We develop a theory of market crashes based on differences of opinion among investors. Because of short-sales constraints, bearish investors do not initially participate in the market and their information is not revealed in prices. However, if other previously bullish investors bail out of the market, the originally bearish group may become the marginal "support buyers," and more will be learned about their signals. Thus accumulated hidden information comes out during market declines. The model explains a variety of stylized facts about crashes and also makes a distinctive new prediction—that returns will be more negatively skewed conditional on high trading volume.

We develop a theory of market crashes based on differences of opinion among investors. Because of short-sales constraints, bearish investors do not initially participate in the market and their information is not revealed in prices. However, if other previously bullish investors bail out of the market, the originally bearish group may become the marginal “support buyers,” and more will be learned about their signals. Thus accumulated hidden information comes out during market declines. The model explains a variety of stylized facts about crashes and also makes a distinctive new prediction—that returns will be more negatively skewed conditional on high trading volume.

We examine security analysts' career concerns by relating their earnings forecasts to job separations. Relatively accurate forecasters are more likely to experience favorable career outcomes like moving up to a high‐status brokerage house. Controlling for accuracy, analysts who are optimistic relative to the consensus are more likely to experience favorable job separations. For analysts who cover stocks underwritten by their houses, job separations depend less on accuracy and more on optimism. Job separations were less sensitive to accuracy and more sensitive to optimism during the recent stock market mania. Brokerage houses apparently reward optimistic analysts who promote stocks.