This study examines whether information revealed by firms’ earnings announcements (EAs) forecasts short-run market-wide volatility in equity index prices. Using an exponential generalized autoregressive conditional heteroskedasticity model that includes controls for the information in an array of macroeconomic announcements, we find that EA information aggregated across firms forecasts market volatility at daily and weekly intervals. EA information’s forecasting power is greatest when more firms announce earnings on a given day, when EAs convey negative news, and for EA information about core earnings. Out-of-sample tests confirm that forecasts incorporating EA information better predict short-run market volatility than forecasts omitting EA information. We conclude that firm-level EAs are a significant source of systematic, market-wide information relevant for predicting near-term market volatility. Data Availability: All data are publicly available from sources cited in the text.

We investigate the role of financial analysts in product quality failures. Relying on information about product recalls, we first show that analyst coverage on average reduces product quality, particularly when managers face greater short-term pressure from institutional investors. However, after identifying a subgroup of analysts who raise questions on product-related issues in earnings conference calls, we find that coverage by these “product analysts” enhances rather than compromises product quality. Firms with greater product analyst coverage are also more likely to retire low-quality products. Additional analysis demonstrates that product analysts help safeguard product quality by further probing into product-related matters and issuing more timely recommendation downgrades after firms announce product deficiencies. Data Availability: Data are available from the public sources cited in the text.