The Economic Applications of Firm-Specific Digital Footprints
PI: Dr. Alan Kwan, HKU
Co-Is: Prof. Andrew Karolyi, Cornell University, Dr. Ben Matthies, Notre Dame College, Dr. Yukun Liu, University of Rochester & Dr. Gaurav Kankanhalli, University of Pittsburgh
This project combines two fields of research that have gained significant traction over the last decade: textual analysis – using machine learning to process unstructured text from the news and other types of documents – and digital footprints – digital traces of how firms interact with digital services. This project combines these elements , studying firm-specific digital footprints in the form of how firms read internet content such as news. This category of data – intent data – is a new phenomenon in the data analytics space and represents a large untapped resource for financial applications.
I have an ongoing collaboration with an industry partner who is the category leader in intent data. Through this collaboration, I have a dataset that measures specific firms reading specific pieces of internet content. On a daily basis, this involves over 1 billion content interactions. I show that these digital footprints are extremely powerful predictors of firm outcomes such as company earnings and ESG performance. The goal of this project is to develop further applications of this data, such as measuring firms that want to raise capital, the composition of firms’ corporate culture, or understanding how investors reading the news affects the formation of asset prices.