I cordially invite you to attend my dissertation proposal scheduled on Wednesday, August 23rd, from 11:00 AM to 12:00 PM. You can join remotely via this Zoom link: https://gatech.zoom.us/j/8374913331

The abstract is included below, and copies of the proposal are available upon request.

Ruiqi Rich Zhu | Ph.D. Candidate

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Area: Information Technology Management

Committee Members: Dr. Yu (Jeffrey) Hu (co-chair, Purdue University), Dr. Sridhar Narasimhan (co-chair), Dr. Mingfeng Lin, Dr. Cheng He (University of Wisconsin-Madison)

Title: The New Investment Paradigm: How Information Technology Shapes Investor Behaviors

Abstract: Information technology and fintech have revolutionized the ways investors access information and make investment decisions. However, with the abundance of information in the digital age, comes with noise and inherent platform biases. Such distraction and biases could lead investors down paths of irrationality and suboptimal decision-making. My dissertation delves into the profound impacts of online platforms on investor behaviors. In my first essay, I examine the effects of recommender systems on online investor behaviors. The results show that funds featured by recommender systems prompt significantly more purchases. This effect is especially salient among unsophisticated investors, who appear more likely to follow system-provided recommendations. An in-depth examination suggests that these investors often face inferior investment outcomes after procuring the recommended funds. One significant reason we identified for this is the reduced effort and information-seeking behavior investors exhibit when opting for recommended funds over non-recommended ones. This reveals a concerning trend: recommender systems might inadvertently widen the wealth disparity among investors in financial landscapes. In my second essay, I explore how merger and acquisition (M&A) rumors on social media shape investment behaviors. While M&A information is valuable in predicting future stock movements, M&A rumors circulating on social media may not always be reliable. Using a unique dataset we curated through ChatGPT, our research discerned that rumors tend to be less reliable when associated articles project negative or ambiguous tones or spotlight high-profile firms. Moreover, we delve into the investor reactions to these rumor articles and the subsequent stock price reactions once such articles become public. Taken together, my two essays contribute to a better understanding of the potential positive and detrimental influence of information technology on investor behaviors.