DescriptionFinancial analysts, as information intermediaries in capital markets, collect information, interact with management and process information to provide their clients useful advice. This dissertation focuses on analysts’ forecasting activities to shed light on the analyst-management interaction and analysts’ information processing activities. The first essay examines whether firm characteristics, in particular growth properties, motivate managers to take action to meet or exceed analysts’ revenue forecasts. I find that growth firms are more likely to achieve zero or positive revenue surprises than non-growth firms. Further, revenue manipulation appears to be a preferred tool for growth firms to avoid unfavorable revenue surprises than revenue expectation management. This differential appears to be due to the incremental effectiveness of revenue manipulation for growth firms. The second essay, using analysts’ earnings forecasts, examines whether estimates of post-earnings-announcement returns derived from the historical firm-specific relation between unexpected earnings and drift returns help predict future post-earnings-announcement returns. I find that firms with historically high post-earnings announcement returns continue to experience high post-earnings announcement returns following future earnings surprises. The final essay investigates whether individual analysts who possess superior forecasting performance benefit from private information obtained from their access to selective disclosure or from their innate information processing skills. The frequency of extreme earnings forecasts is used to proxy for analysts’ reliance on private information. The empirical analysis reveals that private information contributing to analysts’ superior performance primarily stems from analysts’ privileged access to corporate management rather than from their inherent information processing skills.