] for Taiwan. However, CSR is not significant for acquirers' systemic risk indicators (β M -3 f actors Model, β HML -3 f actors Model, and β SMB -3 f actors Model) or for idiosyncratic risk indicators (Idio-risk-3factors Model), which is contrary to the findings of existing research. ...
We used the corporate social responsibility (CSR) data from Hexun Finance to analyze the three channels of market investor evaluation in the process of Chinese listed companies’ mergers and acquisitions (M&A). We found that: (1) because many CSR behaviors of Chinese listed companies are passive, driven by the environment, government, and regulatory authority, rather than proactive CSR for the long-term interests of the company, Chinese market investors are not concerned with the CSR performance of acquirers before the merger; (2) because passive CSR behavior cannot change the system risk and heterogeneity risk of the acquirers, CSR has no effect on the investor evaluation at the acquirer merger; (3) passive CSR can be used to evaluate public opinion, but CSR cannot change the market concerns of investors because investors only consider the systemic risks and heterogeneity rather than the social media evaluation of the company when pricing; and (4) with further study of the integration effect of CSR after M&A, we found that CSR does not reduce the M&A premium, only increases the return on asset (ROA) of the company within one year after M&A, and does not improve the company’s ROA for a long time. Our conclusions help explain why Chinese financial market investors are not concerned with the CSR performance of the M&A party prior to M&A.
... However, there are many anomalies showing that the exogenous information plays an important role in the stock market. News, for example, as one type of the exogenous information, has been intensively investigated for its influence on the stock market, including the relation between the news and stock prices [1,2], stock returns [3], trading volumes [4], investors' behavior [5,6], and the correlation between the inherent sentiment behind the news and the stock market [7]. With the development of the Internet, the web has become one of the most important sources of news. ...
We investigate the dynamic cross-correlations between mass media news, new media news, and stock returns for the SSE 50 Index in Chinese stock market by employing the MF-DCCA method. The empirical results show that (1) there exist power-law cross-correlations between two types of news as well as between news and its corresponding SSE 50 Index return; (2) the cross-correlations between mass media news and SSE 50 Index returns show larger multifractality and more complicated structures; (3) mass media news and new media news have both complementary and competitive relationships; (4) with the rolling window analysis, we further find that there is a general increasing trend for the cross-correlations between the two types of news as well as the cross-correlations between news and returns and this trend becomes more persistent over time.
This study examines the interlinkages among diverse cryptocurrency classes and their multiscale relationship with media climate change concerns to examine how cryptocurrency returns respond to rising climate change concerns. The analysis includes 11 cryptocurrencies classified as dirty, gold-backed, energy, and sustainable and their behavior regarding media climate change concerns, including transition and physical risks. Using squared wavelet coherence and partial wavelet coherence (PWC) on daily data from January 1, 2014 to June 29, 2024, this study shows time-frequency-dependent market integration among cryptocurrency pairs. During rising climate change concerns, returns decrease for some cryptocurrencies while increasing for XRP, implying higher investors' trust in sustainable cryptocurrencies. PWC analysis reveals significant influence of climate change concerns on pairwise returns connectedness among various cryptocurrency classes. This study highlights the need for cryptocurrency traders to incorporate media climate change information into their investment decisions, contributing insights into using diverse crypto-assets for risk management.
How media coverage influences the ESG preferences of institutional investors remains an unsettled issue. We tackle this issue based on a framing-to-priming framework. By analyzing a dataset of 22,941 observations from Chinese listed firms from 2012 to 2021, we find that positive media coverage attracts institutional investors with inherent ESG preferences to invest in the firm, whereas negative media coverage discourages their investment. It implies that a screening process underpins the institutional investors’ ESG preferences. Moreover, our findings indicate that analyst attention and public attention play pivotal mediating roles in the relationship between media coverage and institutional investors’ ESG preferences.
Purpose
The dissemination of misleading and false information through media can jeopardize a company’s reputation, thus posing a threat to its stock and performance. Institutional investors are known to influence capital markets. Therefore, this paper investigates whether institutional investors engage in shaping the media sentiment stock nexus, stabilize company stocks and enhance performance.
Design/methodology/approach
We first investigate the effect of media sentiment on market reactions by using panel regression models. To examine the role of institutional investors, we design a quasi-experiment by exploiting the Financial Crisis of 2008 and go further by examining the heterogeneity across levels of institutional ownership. Due to risk-averse, investors may respond asymmetrically to pessimistic and positive sentiment. Accordingly, we split the sample into two sub-types, good news and bad news, based on keywords representing positive or negative content.
Findings
We find supportive evidence that institutional investors have impacts on how the markets react to media news, and the impacts are heterogeneous in the face of bad and good news. We conjecture that institutional investors act as a stabilizer of stock prices through media sentiment management.
Originality/value
This paper confirms the distinctive effects of institutional investors on capital markets, and uncovers the behind-the-scenes intervention and possible causal link running from institutional investors to media sentiment management. It contributes to the broad field of institutional investors' behavior, media news involvement in capital markets and market efficiency.
This paper investigates the impact of unscheduled news announcements on market contagion during the COVID‐19 pandemic. Using coexceedance of stock returns as a metric for market contagion effect, we assess the contribution of news releases from the United States and China on the financial contagion of a representative group of global equity markets through a quantile analysis framework. The empirical results are mixed: news events originating in the United States have a greater impact on market contagion compared with those originating in China, especially at lower quantiles. Stock markets respond asymmetrically to good news versus bad news, and the latter lead to a sharper common fall among the markets than the boost to the market caused by good news. We also find evidence that conditional variance and investor sentiment play some role in the spread of financial market crises, despite differences in extent and direction.
The COVID-19 virus created a health crisis that led to one of the biggest economic crises in the world. This study analyzes the effects of different variables on the stock indexes of 15 different countries grouped into five areas/regions: Europe, the United States, South America, New Zealand, and Asia. The variables include data regarding COVID-19 on infections and death as well as news regarding government actions. The descriptive statistics and the regression analysis expose differences between the areas across all the variables. The variables with the strongest effects are the number of infected people and the number of recoveries, except for South America where only the number of infected people had the strongest effect. In addition, in the United States and New Zealand, infection of famous people and/or people in key positions is the most significant variable, while in Asia and South America it was the behavior of the public and in Europe it was the restrictions on the education system.
