2 research outputs found
Analytics in the Pursuit of Knowledge: Adapting the Knowledge Pyramid
Advances in storage leading to the Internet of Things (IOT) and Big Data has exponentially increased the Data aspect of the traditional Knowledge Pyramid - Data-Information-Knowledge-Wisdom (DIKW). This paper presents an adaptation of the Knowledge Pyramid as an Analytics Pyramid in which Time is posited to represent Wisdom as the pinnacle achievement when pursuing knowledge. Analogies of the DIKW are presented from the Analytics Pyramid as Description-Aggregation-Modeling-Time. Implementing the premise of the Analytics Pyramid focuses on an interative/repetitive movement of both individuals and organizations through all Description-Aggregation-Modeling-Time stages in order to build and obtain the Wisdom pursued in the traditional Knowledge Pyramid. This model reinforces organizational learning and the importance of adaptability when pursuing knowledge. In addition, the wisdom gained from analytics is only recognized when monitored business processes are longitudinal in nature. Organizational analytics must rely on the recognition of a changing environment (Time) in order to adapt
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Essays on Investor Information Processing
This dissertation presents a collection of three essays on how investors process information, one of the most fundamental questions in finance. It employs advanced empirical techniques such as textual analysis and machine learning and spans various investor groups, including institutional investors, retail investors, and investors of emerging asset classes. The first essay âDoes Partisanship Affect Mutual Fund Information Processing? Evidence from Textual Analysis on Earnings Callsâ shows that partisan funds react stronger to information more consistent with their pre-existing beliefs. The second essay âPartisan Return Gap: The Polarized Stock Market in the Time of a Pandemicâ, co-authored with Jinfei Sheng and Zheng Sun, explores how political beliefs affect asset prices during the COVID pandemic. The third essay âHow Do Investors Value Technology in Cryptocurrency? Evidence from Textual Analysisâ, co-authored with Jinfei Sheng and Yukun Liu, examines how investors evaluate and process information about new technologies within the cryptocurrency market. Overall, this dissertation offers valuable insights into how various factors shape investor information processing and asset prices