In Search of Attention

We propose a new and direct measure of investor attention using search frequency in Google (Search Volume Index (SVI)). In a sample of Russell 3000 stocks from 2004 to 2008, we find that SVI (1) is correlated with but different from existing proxies of investor attention; (2) captures investor attention in a more timely fashion and (3) likely measures the attention of retail investors. An increase in SVI predicts higher stock prices in the next 2 weeks and an eventual price reversal within the year. It also contributes to the large first‐day return and long‐run underperformance of IPO stocks.     

Retail investors exonerated: the case of the January effect

We dispel the belief that the January effect is due to retail investor trading. Previous studies suggest that retail investors, affected by behavioural biases and disproportionally invested in small capitalization stocks, are the source of the January effect. Furthermore, the literature regards retail investor trading and the tax‐loss selling hypothesis as essentially the same explanation. We separate tax implications and market capitalization to show that retail traders are not the cause of the January effect. Our study is an important direct test of whether retail trading causes market anomalies.     

Investor Sentiment and the Cross-Section of Stock Returns

We study how investor sentiment affects the cross‐section of stock returns. We predict that a wave of investor sentiment has larger effects on securities whose valuations are highly subjective and difficult to arbitrage. Consistent with this prediction, we find that when beginning‐of‐period proxies for sentiment are low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non‐dividend‐paying stocks, extreme growth stocks, and distressed stocks. When sentiment is high, on the other hand, these categories of stock earn relatively low subsequent returns.     

Retail investor information demand – speculating and investing in structured products

We study the impact of retail investor information demand on trading in bank-issued investment and leverage structured products, which are specifically designed for retail investors. Stock-specific information demand positively predicts speculative trading activity. Furthermore, we find a positive relationship between market-wide information demand and order aggressiveness and order uncertainty for speculating and investing activity. Whereas information supply is associated with speculative long positions, information demand does not induce investors to be predominantly long or short. Finally, we do not find retail investor information demand to contribute to an upward price pressure on security prices. In contrast, information supply exerts negative price pressure. Overall, retail investor trading in individual stocks is much more strongly influenced by market-wide information demand instead of firm-specific information demand. This implies a low informational efficiency of retail investor speculation and investing activity.     

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.     

Nasdaq Trading and Trading Costs: 1993–2002

Nasdaq spreads decline from 1993 to 2002, largely independently of tick‐size reductions. Trade size declines, consistent with greater retail investor activity. Using the method of Chordia, Roll, and Subrahmanyam (2001), we find that concurrent market returns strongly affect liquidity and trading activity. Liquidity exhibits distinct day‐of‐the‐week patterns. There is little evidence that macroeconomic announcements or changes in key interest rates affect Nasdaq stocks overall; but in the bear market, we find a relation between some of these variables and effective spreads, which we interpret as consistent with Nasdaq participants' paying greater attention to fundamentals after the market crash.     

Connecting two markets: An equilibrium framework for shorts,longs, and stock loans

We analyze a reduced-form framework for understanding the equity loan market's impact on share prices. We show that hard-to-borrow stocks will have distinct return patterns, responding more to shocks in the supply of shares available, and to changes in the heterogeneity of investor beliefs, than other stocks. We conduct two empirical tests in which we find strong support for these equilibrium predictions. In our first test, we take advantage of a tax-driven exogenous shock to share loan supply and find that when supply is reduced around dividend record dates, prices of hard-to-borrow stocks increase 1.1% while prices of easy-to-borrow stocks are unaffected. In our second test, we find that hard-to-borrow stocks have 4.8% lower three-month returns than other stocks, with negative returns concentrated in stocks with high heterogeneity in investor beliefs. Thus, we extend the Diether, Malloy, and Scherbina (2002) result that stocks with a greater dispersion of investor beliefs have lower returns.     

Are paper winners gamblers? Evidence from Australian retail investors

This study examines stock market gambling using a comprehensive set of investor characteristics and past portfolio performance measures. We find that retail investors overinvest in ‘lottery stocks’, stocks with gambling‐like properties. Significant portfolio underperformance is the result of gambling through lottery stocks. Investors are more likely to gamble following recent portfolio paper gains, regardless of realised performance, providing new evidence that paper gains trigger a house money effect. Investors trading greater values or holding more stocks, and older and female investors, are less likely to invest in lottery stocks.     