This study empirically investigates the influence of news coverage related to COVID-19 and UK-wide stock market returns. A robust regression model is applied, and demonstrates the asymmetric dependence between stock market data and coverage of COVID-19 including media items, fake news and contagion. The study findings point to the benefits of utilising appropriate communications channels more strongly to minimise financial disruptions related to COVID-19. This particular research appears to be amongst the first research to consider both Covid-19 media coverage and stock return. Our data is limited for only a single country. More clarification for Covid-19 need qualitative understandings into UK market. The control variables fundamentally partial in this topic
Investments made by investors contribute to both inflow and outflow of funds in the capital market. Investment decision making is complex due to its uncertain behaviour. In literature, there is evidence of a gap between intention and behaviour among other aspects of human behaviour like consumer buying behaviour. Therefore, this study explores the intention–behaviour gap in investment behaviour of retail investors by examining the effect of two moderators, namely risk propensity (RP) and opinion of stakeholders (OPI). The present study also focuses on identifying financial and non-financial factors influencing equity investment intention (EII) and measures its impact on equity investment behaviour (EIB). A model is, thus, conceptualized and hypotheses have been developed accordingly. For validation of the model, a set of primary data of retail investors is collected (through questionnaire framing) and the hypotheses are tested by using advanced statistical techniques, namely structural equation modelling. The outcomes of this study signify the impact of EII that catapults behavioural approach in investment decision making for any potential investor in the near future.
The volatility of the initial return and trading volume is evident from early observations of the Malaysian initial public offering (IPO) market on the first trading day. Making informed investment decisions is essential for a more accurate assessment of businesses and capital security. Investors should therefore be aware of what influences IPO initial return and trading volume. However, only a few amounts of prior research on the initial return and trading volume on the first trading day of an IPO has focused on the issue of investors’ reaction. Specifically, previous studies have not taken into consideration how individual investors feel about IPO companies as the primary influence. In this study, the sentiment of individual investors is measured using the Google Search Volume Score (GSVS), a practical approximation (Da et al., 2011). This is because most people who use Google to look up information, particularly about recently released equities, are individual investors. Between 2004 and 2020, 271 initial public offerings (IPOs) listed on Bursa Malaysia’s Main Market and Access, Certainty, Efficiency (ACE) Market made up the study sample. This study demonstrated that pre-market investor sentiment significantly and favourably effects IPO initial return and trading volume on the first trading day based on ordinary least square regression (OLS) models.
Purpose
This study aims to determine whether the stock holdings of equity mutual funds are informative for predicting future stock performance in the Chinese market. It is a puzzle that actively managed mutual funds underperform passive benchmarks, whereas retail investors still delegate investment decisions to the fund managers. The present study sheds light on whether mutual fund managers possess security selection skills in their top ten holdings.
Design/methodology/approach
By regression analysis and portfolio sorting, this study focuses on 830 Chinese A-share stocks in the industry research reports from the Guotai Junan Securities Company. It collects mutual fund's top ten holdings data from the Wind Financial Terminal between 2019Q1 and 2021Q1. As robustness checks, the result holds for the fixed-effect model, an additional measure of ranks in the top ten holdings, the predictability test based on the confusion matrix and two stage least square (2SLS) regression.
Findings
The authors find that the top ten holdings by equity mutual funds are informative for predicting stock performance and can provide valuable information for investors to support their decision-making.
Practical implications
The findings of this study provide insightful guidance for retail investors in making investment decisions and support the hypothesis that active fund management adds value.
Originality/value
Firstly, the authors find that the top ten holdings of Chinese mutual funds show significantly positive signals for future stock excess returns, indicating the selection skills of fund managers. Secondly, the above positive relationship exhibits a diminishing marginal effect with more funds holding this stock. Thirdly, the authors find that the predictability horizon of the number of overweighing funds is up to three quarters and then diminishes in the fourth quarter. Finally, investors have a 59% prediction accuracy for the whole stock sample and an 85% precision conditional on the predicted positive subsample to outperform the market. The authors also address the endogeneity and reverse causality issues.
Motivated by the idea that “coverage by mass media can play a role in alleviating information problems even if it does not break genuine news” (Fang and Peress, 2009: 2050), this study is first to relate media coverage to performing moving average (MA) technical trading in the cross-section. Testing a sample of Taiwanese listed stocks over the period 1996 to 2021, we find that the MA strategy’s profitability is high (low) for portfolios grouped by stocks with low (high) media coverage. For the “low-media-coverage” portfolio, the MA strategy earns about 24.75% per annum, adjusting for the Fama–French five risk factors. The MA’s superior performance on the “low-media-coverage” portfolio remains after controlling for market liquidity and market sentiment. We also find that the low media effect on the MA strategy’s profitability is more pronounced during recessionary periods. Our overall results are supported by the hypothesis that a low level of media coverage induces investor inattention and slows information diffusion, which amplifies the investors’ under reaction bias and stronger price continuation, being associated with a higher MA strategy’s profitability.
The sharing economy model that was developed in the last decade has a major effect on a different aspect of life. The purpose of this research is to test the effect of a sharing economy product on its competitors. Specifically, this study used the event study approach to examine how Airbnb announcements affected hotel stock prices. To accomplish this goal, we used 180 Airbnb announcements to investigate the general effect of Airbnb, and the effects according to the type of announcement and the type of audience. The findings indicate that general Airbnb announcements have a negative effect on the hotel stock prices. In addition, investors respond negatively to positive announcements but not to neutral ones. Finally, announcements targeting young people have no effect on the stock prices of hotel companies, while the effect of announcements targeting families lasts the longest. We also explored investment strategies for general investors and those with inside information. We suggest that general investors short sell the stock on the day of the news announcement. Investors with inside information should short sell the stock a few days before the day of the news announcement. In both cases, investors should close their positions a few days later depending on the type of announcement.
In this paper, we examine the impact of investor sentiment on Bitcoin returns. Using a large dataset of messages discussed on social media and several financial indicators, we create a sentiment indicator based on computational text analysis and driven by the principal component analysis (PCA) method. We utilize a vector autoregressive analysis and other analytical methods to examine the sentiment index–bitcoin return nexus. Our findings reveal that the sentiment index is a strong predictor of cryptocurrency market returns in the short term. Furthermore, we confirm that during the COVID-19 pandemic, investors' sentiments significantly impacted Bitcoin returns. Our results show that the proposed sentiment index can generate excess returns for investors who utilize it as a return predictor. Our empirical findings suggest important policy implications.
Purpose
This study examines the influence of various COVID-19 catastrophes variables on the stock market liquidity, considering the market depth and market tightness in the technology industry of the four biggest ASEAN capital markets.
