Field of finance

The first chapter examines the role of information processing costs on post earnings announcement drift. Here I distinguish between hard information—quantitative information that is more easily processed—and soft information which has higher processing costs. Using the textual information inside Dow Jones News Service articles, I find that qualitative earnings information has additional predictability for asset prices beyond the predictability in quantitative information. I also find that qualitative information has greater predictability for returns at longer horizons, suggesting that frictions in information processing generate price drift. Using a tool from natural language processing called typed dependency parsing, I demonstrate that qualitative information relating to positive fundamentals and future performance is the most di¢ cult information to process.;The second chapter examines the role news and liquidity play in "pairs trading." Pairs trading involves taking a bet that the price paths of two stocks that have historically moved together will converge again after any divergence. Consistent with the view that profits to pairs trading comes through market making, i.e., short term liquidity provision and price discovery, we find that pairs trading profits are higher when the initial divergence is due to (a) news that temporarily reduces the liquidity of one of the stocks in the pair, or (b) news that affects both stocks in the pair, and there are a priori reasons to believe that one stock reacts faster to such news. Profits are lower when the initial divergence in prices is associated with value relevant news specific to a stock in the pair. Pairs involving smaller, less liquid and more volatile stocks tend to converge faster after initial divergence. When one of the stocks in the pair is more likely to have sluggish response to common information as evidenced by less common sell side coverage and institutional holdings, the risk of a margin call due to further divergence is lower. Closing out positions that do not converge within 10 days leads to higher risk adjusted returns ignoring transactions costs when compared to holding positions for 6 months.;The third chapter proposes a new way to measure investor attention which avoids the problems inherent in traditional measures like media articles and trading volume which are indirect proxies. We propose a direct measure of investor demand for attention—active attention—using search frequency in Google (SVI). In a sample of Russell 3000 stocks from 2004 to 2008, we find SVI to be correlated with but different from existing proxies of investor attention. In addition, SVI captures investor attention on a more timely basis. SVI allows us to shed new light on how retail investor attention affects the returns to IPO stocks and price momentum strategies. Using retail order execution in SEC Rule 11Ac1-5 reports, we establish a strong and direct link between SVI changes and trading by less sophisticated individual investors. Increased retail attention as measured by SVI during the IPO contributes to the large first-day return and long-run underperformance of IPO stocks. We also document stronger price momentum among stocks with higher levels of SVI, consistent with the explanation of momentum proposed by Daniel, Hirshleifer and Subrahmanyam (1998).