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.     

Dumb money: Mutual fund flows and the cross-section of stock returns

We use mutual fund flows as a measure of individual investor sentiment for different stocks, and find that high sentiment predicts low future returns. Fund flows are dumb money–by reallocating across different mutual funds, retail investors reduce their wealth in the long run. This dumb money effect is related to the value effect: high sentiment stocks tend to be growth stocks. High sentiment also is associated with high corporate issuance, interpretable as companies increasing the supply of shares in response to investor demand.     

What's in a “China” Name? A Test of Investor Attention Hypothesis

We study whether a firm's name affects investor attention and firm valuation. Some Chinese firms listed on US stock exchanges have the word “China” included in their company names (“China‐name stocks”), while others do not (“non‐China‐name stocks”). During the 2007 China stock market boom, we find that China‐name stocks significantly outperform non‐China‐name stocks. This is not due to differences in firm characteristics, risk, or liquidity. The “China‐name effect” is largely consistent with the investor attention hypothesis that price pressure caused by increased investor attention on China‐name stocks during the boom period drives up China‐name stocks more than non‐China‐name stocks.     

Speculative trading preferences of retail investor birth cohorts

This study examines the effect of investor birth cohorts on speculative investment preferences. Using retail trading and portfolio data from Finland over two decades, we find that individuals who have experienced desirable macro-economic and social conditions during adolescence, such as high gross domestic product (GDP) growth and low divorce rates, are more likely to invest in speculative stocks. A positive relation is found between the proportion of speculative-prone cohorts in the stock market and returns of stocks of lottery nature. We provide new evidence on the adverse effect of speculative investments, finding that cohorts with higher speculative investment weights on their portfolios achieve lower absolute and risk-adjusted returns. We also provide support for earlier research that identifies a positive association between recent portfolio performance and the propensity to invest in speculative stocks.     

When does attention matter? The effect of investor attention on stock market volatility around news releases

We empirically investigate how retail and institutional investor attention is related to the way stock markets process information. With a focus on 360 US stocks in the S&P 500 universe, our results show that higher retail investors’ attention around news releases increases the post-announcement stock return volatility, whereas institutional investor attention has a small but negative impact on volatility on days following news releases on average over the cross-section of companies. These findings are in line with the hypotheses that attention of retail investors slows price-adjustments to new information and attention of institutional investors results in the opposite reaction. We show that these effects are heterogeneous in the type of news and the topic of the information being released. A portfolio allocation application highlights that these results are not only statistically significant but also sizeable in economic terms and can lead to an overperformance as large as dozens of basis points.     

Does Noninformative Text Affect Investor Behavior?

This article demonstrates that easily processed texts affect investor trading behavior even in the absence of any informational content. We examine the trading symbols of US firms and find that stocks with clever tickers (those that are actual words in the English language) are more liquid, as measured by higher turnover and trading volume, as well as lower spreads. Furthermore, clever ticker stocks are traded more by uninformed investors and have larger market reactions on earnings announcement days. These results suggest that ticker fluency facilitates trading by improving the firm's visibility among retail investors through attention grabbing and memorization.     

Investor attention and global market returns during the COVID-19 crisis

The financial market response to the COVID-19 pandemic provides the first example of a market crash instigated by a health crisis. As such, the crisis provides a unique setting in which to examine the market response to changes in investor attention. We utilise Google search volume (GSV) as a proxy for investor attention. GSV for the “coronavirus” keyword increases markedly from late-February and peaks in mid-March before declining substantially. Our results are broadly consistent with Da, Engelberg, and Gao (2015), indicating that GSV is primarily a proxy for the attention of retail investors and confirming that investor attention negatively influences global stock returns during this crisis period. A rise in the number of internet searches during the COVID-19 crisis induces a faster rate of information flow into financial markets and so is also associated with higher volatility. The identified relationships are economically and statistically significant even after controlling for the number of COVID-19 cases and macroeconomic effects. Increases in GSV have less impact on government bond yields where the limited role of GSV is likely due to lower participation of retail investors. The results suggest that, rather than searching for information on potential stocks to buy (Barber & Odean, 2008), retail investors are searching for information to resolve uncertainty about household FEARS (Da et al., 2015) during the COVID-19 crisis.     