Design/methodology/approach
The study utilised the panel data regression analysis obtained from 177 listed technology companies across the four ASEAN countries from March 2, 2020 to June 30, 2021 using the random effect and weighted least squares. The study also supported the result with robustness test, implementing the quantile regression to further present companies' segmentation within the variables.
Findings
The regression results indicate that daily growth COVID-19 confirmed cases and stringency that adversely impacted the stock market liquidity. Confirmed deaths were also found to have a detrimental effect on the stock market liquidity. On the other hand, recoveries and vaccination of COVID-19 enhance the stock market liquidity to escalate.
Research limitations/implications
The study affirms that stock market liquidity is bound to be driven by the COVID-19 variables, but only to be limited to the technology industry observed in four major ASEAN capital markets. Awareness by investors and government could be shifted towards the rise of confirmed cases, recoveries, vaccination and stringency as it improves the liquidity of capital market in aggregate. However, rise of confirmed deaths negatively affect the liquidity. All in all, government and stock market regulator should promote transparency to boost investors' confidence in trading.
Originality/value
This study initiates the investigation in the four biggest ASEAN capital markets, particularly in the technology industry, regarding the COVID-19 catastrophes and stock market liquidity in terms of both market depth and market tightness. Further, this study enriches the impact of COVID-19 by taking the recovery cases and vaccination of COVID-19 as additional consideration.
The impact of the COVID-19 pandemic on tourism has received general attention in the literature, while the role of news during the pandemic has been ignored. Using a time-frequency connectedness approach, this paper focuses on the spillover effects of COVID-19-related news on the return and volatility of four regional travel and leisure (T&L) stocks. The results in the time domain reveal significant spillovers from news to T&L stocks. Specifically, in the return system, T&L stocks are mainly affected by media hype, while in the volatility system, they are mainly affected by panic sentiment. This paper also finds two risk contagion paths. The contagion index and Global T&L stock are the sources of these paths. The results in the frequency domain indicate that the shocks in the T&L industry are mainly driven by short-term fluctuations. The spillovers from news to T&L stocks and among these T&L stocks are stronger within 1 month.
Many scholars have explored the COVID-19 impact on the crude oil, gold, and Bitcoin markets, whereas most have ignored the media coverage influence. This paper focuses on examining information spillover from epidemic-related news to the crude oil, gold, and Bitcoin markets with the time-frequency analysis method. The empirical results reveal that both the return and volatility spillovers from epidemic-related news to the crude oil, gold, and Bitcoin markets are stronger in the short term (less than 1 week). In the long term, only the media sentiment index notably impacts crude oil, gold, and Bitcoin market returns. The volatility spillover from media coverage to crude oil mainly occurs in the short term. Regarding the gold and Bitcoin markets, the long-term volatility spillovers are significant. An obvious risk contagion path is found. Media hype is the main risk transmitter and transmits vast shocks to these three markets, especially the Bitcoin market, which subsequently transmits these shocks to the gold market. Risk accumulates systemically in the gold and Bitcoin markets. These findings have crucial empirical implications for policymakers and investors when formulating related short- or long-term decisions during the pandemic.
Moderation effect of openness and extraversion on the association between financial market information and trading behaviour of individual investors. Paradigms, 15(1), 67-73. The purpose of this paper is to examine the moderating influence of openness and extraversion personality traits on the association between financial market information and the trading behaviour of individual investors. For this study, data was collected from PSX Lahore office consisting of 238 individual investors selected on a random basis. Two dimensions of big-five personality traits, openness and extraversion, are used as moderators to assess the deviations in the relationship amid market information and investors' trading behavior. The findings of this study endorsed that openness and extraversion have significant moderating control on the connection between financial market information and stock trading behavior. The openness moderates positively aligned to previous findings whereas extraversion negatively moderates the link which deviates from the findings of previous researchers. This study proposes that the personality traits of the investors can be relevant but ignore the rational decision-making process regarding investment in stocks in a financial market. The data was collected at one time which may be dependent on the mood of the respondent. The findings of this study would be helpful theoretically as well as practically in financial markets and further researches. The study throws light on openness and extraversion impact with the level of information about the financial market on stock trading behavior which opens the new theoretical as well as practical insights in the PSX context.
COVID-19 pandemic created a health emergency that led to a huge global economic crisis. This article examines the effects of a wide range of variables including the number of infections, deaths, and recoveries, as well as categorical variables like public behaviour and government restrictions on stock indexes on 16 different countries. It compares the situation in Israel with the other explored countries. The regression analysis revealed that while in Israel all the variables affected stock-index returns, in the other countries only a few of the variables did so.
Capital enrichment (CE) results from capital flows, which reflect the capital distribution among different regions and industries. This paper constructs the evaluation model of resource allocation efficiency from the perspective of capital and innovation resources. It expounds on CE’s theoretical mechanism by using the panel data from 2011 to 2018 for system GMM estimation. It finds that the manufacturing capital allocation efficiency (CAE) and innovation resource allocation efficiency (IRAE) show a volatile development trend. Both static and dynamic panel models show that there is a significant U-shaped curvilinear relationship between CE and CAE, CE and IRAE. CE’s inhibitory effect on CAE and IRAE decreases with the improvement of CE until it exceeds the critical value of 8.27 and 8.93. After that, its impact on CAE and IRAE changes from negative to positive.
Numerous studies have proven that news media sentiment has an impact on stock market volatility, making topics such as how to quantify news media sentiment and use it to predict stock market volatility increasingly relevant. In this paper, a Chinese financial sentiment lexicon was constructed to quantify the emotions in the news media as a sentiment index to be added to the model and establish new prediction models HAR-RV-AI and GRU-AI. To compare the prediction ability of the models, we consider the loss function and model confidence set (MCS) test as the evaluation criterion and employ the rolling window strategy for out-of-sample forecasting. The prediction results of the GRU model are found to be better than the HAR-RV model, and the prediction effect of the model improved after the addition of the news media sentiment index.
Purpose
The purpose of this paper is to develop an in-depth contextualized understanding of individual investors’ buying decision in Indian stock market. Specifically, it provides answers to: how do individual investors make buying decision in stock market; and how and when do biases set in during such decisions. The paper also brings forward some aspects of individual’s journey as an investor.
