An encyclopedia for stock markets? Wikipedia searches and stock returns

We present empirical evidence that collective investor behavior can be inferred from large-scale Wikipedia search data for individual-level stocks. Drawing upon Shannon transfer entropy, a model-free measure that considers any kind of statistical dependence between two time series, we quantify the statistical information flow between daily company-specific Wikipedia searches and stock returns for a sample of 447 stocks from 2008 to 2017. The resulting stock-wise measures on information transmission are then used as a signal within a hypothetical trading strategy. The results evidence the predictive power of Wikipedia searches and are in line with the previously documented notion of buying pressure revealed by online investor attention and the trading patterns of retail investors.     

Predicting Stock Returns Using Financial Statement Information

We examine the profitability of the Ou and Penman (1989a) Pr trading strategy and the Holthausen and Larcker (1992) Prob trading strategy over the period 1980–1992 in the UK. This is a test of whether an investor can earn abnormal returns by exploiting fundamental accounting data. We employ alternative abnormal return metrics and research designs to control for risk. Using a UK dataset offers an independent test because the UK differs from the US in its formal and informal financial reporting environment, its structure of share ownership, and the behaviour of its economy over the study period. We find consistent evidence that an investor could have used a summary measure of financial statement information to predict future abnormal returns by indirectly predicting one-year-ahead earnings changes, but only weak and inconsistent evidence that an investor could have used a summary measure of financial statement information to predict one-year-ahead stock returns directly. We offer some thoughts on the reasons for these different results.     

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.     

Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

Communication and Comovement: Evidence from Online Stock Forums

We study investor communication and stock comovement using a novel data set from an active online stock forum in China. We find substantial comovement among the returns of a stock and its “related stocks,” which are frequently discussed in the subforum dedicated to the given stock. Comovement is greater when the discussion of related stocks is more intensive. Further, the effect of communication on comovement is stronger for stocks associated with higher information uncertainty. Codiscussed stocks are more actively traded and experience more correlated trading. A trading strategy that exploits communication‐driven comovement generates abnormal returns. Our findings highlight the impact of investor communication on asset comovement.     

Option trading and individual investor performance

This paper examines the impact of option trading on individual investor performance. The results show that most investors incur substantial losses on their option investments, which are much larger than the losses from equity trading. We attribute the detrimental impact of option trading on investor performance to poor market timing that results from overreaction to past stock market returns. High trading costs further contribute to the poor returns on option investments. Gambling and entertainment appear to be the most important motivations for trading options while hedging motives only play a minor role. We also provide strong evidence of performance persistence among option traders.     

Twitter activity,investor attention,and the diffusion of information

We examine the impact of Twitter attention on stock prices by examining over 21 million company‐specific tweets over a 5‐year period. Through a quasi‐natural experiment identifying official Twitter outages, we find that Twitter influences stock trading, especially among small, less visible securities primarily traded by retail investors. In addition, we determine that Twitter activity is associated with positive abnormal returns and when tweets occur in conjunction with traditional news events, more information is spread to investors. Finally, we show that retail investor activity drives the Twitter effect as institutional investors less actively trade the affected stocks.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

The Effects of Stock Characteristics on the Direction and Extent of Herding by Foreign Institutional Investors in the Taiwan Stock Exchange

We use a dynamic herding measure to explore the causes of foreign institutional investor (FII) herding in the Taiwan stock market and examine the effects of stock characteristics on the direction and extent of such herding. We find that FII herding primarily results from cascades rather than habit investing or momentum trading. The result of a panel smooth transition regression shows that FIIs' negative cascades focus on their largest net purchases of stocks, but FIIs' positive cascades focus on winner and small-sized stocks. To increase portfolio returns, investors can use FIIs' cascades to inform their stock purchases.     

投资者关注度与股票市场——以PM2.5概念股为例

近年来雾霾成为中国社会的热点话题,而雾霾频发导致PM2.5概念股受到投资者广泛的关注。本文结合现实环境问题,研究投资者通过对环境的关注度继而对与环境相关的股票的影响。具体而言,本文探究投资者对雾霾和PM2.5概念股的关注度对PM2.5概念股的影响。分析发现投资者对雾霾和PM2.5概念股的关注度的增加能拉升PM2.5概念股的股价。投资者对雾霾的关注度和PM2.5概念股的收益率显著正相关。关注度的增加同时也提高PM2.5概念股交易的活跃程度以及PM2.5概念股涨停的可能性。此外,本文发现正面的新闻报道会拉升PM2.5概念股的股价而负面的新闻报道会降低其股价。最后,本文通过讨论内生性和异质性等一系列稳健性检验进一步验证上述结论。     

Extreme dependence in investor attention and stock returns – consequences for forecasting stock returns and measuring systemic risk

We characterize co-movements in investor attention by modeling multivariate internet search volume data. Using a variety of copula models that can capture both asymmetric and skewed dependence, we find empirical evidence of strong non-linear and asymmetric dependence in the attention investors give to companies. Modeling three years of daily stock returns and search volumes from Google Trends for 29 bank names, we find a striking similarity between the dependence structure inherent in stock returns and the dependence in the corresponding time series of search queries. We then document the existence of significant asymmetric and skewed tail dependence in the joint distribution of stock returns and investor attention. Finally, stock returns and internet search volumes appear to evolve concurrently in real time with neither one leading the other. Our findings have important implications, e.g. for the analysis of banks' interconnectedness based on equity data and the pricing of investor attention in the cross-section of stock returns.     

