Defining ambiguity as investor's uncertainty about the precision of the observed information, Chapter One constructs an empirical measure of ambiguity based on analysts' earnings forecast information, and finds that the market tends to react more negatively to highly ambiguous bad news, while it tends to be less responsive to highly ambiguous good news. This result supports the theoretical argument of Epstein and Schneider (2003, 2008) that ambiguity-averse investors take a worst-case assessment of the information precision, when they are uncertain about the information precision. In addition, Chapter One shows that returns on stocks exposed to highly ambiguous and intangible information are more negatively skewed. Chapter Two finds that certain traders are informed about either the forthcoming analysts' forecasts or long-term value of the stock, and informed traders prefer to use medium-size trades to exploit their private information advantage. Specifically, medium-size trade imbalance prior to the forecast announcements is positively correlated with the nature of forecast revisions, while in the days immediately after the forecasts medium-size trade imbalance is positively correlated with future stock returns for up to four months. Small-size trade imbalance is also positively correlated with future returns but only following downward revisions. In contrast, it is also shown that large trades placed right after the forecasts are unprofitable and generate slightly negative profits in the long run. Overall, our results are consistent with the "stealth trading hypothesis" proposed by Barclay and Warner (1993).