Decision-making is often considered to be a rational and cognitive process; however, recent literature shows that human emotions play a very important role in the decision-making process. Despite the overwhelming evidence from the psychology literature, there has been little recognition and consideration for the role of human emotions in financial decision-making. In order to cover this research gap, our study examines the relationship between emotions proxied by the news and social media and the decision-making process of investors. The 10 different emotions that we evaluate are calculated on an ongoing basis by applying advanced algorithms which scan listings on the news and social news media. Our sample consists of firms listed on the S&P500 and covers the 20 years from 1998 to 2017. We recognise that there are two channels through which emotions impact on market valuations: one being a direct impact and the other being an indirect path through which emotions condition how investors respond to information signals. The first empirical chapter of the study investigates the impact of emotions on investor behaviour at the time of the earnings announcement. We find that Aggregate_Emotion, the aggregate across our individual emotions, has a significant impact on the decision-making of investors, as does the aggregate of both the positive and negative emotions considered. Our findings concerning individual emotions are mixed: while optimism and joy, and stress and gloom all impact on investor decision, anger and fear prove to be emotions that have little or no impact on investor behaviour. We also consider the relative impact of the two media sources, and we reveal mixed findings. For example, with social media, we find the greatest influence with respect to love/hate, whereas, for the news media we see a greater influence in the case of trust. The second chapter studies the impact of emotions during the post-earnings announcement drift (PEAD). PEAD is one of the longest surviving anomalies that challenge the efficient market hypothesis. While several studies have identified factors such as liquidity risk, arbitrage risk, and unsophisticated investors etc. that cause PEAD to persist, our results show that human emotions are yet another factor that plays a role in explaining the existence of this long-standing anomaly. Our results suggest that the drift can be explained by both the level of emotions at the time of the announcement but even more so by the direction of the level of emotions during the post-announcement period. All the individual positive emotions contribute towards how the investors value stocks over the post-announcement period, whereas the results for individual negative emotions are a bit weaker when compared to positive emotions. Finally, in the third empirical chapter, the focus is on identifying whether it is possible to use available information on human emotions to identify and exploit mispricing in stock pricing. Using the insights from the first two empirical chapters, we develop a two-part strategy that invests in the firms on the basis of aggregate positive and negative emotions. The first part of the strategy involves going long(short) when there is an exceedingly positive(negative) earnings announcement, and the positive(negative) emotions are in the bottom quartile before the earnings announcement. In the second part, we reverse the trade when the emotion either increases by a pre-specified amount or we reach the end of a pre-specified period. Our investment strategy(ies) produces significant positive returns, even after we take account of trading costs and factor exposures. Efficient Market Hypothesis (EMH) argues that in a well-functioning financial market, new information gets instantly reflected in the stock prices. Our results are at odds with EMH and show that emotions can cause underreaction at the time of the release of new information. Furthermore, we also show that there is no automatic correction of the stock prices in the post-announcement period as the direction of the stock valuations is influenced by the direction that emotion takes in the post-announcement period. Overall, the results of our studies show that emotions play a significant role in impacting the decision-making process of investors and shaping stock prices.