Investor Inattention and Friday Earnings Announcements

Does limited attention among investors affect stock returns? We compare the response to earnings announcements on Friday, when investor inattention is more likely, to the response on other weekdays. If inattention influences stock prices, we should observe less immediate response and more drift for Friday announcements. Indeed, Friday announcements have a 15% lower immediate response and a 70% higher delayed response. A portfolio investing in differential Friday drift earns substantial abnormal returns. In addition, trading volume is 8% lower around Friday announcements. These findings support explanations of post‐earnings announcement drift based on underreaction to information caused by limited attention.     

Economic and financial crises and the predictability of U.S. stock returns

We argue that the use of publicly available and easily accessible information on economic and financial crises to detect structural breaks in the link between stock returns and macroeconomic predictor variables improves the performance of simple trading rules in real time. In particular, our results suggest that accounting for structural breaks and regime shifts in forecasting regressions caused by economic and financial crises has the potential to increase the out-of-sample predictability of stock returns, the performance of simple trading rules, and the market-timing ability of an investor trading in the U.S. stock market.     

The Pitch Rather Than the Pit: Investor Inattention,Trading Activity,and FIFA World Cup Matches

This paper analyzes stock market trading in 15 countries during the 2010 and 2014 soccer FIFA World Cups. We find evidence for substantial investor inattention during these major sporting events. The lack of attention for the trading pit is particularly large when the national soccer team is competing, with traded volumes declining by as much as 48%. During national team matches, prices on local stock markets can temporarily decouple from global financial market developments. These findings suggest that major sporting events can act as a laboratory in which to investigate investor inattention.     

Glamour among value: P/E ratios and value investor attention

The trailing-four-quarter price–earnings (P/E) ratio is the most popular fundamental value proxy. This article is the first to examine the P/E ratio as the preeminent measure of value investor attention. Trailing-four-quarter P/E ratios predict significantly greater cross-sectional variation in stock returns than lagged P/E ratios or current price-to-book (P/B) ratios. P/E strategy returns are robust to variables that proxy for fundamental risk, variables mechanically related to P/E ratios, relative trading volume, and liquidity. The role of attention is evident in return patterns across long and short portfolios, day of the week, and time since formation. Stocks with low P/E ratios exhibit an increase in total trading volume driven by small trades, an improvement in liquidity, and lower idiosyncratic volatility. These patterns are consistent with the typical trading activity of individual investors, who have the strongest attention constraints.     

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.     

Volume autocorrelation,information, and investor trading

This study investigates whether the widely documented daily correlated trading volume of stocks is driven by individual investor trading, institutional trading, or both. We find that at least 95% of NYSE and AMEX stocks exhibit statistically significant, positive serial correlation. Volume autocorrelation decreases with the level of institutional ownership of a stock. We also show that the rate of arrivals of new information to the market contributes to the clustering of trades. When there is high information flow to the market, institutional trading generates a more pronounced effect on volume autocorrelation than individual investor trading. Our results are broadly consistent with the predictions of trading volume patterns suggested by most theoretical models of stock trading and by empirical research on investor trading.     

Noise trading and stock market volatility

We investigate the relative effects of fundamental and noise trading on the formation of conditional volatility. We find significant positive (negative) effects of investor sentiments on stock returns (volatilities) for both individual and institutional investors. There are greater positive effects of rational sentiments on stock returns than irrational sentiments. Conversely, there are significant (insignificant) negative effects of irrational (rational) sentiments on volatility. Also, we find asymmetric (symmetric) spillover effects of irrational (rational) bullish and bearish sentiments on the stock market. Evidence in favor of irrational sentiments is consistent with the view that investor error is a significant determinant of stock volatilities.     

投资者关注与市场反应——来自中国证券交易所交易公开信息的自然实验

涨停的股票能否被交易公开信息披露取决于收益率排名中的随机因素,与股票的基本面特征无关。本文利用这一机制设计自然实验检验了投资者关注对股价的影响。实证结果显示交易公开信息披露使股票受到投资者更多的关注,增加了小额资金的净流入,减少了大额资金的净流入和股价的短期收益率,抑制了股价短期波动率,同时降低了股价在长期发生反转的可能性。频繁登上交易公开信息的知名营业部买入的股票受到更多关注,相应的市场反应也更加显著。进一步的研究表明监管性信息披露引发的投资者关注通过降低市场信息不对称抑制了股价反转。     

Corporate misconduct,media coverage,and stock returns

This study examines the impact of increased investor attention to corporate misconduct (CM) on stock returns. We show that media coverage provides an important channel through which investor awareness of corporate wrongdoings can be enhanced. Using a unique research setting in Korea based on text analysis during the 2008–2020 period, we find that investors exhibit short-term adverse reactions to CM events. More importantly, the increased social awareness of CM issues through media coverage leads investors to penalize firms more severely. We also find that the adverse reaction to CM events is more prominent for firms with a greater negative media tone and surprise. The combined evidence supports the investor attention theory. Furthermore, the negative effects of CM on stock returns are smaller for firms with positive Corporate Social Responsibility (CSR) and Environmental, Social, and Governance (ESG) reputations, consistent with the insurance theory.