In this paper we examine the time-series and cross-sectional volatility in analyst forecasts. We derive a bound on the degree of variation in forecasts, analogous to the variance bound literature in finance, and document the frequency and circumstances surrounding violations of this bound. We find that the time-series of individual forecasts are excessively volatile approximately 17 percent of the time, affecting up to 50 percent of the aggregate market value of stocks. We also find that the market-wide frequency of excessively volatile forecasts in a year is positively correlated with aggregate stock market volatility and market sentiment, and is negatively correlated with future aggregate stock returns. We find that the cross-section of analyst forecasts are excessively volatile approximately 8 percent of the time, and observe that excessively volatile forecasts are more common for larger firms. As a precursor to identifying the underlying causes and consequences of excessively volatile forecasts, we describe the time period characteristics, analyst characteristics, and firm characteristics that are associated with these events.