Corporate media connections and merger outcomes

We examine the relation between acquirer social ties with the media and merger outcomes. We find that, consistent with the media management hypothesis, media connectedness is associated with the higher bid announcement return, lower takeover premium, poorer post-merger operating performance, greater likelihood of deal closure, and greater acquisitiveness. The association between media connections and merger announcement returns is more pronounced for stock deals. Examining the underlying channel, we show that the media networks are positively related to acquirers' media coverage and sentiment of the news articles during the pre-bid announcement period. Our findings are robust to alternative variable measurement as well as tests for endogeneity.     

Which sentiment index is more informative to forecast stock market volatility? Evidence from China

In this paper, we investigate the predictive ability of three sentiment indices constructed by social media, newspaper, and Internet media news to forecast the realized volatility (RV) of SSEC from in- and out-of-sample perspectives. Our research is based on the heterogeneous autoregressive (HAR) framework. There are several notable findings. First, the in-sample estimation results suggest that the daily social media and Internet media news sentiment indices have significant impact for stock market volatility, while the sentiment index built by traditional newspaper have no impact. Second, the one-day-ahead out-of-sample forecasting results indicate that the two sentiment indices constructed by social media and Internet media news can considerably improve forecast accuracy. In addition, the model incorporating the positive and negative social media sentiment indices exhibits more superior forecasting performance. Third, we find only the sentiment index built by Internet media news can improve the mid- and long-run volatility predictive accuracy. Fourth, the empirical results based on alternative prediction periods and alternative volatility estimator confirm our conclusions are robust. Finally, we examine the predictability of the monthly sentiment indices and find that the two sentiment indices of social media and Internet media news contain more informative to forecast the monthly RV of SSEC, CSI800, and SZCI, however invalid for CSI300.     

Earnings Announcement Lags and Market Responses—Does the Tone of the News and the Market Sentiment Matter?

We investigate earnings announcement lags (period from the end of the reporting period until the announcement date) for the good and the bad quarterly earnings news across different market sentiment periods as well as market reactions thereto. Companies listed on Baltic stock exchanges exhibit clear signs of strategic timing of earnings announcements. Earnings announcement lags for the bad news tend to be longer than those for the good news. This difference is more pronounced during low market sentiment periods. If the release of the bad news is postponed, abnormal return responses remain lower, as expected.     

Trade the tweet: Social media text mining and sparse matrix factorization for stock market prediction

We investigate the potential use of textual information from user-generated microblogs to predict the stock market. Utilizing the latent space model proposed by Wong et al. (2014), we correlate the movements of both stock prices and social media content. This study differs from models in prior studies in two significant ways: (1) it leverages market information contained in high-volume social media data rather than news articles and (2) it does not evaluate sentiment. We test this model on data spanning from 2011 to 2015 on a majority of stocks listed in the S&P 500 Index and find that our model outperforms a baseline regression. We conclude by providing a trading strategy that produces an attractive annual return and Sharpe ratio.     

Dispersion in news sentiment and corporate bond returns

We construct a news sentiment index at the firm level by using textual analysis of news articles and find that dispersion in news sentiment is a significant predictor of corporate bond returns. Bonds of firms with high dispersion in news sentiment have a highly significant average return of 7.38 percent. A portfolio that longs bonds with high dispersion in news sentiments and shorts bonds with low dispersion earns an average biweekly return of 8.53 percent. This finding is in line with an argument that dispersion in news sentiment is a proxy for future cash flow uncertainty.     

Sentiment stocks

To study how investor sentiment at the firm level affects stock returns, we match more than 58 million social media messages in China with listed firms and construct a measure of individual stock sentiment based on the tone of those messages. We document that positive investor sentiment predicts higher stock risk-adjusted returns in the very short term followed by price reversals. This association between stock sentiment and stock returns is not explained by observable stock characteristics, unobservable time-invariant characteristics, market-wide sentiment, overreaction to news, or changing investor attention. Consistent with theories of investor sentiment, we find that the link between sentiment and stock returns is mainly driven by positive sentiment and non-professional investors. Finally, exploiting a unique feature of the Chinese stock market, we are able to isolate the causal effect of sentiment on stock returns from confounding factors.     

Technical analysis: Novel insights on contrarian trading

We analyze the predictive power of technical analysis with a novel data set based on news sentiment that allows to systematically examine a set of technical analysis indicators over an extensive time period. We do not find much statistically significant relationships with the examined indicators and future asset returns, and we almost do not find any alphas in trading strategies based on technical analysis sentiment. We find evidence for a contrarian-based hypothesis: past market returns and technical analysis sentiment are able to predict future technical analysis sentiment with a negative relationship.     

Intraday online investor sentiment and return patterns in the U.S. stock market

We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.     

Media coverage and investment efficiency

We examine the effect of media coverage on firm-level investment efficiency. We find that media coverage reduces under-investment but increases over-investment. The negative effect of media coverage on under-investment is more pronounced in firms affected by greater information asymmetry and poorer corporate governance. The positive effect of media coverage on over-investment is driven by media-induced CEO overconfidence. Additional results show that both investment- and non-investment-related news coverage decrease under-investment, while non-investment-related news coverage is more influential in increasing over-investment. In general, higher news optimism is associated with less under-investment but more over-investment. Moreover, media coverage affects investment efficiency through its information dissemination rather than information creation function. Collectively, our results suggest that firms’ media visibility promotes more over-investment than under-investment.     