Design/methodology/approach
Given the exploratory nature of this study, the paper takes a step away from typically used variance approach and instead uses a process approach. The authors do in-depth one-on-one interview, where each respondent shares his/her lived experiences as an investor retrospectively. To understand buying decision, each respondent is asked to elaborate three significant buying transactions carried out by him/ her in stock market.
Findings
Socio-cultural factors are found to have significant influence in inducing respondents to enter market. “Safe” vs “Risky” mental account emerges as the prominent stock categorization done by Indian investors. Three building blocks, namely, Identification, Rationalization and Further Validation emerge as the building blocks that culminate into buying decision of individual investors. The biases are seen to play a dual role in such decisions; as Attention Boosters and Rationales.
Originality/value
This study, to the best of authors’ knowledge, is first of its kind which amalgamates behavioral biases with phenomenon such as attention and Rationalization, to understand “how” behavioral biases set in during buying decision of individual investors.
We survey the works applying text analytics to the study of news media in financial markets beyond intraday horizons, and expand into the fundamental economic theory and concepts relevant to the field. We compare and contrast the news sources, textual analysis methods and empirical modelling approaches adopted within the literature. We distil and categorise the key empirical insights, and summarise the bibliographic history of the literature so far. While this rapidly growing field has yielded many exciting discoveries, there are a number of promising avenues for future research which will only benefit from continued advances in computational technology.
The Global Financial Crisis and stock market crashes that occurred in various countries during 2000–2015 have exposed significant weaknesses in economies, Stock Indices and “Regulatory Strategic Alliances” and Intertemporal Asset Pricing Theories.
We construct a new, parsimonious, measure of disclosure quality – disaggregation quality (DQ) – and offer validation tests. DQ captures the level of disaggregation of accounting data through a count of non-missing Compustat line items, and reflects the extent of details in firms’ annual reports. Conceptually DQ differs from existing disclosure measures in that it captures the ‘fineness’ of data and is based on a comprehensive set of accounting line items in annual reports. Unlike existing measures which are usually applicable for a subset of firms or are based on a subset of information items, DQ can be generated for the universe of Compustat industrial firms. We conduct three sets of validation tests by examining DQ's association with variables predicted by prior literature to be associated with information quality. DQ is negatively (positively) associated with analyst forecast dispersion (accuracy), negatively associated with bid-ask spreads and cost of equity. These associations continue to hold after we control for firm fundamentals. Taken together, results from this battery of validation tests are consistent with our measure capturing disclosure quality.This article is protected by copyright. All rights reserved
If competitive equilibrium is defined as a situation in which prices are such that all arbitrage profits are eliminated, is it possible that a competitive economy always be in equilibrium? Clearly not, for then those who arbitrage make no (private) return from their (privately) costly activity. Hence the assumptions that all markets, including that for information, are always in equilibrium and always perfectly arbitraged are inconsistent when arbitrage is costly. We propose here a model in which there is an equilibrium degree of disequilibrium: prices reflect the information of informed individuals (arbitrageurs) but only partially, so that those who expend resources to obtain information do receive compensation. How informative the price system is depends on the number of individuals who are informed; but the number of individuals who are informed is itself an endogenous variable in the model. The model is the simplest one in which prices perform a well-articulated role in conveying information from the informed to the uninformed. When informed individuals observe information that the return to a security is going to be high, they bid its price up, and conversely when they observe information that the return is going to be low. Thus the price system makes publicly available the information obtained by informed individuals to the uninformed. In general, however, it does this imperfectly; this is perhaps lucky, for were it to do it perfectly , an equilibrium would not exist. In the introduction, we shall discuss the general methodology and present some conjectures concerning certain properties of the equilibrium. The remaining analytic sections of the paper are devoted to analyzing in detail an important example of our general model, in which our conjectures concerning the nature of the equilibrium can be shown to be correct. We conclude with a discussion of the implications of our approach and results, with particular emphasis on the relationship of our results to the literature on "efficient capital markets."
We present a synthesis of academic research on corporate payout policy grounded in the pioneering contributions of Lintner [1956] and Miller and Modigliani [1961]. We conclude that a simple asymmetric information framework that emphasizes the need to distribute FCF and that embeds agency costs (as in Jensen [1986]) and security valuation problems (as in Myers and Majluf [1984]) does a good job explaining the main features of observed payout policies - i.e., the massive size of corporate payouts, their timing and, to a lesser degree, their (dividend versus stock repurchase) form. We also conclude that managerial signaling motives, clientele demands, tax deferral benefits, investors’ behavioral heuristics, and investor sentiment have at best minor influences on payout policy, but that behavioral biases at the managerial level (e.g., over-confidence) and the idiosyncratic preferences of controlling stockholders plausibly have a first-order impact. Contents: 1) Introduction. 2) Basic theory: The need to distribute FCF is foundational. 3) Security valuation problems, agency costs, and optimal payout policy. 4) Corporate payouts: Scale, concentration, and earnings linkage. 5) Payouts and earnings: A closer look. 6) Are dividends disappearing? 7) Why do dividends survive? 8) Signaling and the information content of dividends. 9) Behavioral influences on payout policy. 10) Clientele effects: Transaction costs, institutional ownership, and payout policy. 11) Controlling stockholders and payout policy. 12) Taxes and payout policy. 13) The advantages of stock repurchases. 14) Conclusion: What we know about payout policy and promising areas for future research. Appendix: Microsoft’s dividend and stock buyback plans. References.
We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. Previous research has not been successful in quantifying tone using positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing.
This article studies differences in the information content of 870,000 news announcements in 56 markets around the world. In most developed markets, a firm's stock price moves much more on days with public news about the firm. In contrast, in many emerging markets volatility is similar on news and non-news days. We examine several hypotheses for our findings. Cross-country differences in stock price reactions are best explained by insider trading, followed by differences in the quality of the news dissemination mechanism. Our findings are useful for quantifying the extent of insider trading and how the financial media affects international markets. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.
This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the cross-sectional positive return–illiquidity relationship. Also, stock returns are negatively related over time to contemporaneous unexpected illiquidity. The illiquidity measure here is the average across stocks of the daily ratio of absolute stock return to dollar volume, which is easily obtained from daily stock data for long time series in most stock markets. Illiquidity affects more strongly small firm stocks, thus explaining time series variations in their premiums over time.
Using a comprehensive database of headlines about individual companies, I examine monthly returns following public news. I compare them to stocks with similar returns, but no identifiable public news. There is a difference between the two sets. I find strong drift after bad news. Investors seem to react slowly to this information. I also find reversal after extreme price movements unaccompanied by public news. The separate patterns appear even after adjustments for risk exposure and other effects. They are, however, mainly seen in smaller, more illiquid stocks. These findings support some integrated theories of investor over- and underreaction.
