We investigate whether the returns of industry portfolios predict stock market movements. In the US, a significant number of industry returns, including retail, services, commercial real estate, metal, and petroleum, forecast the stock market by up to two months. Moreover, the propensity of an industry to predict the market is correlated with its propensity to forecast various indicators of economic activity. The eight largest non-US stock markets show remarkably similar patterns. These findings suggest that stock markets react with a delay to information contained in industry returns about their fundamentals and that information diffuses only gradually across markets.

We investigate the financial recontracting of firms completing distressed exchanges and those reorganizing under Chapter 11. We find that recovery rates for creditors, on average, are higher in distressed exchanges than in Chapter 11 reorganizations, as are equity deviations from absolute priority. The difference in deviations potentially provides valuable information on the higher costs of formal reorganization. Also, cash is used more extensively to redeem creditors' claims in Chapter 11 than in distressed exchanges. The greater use of cash can be attributed to provisions of the Bankruptcy Code that permit conservation of cash and facilitate asset sales.

We put forward a model in which analysts are uncertain about a firm’s earnings process. Faced with the possibility of using a misspecified model, analysts issue forecasts that are robust to model misspecification. We estimate that this mechanism explains approximately 60% of the autocorrelation in analysts’ forecast errors. The remainder stems from the cross-sectional variation in mean forecast errors and in analysts’ estimation errors of the persistence of earnings growth shocks. Consistent with our model, we find that analysts learn about some features of the earnings process but not others, and this learning reduces, but does not eliminate, the autocorrelation of forecast errors as firms age. Other potential explanations for the autocorrelation of analyst forecast errors are rejected. Our model of robust forecasting applies not only to analysts’ forecasts but also to all model-based forecasts.