This article shows that correlated errors in news about fundamentals are an important, rational determinant of excess comovement. Individual analysts’ forecast errors tend to be correlated across stocks. Using a proxy for correlated forecast errors based on analyst coverage, I find that stocks with similar sets of analysts exhibit more excess comovement, controlling for industry and other variables. Exogenous changes in commonality in analyst coverage around i) brokerage firm mergers and ii) additions to an index lead to changes in excess comovement. This information channel explains 10% to 25% of the increase in comovement around additions to the S&P 500 index.

Previous research documents differences in trading desk skills across management companies that result in significant variation in execution costs. In this paper, we utilize links between management companies and their institutional clients to explore variation in execution costs within management companies. For a subset of management companies, we find that systematic differences in execution costs exist across clients; these differences are comparable to the variation documented across management companies and persist over time. Clients who receive lower execution costs reward management companies with an increase in dollar trading volume. We find no evidence that the results are driven by broker commissions or differences in trading practices. Given the economic significance of our findings and implications for institutional investors, this aspect of execution should be recognized regardless of the ultimate source of the differences.

We propose a direct measure of abnormal institutional investor attention (AIA) using news searching and news reading activity for specific stocks on Bloomberg terminals. AIA is highly correlated with institutional trading measures and related to, but different from, other investor attention proxies. Contrasting AIA with retail attention measured by Google search activity, we find that institutional attention responds more quickly to major news events, leads retail attention, and facilitates permanent price adjustment. The well-documented price drifts following both earnings announcements and analyst recommendation changes are driven by announcements to which institutional investors fail to pay sufficient attention. Received February 24, 2016; editorial decision December 29, 2016 by Editor Andrew Karolyi.

We examine the relationship between credit rating levels and rating agency fees in a public finance market in which rating agencies earn lower fees and face higher disclosure requirements relative to corporate bond and structured finance markets. Controlling for variation in the complexity of credit analysis at the issue level, we find evidence that rating agency conflicts of interest distort credit ratings in the municipal bond market. Unexpectedly expensive ratings are more likely downgraded, and inexpensive ratings are more likely upgraded. The relationship between credit ratings and rating agency fees is driven by issuers who lose access to AAA insurance.

A common belief held among researchers and policy makers is that regulatory reliance has inflated market demand for credit ratings, despite their decreasing informational value. Advances in information technology, coupled with reputation losses following the subprime crisis, renew the question of whether investors still rely on ratings to assess credit risk. Using Moody’s 2010 scale recalibration, which was unrelated to changing issuer fundamentals, we find that ratings still matter to investors and to issuers—apart from any regulatory implications. Our results commend improved disclosure to mitigate mechanistic reliance on ratings and inefficiencies due to rating standards that vary across asset classes. Received October 9, 2015; editorial decision June 7, 2017 by Editor Andrew Karolyi.

ABSTRACT We study whether firm and macroeconomic announcements that convey systematic information generate a return premium for firms that experience information spillovers. We use information consumption to proxy for investor learning during these announcements and construct ex ante measures of expected information consumption (EIC) to calibrate whether learning is priced. On days when there are information spillovers, affected stocks earn a significant return premium (5% annualized) and the capital asset pricing model performs better. The positive effect of the Federal Reserve Open Market Committee announcements on the risk premia of individual stocks appears to be modulated by EIC. Our findings are most consistent with a risk‐based explanation.