Individual investor trading results in systematic and economically large losses. Using a complete trading history of all investors
in Taiwan, we document that the aggregate portfolio of individuals suffers an annual performance penalty of 3.8 percentage
points. Individual investor losses are equivalent to 2.2% of Taiwan's gross domestic product or 2.8% of the total personal
income. Virtually all individual trading losses can be traced to their aggressive orders. In contrast, institutions enjoy
an annual performance boost of 1.5 percentage points, and both the aggressive and passive trades of institutions are profitable.
Foreign institutions garner nearly half of institutional profits.
Relative to quantitative methods traditionally used in accounting and finance, textual analysis is substantially less` precise. Thus, understanding the art is of equal importance to understanding the science. In this survey, we describe the nuances of the method and, as users of textual analysis, some of the tripwires in implementation. We also review the contemporary textual analysis literature and highlight areas of future research. © 2016 University of Chicago on behalf of the Accounting Research Center
We provide a model in which a single psychological constraint, limited attention, explains both under- and overreaction to
different earnings components. Investor neglect of earnings induces post-earnings announcement drift and the profit anomaly.
Neglect of earnings components causes accrual and cash flow anomalies. The model offers empirical implications relating the
strength of earnings-related anomalies to the forecasting power of current earnings-related information for future earnings,
investor attentiveness, and the volatilities of and correlation between accruals and cash flows. We also show that, owing
to attention costs, in equilibrium not all investors choose to attend to earnings or its components.
I use uniquely comprehensive data on financial news events to test four predictions from an asymmetric information model of a firm's stock price. Certain investors trade on information before it becomes public; then, public news levels the playing field for other investors, increasing their willingness to accommodate a persistent liquidity shock. Empirically, I measure public information using firms' stock returns on news days in the Dow Jones archive. I find four patterns in postnews returns and trading volume that are consistent with the asymmetric information model's predictions. Some evidence is, moreover, inconsistent with alternative theories in which traders interpret news differently for rational or behavioral reasons.
When local media report news about local companies, they use fewer negative words compared to the same media reporting about nonlocal companies. We document that one reason for this positive slant is the firms' local media advertising expenditures. Abnormal positive local media slant strongly relates to firm equity values. The effect is stronger for small firms; firms held predominantly by individual investors; and firms with illiquid or highly volatile stock, low analyst following, or high dispersion of analyst forecasts. These findings show that news content varies systematically with the characteristics and conflicts of interest of the source.
This article tests whether stock market investors appropriately distinguish between new and old information about firms. I define the staleness of a news story as its textual similarity to the previous ten stories about the same firm. I find that firms' stock returns respond less to stale news. Even so, a firm's return on the day of stale news negatively predicts its return in the following week. Individual investors trade more aggressively on news when news is stale. The subsequent return reversal is significantly larger in stocks with above-average individual investor trading activity. These results are consistent with the idea that individual investors overreact to stale information, leading to temporary movements in firms' stock prices.
This paper investigates whether stock prices reflect information about future earnings contained in the accrual and cash flow components of current earnings. The extent to which current earnings performance persists into the future is shown to depend on the relative magnitudes of the cash and accrual components of current earnings. However, stock prices are found to act as if investors "fixate" on earnings, failing to reflect fully information contained in the accrual and cash flow components of current earnings until that information impacts future earnings.
This study evaluates alternative measures of the tone of financial narrative. We present evidence that word-frequency tone measures based on domain-specific wordlists-compared to general wordlists-better predict the market reaction to earnings announcements, have greater statistical power in short-window event studies, and exhibit more economically consistent post-announcement drift. Further, inverse document frequency weighting, advocated in Loughran and McDonald (2011), provides little improvement to the alternative approach of equal weighting. We also provide evidence that word-frequency tone measures are as powerful as the Naýve Bayesian machine-learning tone measure from Li (2010) in a regression of future earnings on MD&A tone. Overall, although more complex techniques are potentially advantageous in certain contexts, equal-weighted, domainspecific, word-frequency tone measures are generally just as powerful in the context of financial disclosure and capital markets. Such measures are also more intuitive, easier to implement, and, importantly, far more amenable to replication.
We document systematic evidence of risk effects of disclosures culled from a virtually exhaustive set of sources from the print medium. We content analyze more than 100,000 disclosure reports by management, analysts, and news reporters (i.e., business press) in constructing firm-specific disclosure measures that are quantitative and amenable to replication. We expect credibility and timeliness differences in the disclosures by source, which would translate into differential cost of capital effects. We find that when content analysis indicates favorable disclosures, the firm's risk, as proxied by the cost of capital, stock return volatility, and analyst forecast dispersion, declines significantly. In contrast, unfavorable disclosures are accompanied by significant increases in risk measures. Analysis of disclosures by source-corporations, analysts, and the business press-reveals that negative disclosures from business press sources result in increased cost of capital and return volatility, and favorable reports from business press reduce the cost of capital and return volatility.
A commonly-used platform to assess the tone of business documents in the extant accounting and finance literature is Diction. We argue that Diction is inappropriate for gauging the tone of financial disclosures. About 83% of the Diction optimistic words and 70% of the Diction pessimistic words appearing in a large 10-K sample are likely misclassified. Frequently occurring Diction optimistic words like respect, security, power, and authority will not be considered positive by readers of business documents. Similarly, over 45% of the Diction pessimistic 10-K word-counts are not and no. The Loughran-McDonald (2011) dictionary appears better at capturing tone in business text than Diction.
We analyze the transmission of the 2007 to 2009 financial crisis to 415 country-industry equity portfolios. We use a factor model to predict crisis returns, defining unexplained increases in factor loadings and residual correlations as indicative of contagion. While we find evidence of contagion from the U.S. and the global financial sector, the effects are small. By contrast, there has been substantial contagion from domestic markets to individual domestic portfolios, with its severity inversely related to the quality of countries’ economic fundamentals. This confirms the “wake-up call” hypothesis, with markets focusing more on country-specific characteristics during the crisis.This article is protected by copyright. All rights reserved.
Using data from Finland, this study analyzes the extent to which past returns determine the propensity to buy and sell. It also analyzes whether these differences in past-return-based behavior and differences in investor sophistication drive the performance of various investor types. We find that foreign investors tend to be momentum investors, buying past winning stocks and selling past losers. Domestic investors, particularly households, tend to be contrarians. The distinctions in behavior are consistent across a variety of past-return intervals. The portfolios of foreign investors seem to outperform the portfolios of households, even after controlling for behavior differences.
