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 using 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 where institutional investors fail to pay sufficient attention.

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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.

Firms whose human capital is concentrated in a few irreplaceable employees lack diversification in their human capital stock, exposing them to key human capital risk. Using disclosures of “key man life insurance” to measure this risk, we show that exposed firms are riskier. These younger, smaller, growth firms have abnormally high volatility, and following announcement of key employee departures, the most exposed firms lose 8% of their value. Key employees tend to be highly educated. They are four times more likely to hold PhD degrees than top managers, and firms with key human capital are more innovative.

The appraisal of the "market value" of homes serving as the collateral for mortgages is a fundamental part of the underwriting process. If a loan should default, however, it is not the retail market value that the lender obtains, but rather the "recovery value." In this research, we show how recovery values differ from market values at origination and explore the reasons for the differences. Using a large sample of chattel mortgages on manufactured homes, we explore the relationship among the selling prices, the book values, and the fitted values from simple hedonic models with spatial autocorrelation. We then address the differences between selling prices at origination and recoveries from repossessed homes. We find that the spread between them varies systematically with home characteristics and especially with "atypicality," that is, with measures of how unusual a home is. Selling prices both at origination and recovery affect borrower defaults.For decades, property appraisal has been a mainstay of mortgage underwriting and is an essential element of the verification process for lenders. The appraiser provides a professional estimate of the value of the property that can be used to verify that the selling price is representative of current market conditions. The lender uses the appraisal to assess whether the loan will perform, that is, repay in full, and whether the loan will be profitable for the lender. But is the simple point estimate sufficient for assessing the risks associated with the collateral? Can lenders improve loan decisions with information on the expected second moment or with estimates of the likely recovery values from a default?In this research, we explore these issues with a large data set of chattel mortgages on manufactured homes. Manufactured homes, although little researched, are an increasingly important segment of the housing market. The Manufactured Housing Institute reports that 8% of the U.S. population lives in manufactured homes. In 2001, manufactured homes made up about 15% of residential starts.