Award at the 2005 European Finance Association Meeting, to the retail broker and discount

Abstract: A mutual-fund manager is more likely to hold (or buy, or sell) a particular stock in any quarter if other managers in the same city are holding (or buying, or selling) that same stock. This pattern shows up even when controlling for the distance between the fund manager and the stock in question, so it is distinct from a local-preference effect. It is also robust to a variety of controls for investment styles. These results can be interpreted in terms of an epidemic model in which investors spread information about stocks to one another by word of mouth.

at University of Notre Dame for helpful discussions and valuable comments. We thank Itamar Simonson for making the investor data available to us and Terrance Odean for answering numerous questions about the investor database. All remaining errors and omissions are our own. Do Dividend Clienteles Exist? Evidence on Dividend Preferences of Retail Investors We study the stock holdings and trading behavior of a representative group of more than 60,000 households and find evidence consistent with dividend clienteles. The stock holdings of retail investors indicate a preference for dividend yield that increases with risk aversion and age (the latter is consistent with life-cycle or consumption preferences) and decreases with income (consistent with low-tax investors holding high-yield stocks). The stock trading behavior of retail investors provide reinforcing evidence of these dividend preferences. Older, low-income investors disproportionally purchase stocks before the ex-dividend day. Among small stocks, the ex-day premium increases with age and decreases with income, which is consistent with tax explanations of the ex-day premium. We also find evidence that older, low-income investors purchase stocks after they initiate dividends. Finally, consistent with

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 in stock prices.

This paper develops a test of under-reaction to news induced by the presence of investors who display the tendency to realize gains and ride losses, known as the disposition effect. The disposition effect, a widely documented fact in investor behavior, implies that stock prices underreact more to bad news when more current holders are facing a capital loss, and under-react more to good news when more current holders are facing a capital gain. I use a database of mutual funds holdings to construct a measure of reference prices for individual stocks. Using this novel measure of reference price, I show that post-event predictability is most severe when the disposition effect predicts the biggest under-reaction. I show that exposure to a disposition variable spreads the cross-sectional differences in post-event returns: post-event drift is bigger when the news and the capital gains overhang have the same sign and the magnitude of the post-event drift is directly related to the amount of unrealized capital gains (losses) experienced by the stock holders prior to the event date.

I describe asset price dynamics caused by the slow movement of investment capital to trading opportunities. The pattern of price responses to supply or demand shocks typically involves a sharp reaction to the shock and a subsequent and more extended reversal. Theamplitude oftheimmediate price impact andthepatternof the subsequent recovery can reflect institutional impediments to immediate trade, such as search costs for trading counterparties or time to raise capital by intermediaries. I discuss special impediments to capital formation during the recent financial crisis that caused asset price distortions, which subsided afterward. After presenting examples of price reactions to supply shocks in normal market settings, I offer a simple illustrative model of price dynamics associated with slow-moving capital due to the presence of inattentive investors.

and the Federal Reserve Bank of New York. We thank Michael Emmet and Priya Gandhi for excellent research assistance. The views stated here are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of New York, or the Federal Reserve System. We are responsible for all errors. Fifteen Minutes of Fame? The Market Impact of Internet Stock Picks We examine 120 Nasdaq and Over-the-Counter “buy ” recommendations made by Internet sites from April 1999 to June 2001. The stock picks show substantial short- and long run price and liquidity gains, although no new information is revealed about them. For example, turnover and market value one year after the pick month are higher for these stocks compared to a sample matched by size, book-to-market value, and liquidity. We find that, after controlling for fundamental, microstructure and momentum factors, stocks with lower initial liquidity have greater improvements in liquidity on the pick day. Further, stocks with lower initial liquidity and higher pick-day liquidity have higher pick-day excess returns. These results support the idea that stocks have multiple liquidity equilibria, and that the stock picks, by coordinating uninformed trading activity, push initially illiquid stocks to a higher liquidity equilibrium.

The Sarbanes-Oxley (SOX) Act of 2002 is one of the, if not the, most important pieces of legislation affecting corporations traded on the U.S. stock exchanges. While SOX does not explicitly address the issue of information security, the definition of internal control provided by the SEC, combined with the fact that the reporting systems in all firms required to comply with SOX are based on systems that promote information security and integrity does imply that more focus on information security is a necessary compliance requirement. Using a dataset on stock market abnormal returns that runs from the period 2000-2006 and consists of 300 firms, we aim to examine how the stock market reaction varies for 8-K filings and news media releases, and how this reaction has changed since the passage of the SOX Act. We hypothesize that the greater timeliness of the 8-K filings induced by SOX increases and accelerates the quality of their information disclosure and dissemination in the market. Further, we classify news articles into press- and firm-initiated articles and hypothesize that the press-initiated coverage of material events has increased in the post-SOX period. We find that the effect of firm-initiated media coverage had significant negative impact relative to press-initiated coverage on the measures of informativeness suggesting that media played a significant role during the scandal-ridden periods when the firms had poor information environment between 2002 and 2004. We also find that the timeliness of release of media articles determines the level of informativeness, suggesting that media is an information intermediary and its role acts as a substitute to the firm’s existing information disclosure environment

Abstract—Traditional movie gross predictions are based on numerical and categorical movie data. But since the 1990s, text sources such as news have been proven to carry extra and meaningful information beyond traditional quantitative finance data, and thus can be used as predictive indicators in finance. In this paper, we use the quantitative news data generated by Lydia, our system for large-scale news analysis, to help us to predict movie grosses. By analyzing two different models (regression and k-nearest neighbor models), we find models using only news data can achieve similar performance to those use numerical and categorical data from The Internet Movie Database (IMDB). Moreover, we can achieve better performance by using the combination of IMDB data and news data. Further, the improvement is statistically significant. I.

An unsupervised learning method, based on corpus linguistics and special language terminology, is described that can extract time-varying information from text streams. The method is shown to be ‘language-independent ’ in that its use leads to sets of regular-expressions that can be used to extract the information in typologically distinct languages like English and Arabic. The method uses the information related to the distribution of Ngrams, for automatically extracting ‘meaning bearing ’ patterns of usage in a training corpus. The analysis of an English news wire corpus (1,720,142 tokens) and Arabic news wire corpus (1,720,154 tokens) show encouraging results. 1