Investigating Predictive Power of Stock Micro Blog Sentiment in Forecasting Future Stock Price Directional Movement

This study attempts to discover and evaluate the predictive power of stock micro blog sentiment on future stock price directional movements. We construct a set of robust models based on sentiment analysis and data mining algorithms. Using 72,221 micro blog postings for 1909 stock tickers and 3874 distinct authors, our study reveals not only that stock micro blog sentiments do have predictive power for simple and market-adjusted returns respectively, but also that this predictive accuracy is consistent with the underreaction hypothesis observed in behavioral finance. We establish that stock micro blog with its succinctness, high volume and real-time features do have predictive power over future stock price movements. Furthermore, this study provides support for the model of irrational investor sentiment, recommends a supplementary investing approach using user-generated content and validates an instrument that may contribute to the monetization schemes for Virtual Investing Communities

Doctor of Philosophy

dissertationDue to the popularity of Web 2.0 and Social Media in the last decade, the percolation of user generated content (UGC) has rapidly increased. In the financial realm, this results in the emergence of virtual investing communities (VIC) to the investing public. There is an on-going debate among scholars and practitioners on whether such UGC contain valuable investing information or mainly noise. I investigate two major studies in my dissertation. First I examine the relationship between peer influence and information quality in the context of individual characteristics in stock microblogging. Surprisingly, I discover that the set of individual characteristics that relate to peer influence is not synonymous with those that relate to high information quality. In relating to information quality, influentials who are frequently mentioned by peers due to their name value are likely to possess higher information quality while those who are better at diffusing information via retweets are likely to associate with lower information quality. Second I propose a study to explore predictability of stock microblog dimensions and features over stock price directional movements using data mining classification techniques. I find that author-ticker-day dimension produces the highest predictive accuracy inferring that this dimension is able to capture both relevant author and ticker information as compared to author-day and ticker-day. In addition to these two studies, I also explore two topics: network structure of co-tweeted tickers and sentiment annotation via crowdsourcing. I do this in order to understand and uncover new features as well as new outcome indicators with the objective of improving predictive accuracy of the classification or saliency of the explanatory models. My dissertation work extends the frontier in understanding the relationship between financial UGC, specifically stock microblogging with relevant phenomena as well as predictive outcomes

The Web 2.0 as Marketing Tool: Opportunities for SMEs

The new generation of Internet applications widely known as Social Media or Web 2.0 offers corporations a whole range of opportunities for improving their marketing efficiency and internal operations. Web 2.0 applications have already become part of the daily life of an increasing number of consumers who regard them as prime channels of communication, information exchange, sharing of expertise, dissemination of individual creativity and entertainment. Web logs, podcasts, online forums and social networks are rapidly becoming major sources of customer information and influence while the effectiveness of traditional mass media is rapidly decreasing. Using the social media as a marketing tool is an issue attracting increasing attention. The hitherto experience is that large public corporations are more likely to make use of such instruments as part of their marketing and internal operations (McKinsey, 2007).The paper defines the Web 2.0 phenomenon and based on the experience of large corporations examines how SMEs could engage the various Web 2.0 instruments in order to efficiently market their products, improve customer relations, increase customer retention and enhance internal operations

Critical Analysis of Social Processes and Goal Orientation in an Online Financial Community

No Full Tex

CrowdIQ: A New Opinion Aggregation Model

In this study, we investigate the problem of aggregating crowd opinions for decision making. The Wisdom of Crowds (WoC) theory explains how crowd opinions should be aggregated in order to improve the performance of decision making. Crowd independence and a weighting mechanism are two important factors to crowd wisdom. However, most existing crowd opinion aggregation methods fail to build a differential weighting mechanism for identifying the expertise of individuals and appropriately accounting for crowd dependence when aggregating their judgments. We propose a new crowd opinion aggregation model, namely CrowdIQ, that has a differential weighting mechanism and accounts for individual dependence. We empirically evaluate CrowdIQ in comparison to four baseline methods using real data collected from StockTwits. The results show that, CrowdIQ significantly outperforms all baseline methods in terms of both a quadratic prediction scoring measure and simulated investment returns