We set out in this study to examine advantaged investors' order choices by computing gains and losses from executed orders in a pure order-driven stock market, the Taiwan Stock Exchange. We carry out an event study on the profitability of order categories around annual earnings announcements. We use a unique and extremely comprehensive dataset which can accurately classify executed orders by order size and aggressiveness for each investor group. We find that, as a group, individual investors are less informed about imminent corporate earnings announcements and the related value implications. Domestic institutions with better local connections have access to privileged information, resulting in significant trading profits in the pre-event window. Informed domestic institutions tend to employ large-sized orders to take up all of the available liquidity. Although limited in terms of private information, foreign institutions with superior expertise accrue profits by trading conservatively through the use of small- to medium-sized orders and less aggressive prices. Order flows are more serially correlated in the pre-event period, especially medium-sized orders from foreign institutions. The results are robust after controlling for various market condition variables. They also hold to different lengths of pre-event window and in the absence of price impacts.
This paper examines the trading behavior and decomposes the trading performance of foreign, individual and institutional investors as well as proprietary traders in a dynamic emerging stock market, the Stock Exchange of Thailand. Foreign investors follow a positive feedback, momentum strategy and are good short term market timers but have poor security selection performance in poor markets, thus suggesting that they have a macro (market timing) but not a micro (security selection) informational advantage relative to local investors. Institutions and proprietary traders have poor security selection trading performance. Individuals display herding behavior and have fairly good security selection performance, but individual investors appear to compensate proprietary traders for the provision of short term liquidity by proprietary traders, so individuals' security selection gains are canceled out by market timing losses.
We apply computational linguistic text mining (TM) analysis to extract and quantify relevant Chinese financial news in an attempt to further develop the classical early warning models of financial distress. Extending the work of Demers and Vega (2011), we propose a measure of the degree of credit default, referred to in this study as the ‘distress intensity of default-corpus’ (DIDC), and investigate the predictive power of this measure on default probability by incorporating it into the signaling model, along with the classical financial performance variables (the liquidity, debt, activity and profitability ratios). We also apply the ‘naïve probability of the Merton distance to default’ model (Bharath and Shumway, 2008) for our robustness analysis. A logistic regression (LR) model is constructed to better integrate the DIDC and financial performance variables into a more effective early warning signal model, with the incorporation of DIDC into the LR model revealing a significant reduction in Type I errors and an apparent increase in classification accuracy. This provides proof of the effectiveness of the additional information from TM on the financial corpus, whilst also confirming the predictive power of TM on credit default. The major contribution of this study stems from our potential refinement of early warning models of financial distress through the incorporation of information provided by related media reports.
This paper investigates the causal impact of the media in financial markets by exploiting exogenous media blackouts resulting from national newspaper strikes in several countries. Trading volume falls 14% on strike days. Stock volatility is also reduced, especially within the day, during which it falls by 9%. These effects are stronger for small firms. Moreover, the power of lagged stock returns for predicting current returns of small firms vanishes on media strike days, consistent with newspapers propagating news from the previous day. These findings demonstrate that the media influence the stock market by increasing the speed with which information diffuses across investors, and is impounded into stock prices.
This study investigates the impact of foreign investors on the informational efficiency of stock prices in local markets. Using a large sample of Japanese firms over the period 1975 to 2008, we find that prices deviate less from a random walk for stocks with a large change in foreign ownership. This relation is robust to controls for local institutional ownership, stock liquidity, and firm fixed effects. Granger causality tests show that changes in foreign investor trading predict changes in price efficiency in the next period, but not vice versa. Finally, we use a quasi-natural experiment to show that an increase in foreign ownership causes an improvement in price efficiency. Collectively, these results suggest that foreign investors improve price efficiency in local stock markets.
We examine the trading behavior and performance of foreigners, local institutions, and individual investors in the Korean stock market. The key research issue is whether the commonly-documented information disadvantage of foreign investors translates into their underperformance relative to local institutional and individual investors. Our results show the opposite, that the stocks foreigners buy significantly outperform the stocks they sell in terms of both stock returns and operating profitability, leading to the significant outperformance of foreigners’ trading strategies over those of local investors. Our results provide strong evidence that the superior performance of foreigners is attributed to their ability to discern between company stocks with good versus bad, at least short-term, prospects. Our findings on the trading behavior of investors in the Korean market are, in general, consistent with those for other markets documented in the published literature. Foreigners behave like short-term momentum traders pursuing a growth strategy. Local institutions also trade like momentum traders but tend to buy value stocks. In contrast, individual investors trade like contrarians who buy past losers and sell past winners. Our findings show that foreigners prefer large-cap stocks with high dividends. In sharp contrast, individual investors have a strong preference for small-cap, high-leverage, low dividend paying stocks, whereas local institutions tend to buy small-cap, low leveraged stocks.
This paper examines the market pricing of Jones (1991) model-estimated abnormal accruals (often termed "discretionary accruals" in the prior literature) to test whether stock prices rationally reflect the one-year-ahead earnings implications of these accruals. Using the Mishkin (1983) and hedge-portfolio test methods Sloan (1996) employs, I find that the market overestimates the persistence, or one-year-ahead earnings implications, of abnormal accruals, and consequently overprices these accruals. These results extend Subramanyam (1996) by demonstrating that the market not only prices, but also overprices abnormal accruals. They also suggest that the overpricing of total accruals that Sloan (1996) documents is due largely to abnormal accruals. The results are robust to five alternative measures of abnormal accruals, and still hold when I estimate abnormal accruals after controlling for major unusual but largely nondiscretionary accruals. The latter finding is consistent with the notion that the market overprices the portion of abnormal accruals stemming from managerial discretion.
Earnings press releases are an important means by which many firms communicate to investors. This study examines whether investors are influenced by how earnings press releases are written - the tone and other stylistic attributes - using actual earnings press releases and archival capital markets data in a standard short-window event study. To measure the tone and other stylistic aspects of press releases, I use elementary computer-based content analysis. Tone is measured using a frequency count of positive or negative words. Other stylistic aspects are the overall length of the press release, the overall percentage of numbers versus words, and the complexity of the words used. Results suggest that tone of earnings press releases influences investors' reactions to earnings. An explanation for this result is provided by prospect theory (Tversky and Kahneman, 1981, 1986), which predicts that framing financial performance in positive terms, will cause investors to think about the results in terms of increases relative to reference points. Limited evidence is presented that other stylistic attributes of earnings press releases affect investors' reactions to earnings.