US macroeconomic news effects around the US and European financial crises: Evidence from Brazilian and Mexican equity indices

We examine the intraday index return and volatility responses of two Latin American equity markets to US macroeconomic news releases around the periods of the US and European financial crises. We find that while index return is more sensitive than volatility to macroeconomic news in general, the five-minute Brazilian and Mexican index volatilities respond especially strongly to US news surprises, with the Brazilian response being more pronounced, especially during the expansion period. Among the macroeconomic indicators tested, FOMC rate decisions exhibit the highest impact on volatility, and there is evidence of asymmetric response to positive versus negative news.     

Time-variation in the impact of news sentiment

Utilizing firm-specific news sentiment data provided by Thomson Reuters News Analytics, I construct aggregate measures to examine the relationship between news sentiment and stock market returns over the period 2004–2010. I find a highly significant relationship between aggregated measures of news sentiment and stock returns that fluctuates over time and by industry. I identify a link between the time-variation of news sentiment impact and industry beta, and determine that levels of investor sentiment (proxied by VIX) play an important role in explaining this variation.     

Market Response to Investor Sentiment

This paper reconsiders the effect of investor sentiment on stock prices. Our main contribution is that, in addition to the intermediate term return predictability, we also analyze the immediate price reaction to the publication of survey‐based investor sentiment indicators. We find that the sign of the immediate market response is the same as that of the predictability at intermediate time horizons. This is consistent with underreaction to cash flow news or with investor sentiment being related to mispricing. It is inconsistent with the alternative explanations of a rational response to cash flow news or sentiment indicators providing information about future expected returns.     

The Governance Effect of the Media's News Dissemination Role: Evidence from Insider Trading

We investigate whether the media plays a role in corporate governance by disseminating news. Using a comprehensive data set of corporate and insider news coverage for the 2001–2012 period, we show that the media reduces insiders’ future trading profits by disseminating news on prior insiders’ trades available from regulatory filings. We find support for three economic mechanisms underlying the disciplining effect of news dissemination: the reduction of information asymmetry, concerns regarding litigation risk, and the impact on insiders’ personal wealth and reputation. Our findings provide new insights into the real effect of news dissemination.     

Revisiting the ICAPM under the distortion of risk–return tradeoff in short-horizon stock returns

We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.     

Does it really pay off for investors to consider information from social media?

This paper raises the question whether investors can learn something from social media sentiment that they do not already know from (existing) financial information disclosed by companies and financial analysts. Therefore, the relationship between financial information and Refinitiv’s MarketPsych social media sentiment index is explored. The paper introduces adjusted social media sentiment, which corrects social media sentiment for the impact of financial information such as earnings surprises, analyst forecast revisions, new dividends, and 8-K filings. It turns out that adjusted social media sentiment is related to subsequent short-term stock returns. This is particularly true for stocks with negative (adjusted) sentiment. Moreover, looking at long-term holding returns the paper does not find compelling evidence for reversals suggesting that (adjusted) social media sentiment reflects information about the prospects of the firm.     

The tone of financial news and the perceptions of stock and CDS traders

This paper applies novel sentiment analyses to Reuters news to study stock and CDS traders' differential interpretations of financial news. We construct sentiment measures to identify which news content influences investors' behavior and create dynamic word lists that reflect the divergent viewpoints of CDS and equity investors. We find that (1) equity and CDS traders focus on different content within the same news; (2) traders particularly disagree with respect to news concerning debt topics, especially regarding M&A activity; (3) the Great Recession impacted debt news content and altered the typical inverse relationship between equity and CDS markets on news days.     

When is a MAX not the MAX? How news resolves information uncertainty

A well-known asset pricing anomaly, the “MAX” effect, measured by the maximum daily return in the past month, depicts stocks’ lottery-like features and investor gambling behaviour. Using the comprehensive stock-level Dow Jones (DJNS) news database between 1979 and 2016, we consider in a empirical setting how the presence of news reports affects these lottery-type stocks. We find an augmented negative relationship between MAX stocks without news and expected returns, whereby MAX with news coverage generates return momentum. The differing future return relationships between MAX stocks with and without news appears to be best explained by information uncertainty mitigation upon news arrival. Overall, our findings suggest that news plays a role in resolving information uncertainty in the stock market.     

Fundamental strength and short-term return reversal

We document that the fundamental strength (FSCORE) of a firm exerts a significant influence on the performance of short-term reversal strategies. Past losers with strong fundamentals significantly outperform past winners with weak fundamentals. Our FSCORE approach is complementary to Da et al. (2014) cash flow news metrics based on analysts’ forecast revisions in that many firms do not have analyst following. Our approach also seems capable of capturing the lagged effects from past fundamental news shocks. After controlling for fundamental strength, we find that investor sentiment plays a more dominant role than do liquidity shocks in explaining return reversal.     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

Repairing damaged reputations through targeted poverty alleviation: Evidence from private companies’ strategies to deal with negative media coverage

When negative media coverage causes reputational crises, companies must find suitable tools to repair their reputation and reverse their negative image. As a CSR activity with political- and livelihood-related implications, targeted poverty alleviation may be an effective tool. Using data on negative media coverage of Chinese A-share private listed companies, we examine whether companies engage in targeted poverty alleviation in response to reputational crises caused by negative media coverage. We find that negative media coverage leads private companies to engage more actively and intensively in targeted poverty alleviation because of the significant increase in public attention to the bad news. These companies must urgently rebuild their positive image using targeted poverty alleviation to resolve their public opinion crisis. Further analyses suggest that original and in-depth negative media coverage is more likely to cause companies’ active participation in targeted poverty alleviation. In addition, negative media coverage is more likely to lead companies to engage in targeted poverty alleviation when they are in heavily polluting industries or face greater pressure from external investors. Finally, we find that active involvement in targeted poverty alleviation helps companies improve their market reputation and thus effectively manage public relations crises caused by negative media coverage.