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