The recent increase in large scale textual analysis along with the SEC’s plain English initiative makes it important to identify a proxy for measuring readability in financial disclosures. Using a large sample of 10 K filings during 1994–2011 we show that of the two components comprising the most commonly applied readability measure — the Fog Index — one is difficult to implement and the other is misspecified. Using post-filing date return volatility, standardized unexpected earnings, and analyst dispersion to measure the information environment, we find that 10-K document file size provides a simple proxy for readability that outperforms the Fog Index, does not require any parsing of the document, facilitates replication, and is broadly correlated with alternative readability constructs.
We offer here the psychological attraction approach to accounting and disclosure rules, regulation, and policy as a program for positive accounting research. We suggest that psychological forces have shaped and continue to shape rules and policies in two different ways. (1) Good Rules for Bad Users: rules and policies that provide information in a form that is useful for users who are subject to bias and cognitive processing constraints. (2) Bad Rules: superfluous or even pernicious rules and policies that result from psychological bias on the part of the 'designers' (managers, users, auditors, regulators, politicians, or voters). We offer some initial ideas about psychological sources of the use of historical costs, conservatism, aggregation, and a focus on downside outcomes in risk disclosures. We also suggest that psychological forces cause informal shifts in reporting and disclosure regulation and policy, which can exacerbate boom/bust patterns in financial markets.
This paper investigates a unique dataset that enables us to determine the aggregate buy and sell volume of individual investors for a large cross-section of NYSE stocks. We find that individuals trade as if they are contrarians, and that the stocks that individuals buy exhibit positive excess returns in the following month. These patterns are consistent with the idea that risk-averse individuals provide liquidity to meet institutional demand for immediacy. We further examine the relation between individual investor sentiment and short-horizon (weekly) return reversals that have been documented in the literature. Our results reveal that individual investor sentiment predicts future returns, and that the information content of investor sentiment is distinct from that of past returns or past volume. Furthermore, the trading of individuals predicts weekly returns in the post-2000 era for stocks of all sizes, while past return seems to have lost its predictive power for all but small stocks over the same time period. Lastly, we note that there is very little cross-sectional correlation of our individual sentiment measure across the stocks in our sample.
Using transaction data from Indonesia, this paper shows that domestic investors have higher profits than foreign investors. In addition, clients of global brokerages have higher long-term and smaller medium (intramonth) and short (intraday) term profits than clients of local brokerages. This suggests that clients of local brokerages have a short-lived information advantage, but that clients of global brokerages are better at picking long-term winners. Finally, domestic clients of global brokerages have higher profits than foreign clients of global brokerages, suggesting that the combination of local information and global expertise leads to higher profits.
Previous research uses negative word counts to measure the tone of a text. We show that word lists developed for other disciplines misclassify common words in financial text. In a large sample of 10-Ks during 1994 to 2008, almost three-fourths of the words identified as negative by the widely used Harvard Dictionary are words typically not considered negative in financial contexts. We develop an alternative negative word list, along with five other word lists, that better reflect tone in financial text. We link the word lists to 10-K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings.
This paper documents evidence consistent with informed trading by individual investors around earnings announcements using a unique dataset of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose the abnormal returns into a component that is attributed to risk-averse liquidity provision and a component that is attributed to private information or skill, and show that about half of the abnormal returns in the three months following the event can be attributed to private information. We also examine the behavior of individuals after the earnings announcement and find that they trade in the opposite direction to both pre-event returns (i.e., exhibit “contrarian” behavior) and the earnings surprise (i.e., exhibit “news-contrarian” behavior). The latter behavior, which could be consistent with profit-taking, has the potential to slow down the adjustment of prices to earnings news and contribute to the post-earnings announcement drift.
By reaching a broad population of investors, mass media can alleviate informational frictions and affect security pricing even if it does not supply genuine news. We investigate this hypothesis by studying the cross-sectional relation between media coverage and expected stock returns. We find that stocks with no media coverage earn higher returns than stocks with high media coverage even after controlling for well-known risk factors. These results are more pronounced among small stocks and stocks with high individual ownership, low analyst following, and high idiosyncratic volatility. Our findings suggest that the breadth of information dissemination affects stock returns. Copyright (c) 2009 the American Finance Association.
This study examines the relation between ownership structure, as revealed by the percentage of outstanding shares held by institutional investors, and trading volume at earnings announcement dates. We find that volume response as a function of institutional ownership is quadratic with the quadratic curve that reaches a maximum at around 50% institutional ownership. When risk tolerances are identical across investor types such a relation is consistent with Kim and Verrecchia's (1991a) proposition that trading volume response to public announcements increases with the level of cross-investor variation in precision of private predisclosure information.
We test the implications of a multi-asset equilibrium model in which a finite number of risk-averse liquidity providers accommodate non-informational trading imbalances. These imbalances generate predictable reversals in stock returns. An imbalance in one stock also affects the prices of other stocks. The magnitude of the cross-stock price pressure depends on the correlations of the stocks’ underlying cash flows. The model implies that non-informational trading increases the volatility of stock returns. We confirm the model's implications using data from the Taiwan Stock Exchange.
Stocks in the Shanghai market that hit upper price limits typically exhibit three characteristics: high returns, high volumes, and news coverage. We show that these price limit events attract investors' attention. Attention-grabbing events lead active individual investors to buy stocks they have not previously owned. Consistent with lowering investor search costs, events that affect a few (many) stocks lead to increased (decreased) buying. Upper price limit events coincide with initial price increases followed by statistically significant price mean reversion over the following week. Rational traders (statistical arbitrageurs) profit in response to attention-based buying. Smart traders accumulate shares on date t, sell shares on date t + 1, and earn a daily average profit of 1.16%. We show the amount they invest predicts the degree of attention-based buying by individual investors. We end by decomposing individual investor trades in order to estimate losses attributable to behavioral biases.
Instrumental variable (IV) methods are commonly used in accounting research (e.g., earnings management, corporate governance, executive compensation, and disclosure research) when the regressor variables are endogenous. While IV estimation is the standard textbook solution to mitigating endogeneity problems, the appropriateness of IV methods in typical accounting research settings is not obvious. Drawing on recent advances in statistics and econometrics, we identify conditions under which IV methods are preferred to OLS estimates and propose a series of tests for research studies employing IV methods. We illustrate these ideas by examining the relation between corporate disclosure and the cost of capital.