Online Search Frequency,Retail Investor Overreaction,and the Cross-Section of Stock Returns: Evidence from the Chinese Stock Market

I find a strong negative relation between online search frequency and future returns on the Chinese stock market. I suggest that this effect captures retail investor overreaction to unexpected signals, because online search frequency reflects the efforts made by investors to obtain firm-specific knowledge. The effect is particularly strong in stocks with high information uncertainty (high analyst dispersion, big past earnings surprises, low analyst coverage, and large trading volume), whose intrinsic values are difficult or costly for investors to estimate. Online search frequency as a direct indicator of retail investors’ reaction to signals also sheds light on the idiosyncratic volatility (IVOL) puzzle. I find that this puzzle is more pronounced in high-search-frequency subsamples and disappears in low-search-frequency subsamples. Further evidence shows that high search frequency strengthens the negative IVOL effect in stocks with positive signals but weakens this effect in stocks with negative signals. I suggest that the IVOL puzzle in the Chinese market can be partially explained as a reversal following overreaction to positive signals by retail investors.     

Left-tail momentum: Underreaction to bad news,costly arbitrage and equity returns

This paper documents a significantly negative cross-sectional relation between left-tail risk and future returns on individual stocks trading in the US and international countries. We provide a behavioral explanation to this anomaly based on the idea that investors underestimate the persistence in left-tail risk and overprice stocks with large recent losses. Thus, low returns in the left-tail of the distribution persist into the future causing left-tail return momentum. We find that the left-tail risk anomaly is stronger for stocks that are more likely to be held by retail investors, that receive less investor attention, and that are costlier to arbitrage.     

Piecing together the extent of retail fractional trading

We examine the introduction of fractional trading and its impact on retail security ownership. Fractional trading aims to increase investor access to securities with high prices. Over the initial months of Robinhood’s fractional trading program, the number of unique owners increases approximately 53 percentage points more for stocks priced above $100 versus those priced below $50. Intraday, high-price stocks exhibit incremental ownership growth specifically during periods when fractional trading is permitted. Our results show that Robinhood investors make ample use of fractional trading to acquire previously inaccessible securities, indicating a substantial reduction in price-based investing frictions and carrying implications for retail portfolio management. In addition, we show that potential market impacts of fractional trading appear negligible based on share volume data from multiple brokers with fractional trading programs.     

Retail Derivatives and Sentiment: A Sentiment Measure Constructed from Issuances of Retail Structured Equity Products

We use retail structured equity product (SEP) issuances to construct a new sentiment measure for large capitalization stocks. The SEP sentiment measure predicts negative abnormal returns on the SEP reference stocks based on a variety of factor models, and also predicts returns in Fama-MacBeth regressions that include a wide range of covariates. Consistent with our interpretation that SEP issuances reflect investor sentiment, aggregate SEP issuances are highly correlated with the Baker-Wurgler sentiment index. Tobit regressions reveal that proxies for attention and sentiment predict SEP issuance volumes, providing additional evidence consistent with the hypothesis that SEP issuances reflect sentiment.     

Does the location of stock exchange matter? A within-country analysis

The current study documents an interesting phenomenon that retail investors prefer to invest in stocks listed at the stock exchange that is geographically close to them in China. This pattern is robust when we control for the well-documented local bias within a country. Among companies with similar distances to both stock exchanges and companies headquartered locally, investors still display a strong tendency to invest in locally-listed stocks. Among stocks with similar distances to both stock exchanges, those listed in Shanghai (Shenzhen) co-move more in returns and trading volumes, with the benchmark at the Shanghai (Shenzhen) stock exchange. Such a preference for local exchange seems not to be motivated by information advantage, because investors do not obtain abnormal returns from their trades on stocks listed nearby. Our findings provide additional evidence that non-information-based familiarity bias induces investment and that such investor bias and exchange-level sentiment influence asset price formation.