Stone, Dan
PI: Dan Stone
Research Overview
We apply new information technologies, such as machine learning and natural language processing, to the text and language in corporate disclosure to extract meaning and provide new insights into corporate disclosure.
Project: Earnings Conference Calls and Lazy Prices
Description: In my research I explore how the topic overlap between earnings conference calls and financial reporting, and how the comparison languages used in the earnings conference calls mitigate the “laziness” of stock prices.
Students:
Chuancai Zhang, PhD, Fellowship RCTF Graduate Scholarship (University of Kentucky)
Collaborators:
Computational methods:
Topic Modeling: Latent Dirichlet Allocation (LDA)
Differential Evolution (DE)
Software:
Python, Pycharm, and Anaconda
Grants:
Publications:
Center for Computational Sciences