This paper investigates the impact of salient political and economic news on the intraday trading activity, namely, the stock return volatility, the stock price volatility, the number of shares traded, and the trading frequency. Using transactions data on 33 constituent stocks of the Hang Seng Index in the Stock Exchange of Hong Kong (SEHK), we find that political news has a distinct impact on market activity when compared with economic news. We argue that the observed phenomenon is related to the precision of signals associated with these two types of news and investors' perceptual biases.
I review empirical research on the relation between capital markets and financial statements. The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the political process. The capital markets research topics of current interest to researchers include tests of market efficiency with respect to accounting information, fundamental analysis, and value relevance of financial reporting. Evidence from research on these topics is likely to be helpful in capital market investment decisions, accounting standard setting, and corporate financial disclosure decisions.
This paper identifies five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors, related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates, the bond-market factors capture the common variation in bond returns. Most important, the five factors seem to explain average returns on stocks and bonds.
This paper uses recent experimental studies of financial accounting to illustrate our view of how such experiments can be conducted successfully. Rather than provide an exhaustive review of the literature, we focus on how particular examples illustrate successful use of experiments to determine how, when and (ultimately) why important features of financial accounting settings influence behavior. We first describe how changes in views of market efficiency, reliance on the experimentalist’s comparative advantage, new theories, and a focus on key institutional features have allowed researchers to overcome the criticisms of earlier financial accounting experiments. We then describe how specific streams of experimental financial accounting research have addressed questions about financial communication between managers, auditors, information intermediaries, and investors, and indicate how future research can extend those streams. We focus particularly on (1) how managers and auditors report information; (2) how users of financial information interpret those reports; (3) how individual decisions affect market behavior; and (4) how strategic interactions between information reporters and users can affect market outcomes. Our examples include and integrate experiments that fall into both the “behavioral” and “experimental economics” literatures in accounting. Finally, we discuss how experiments can be designed to be both effective and efficient.
This study investigates the trading behavior of institutional and individual investors around both firm-specific news releases in the Wall Street Journal and macro-economic announcements. For the firm-specific news releases we find that investors conduct a high degree of trading around news releases, especially earnings and dividend news. Institutions buy and sell on both good and bad news, while individual investors only trade on good news. The length of the news article (visibility) is also an important attribute to motivate individual investor trading. Lastly, both institutions and individuals buy large firms after good economic news and sell large firms after bad economic news. The trading of small firms does not appear to be motivated by macro-news.
ABSTRACT This paper investigates whether the business press serves as an information intermediary. The press potentially shapes firms' information environments by packaging and disseminating information, as well as by creating new information through journalism activities. We find that greater press coverage reduces information asymmetry (i.e., lower spreads and greater depth) around earnings announcements, with broad dissemination of information having a bigger impact than the quantity or quality of press-generated information. These results are robust to controlling for firm-initiated disclosures, market reactions to the announcement, and other information intermediaries. Our findings suggest that the press helps reduce information problems around earnings announcements. Copyright (c), University of Chicago on behalf of the Accounting Research Center, 2009.
Bibliography: leaves 53-56. Robert C. Merton.
Psychological evidence indicates that it is hard to process multiple stimuli and perform multiple tasks at the same time. This paper tests the INVESTOR DISTRACTION HYPOTHESIS, which holds that the arrival of extraneous news causes trading and market prices to react sluggishly to relevant news about a firm. Our test focuses on the competition for investor attention between a firm's earnings announcements and the earnings announcements of other firms. We find that the immediate stock price and volume reaction to a firm's earnings surprise is weaker, and post-earnings announcement drift is stronger, when a greater number of earnings announcements by other firms are made on the same day. Distracting news has a stronger effect on firms that receive positive than negative earnings surprises. Industry-unrelated news has a stronger distracting effect than related news. A trading strategy that exploits post-earnings announcement drift is unprofitable for announcements made on days with little competing news.
Foreign investors generally underperform domestic investors in trading activities. This study shows that their inferior performance is attributable to non-initiated orders. Foreign investors actually perform better than domestic investors in initiated orders. In addition, their performance is also mixed when trades are classified depending on who the counterparties are. These mixed performances can be explained by neither the information disadvantage hypothesis proposed by [Dvorák, T., 2005. Do domestic investors have an information advantage? Evidence from Indonesia. Journal of Finance 60, 817-839.] nor the poor timing of trade hypothesis suggested by [Choe, H., Kho, B.C., Stulz, R., 2005. Do domestic investors have an edge? The trading experience of foreign investors in Korea. Review of Financial Studies 18, 795-829.]. We propose and confirm that their inferior performance is explained by their aggressive trading behavior. Three metrics we utilize to measure the aggressiveness of foreign investors' trading provide overwhelmingly strong evidence that foreign investors are more aggressive than their domestic counterparts.
We propose a theory based on investor overconfidence and biased self- attribution to explain several of the securities returns patterns that seem anomalous from the perspective of efficient markets with rational investors. The theory is based on two premises derived from evidence in psychological studies. The first is that individuals are overconfident about their ability to evaluate securities, in the sense that they overestimate the precision of their private information signals. The second is that investors' confidence changes in a biased fashion as a function of their decision outcomes. The first premise implies overreaction to private information arrival and underreaction to public information arrival. This is consistent with (1) post-corporate event and post-earnings announcement stock price 'drift', (2) negative long- lag autocorrelations (long-run 'overreaction'), and (3) excess volatility of asset prices. Adding the second premise leads to (4) positive short-lag autocorrelations ('momentum'), and (5) short-run post-earnings announcement 'drift,' and negative correlation between future stock returns and long-term measures of past accounting performance. The model also offers several untested empirical implications and implications for corporate financial policy.
We test and confirm the hypothesis that individual investors are net buyers of attention-grabbing stocks, e.g., stocks in the news, stocks experiencing high abnormal trading volume, and stocks with extreme one-day returns. Attention-driven buying results from the difficulty that investors have searching the thousands of stocks they can potentially buy. Individual investors do not face the same search problem when selling because they tend to sell only stocks they already own. We hypothesize that many investors consider purchasing only stocks that have first caught their attention. Thus, preferences determine choices after attention has determined the choice set.
We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm-specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard-to-quantify aspects of firms' fundamentals, which investors quickly incorporate into stock prices. Copyright (c) 2008 by The American Finance Association.