I will be joining the Chicago Booth School of Business as an assistant professor of finance this summer.

I am a 5th year PhD candidate in financial economics at the Yale School of Management. Much of my work leverages machine learning and natural language processing to address key questions in economics and finance. My current focus is on developing measures of beliefs with applications to asset pricing and behavioral economics.

Before Yale, I was a researcher at Booth, received a master’s degree in statistics from the University of Michigan, and completed my undergraduate degree in economics at the University of Chicago.


  • Ph.D. in Financial Economics, Yale School of Management
  • M.S. in Statistics, University of Michigan, 2017
  • B.A. in Economics, University of Chicago, 2013

Job Market Paper

1. The Ghost in the Machine: Generating Beliefs with Large Language Models
This version: December 2023
[Abstract] [PDF]
Finalist for BlackRock Applied Research Award
Subsumes Surveying Generative AI’s Economic Expectations


2. Business News and Business Cycles
(with Bryan Kelly, Asaf Manela, and Dacheng Xiu)
Forthcoming at Journal of Finance
This version: April 2023
[Abstract] [PDF] [NBER] [SSRN] [Data]

3. Narrative Asset Pricing: Interpretable Systematic Risk Factors from News Text
(with Bryan Kelly and Yinan Su)
Review of Financial Studies
This version: May 2023
[Abstract] [PDF] [RFS] [SSRN] [Code] [Data]

4. Change-point Computation for Large Graphical Models: A Scalable Algorithm for Gaussian Graphical Models with Change-points
(with Yves Atchadé)
Journal of Machine Learning Research
This version: January 2018
[Abstract] [PDF] [JMLR] [Code]

Working Papers

5. Asset Pricing with Narrative Churn
(with Hongyu Wu)
This version: October 2023

6. Associative Memory is Machine Learning
(with Tianshu Lyu)
This version: September 2023

7. Macro-based Factors for the Cross-Section of Currency Returns
(with Leandro Gomes and Joao Valente)
This version: May 2023
[Abstract] [PDF] [SSRN] [Code]

Code & Data

  • regIPCA

    A penalized implementation of instrumented principal components analysis in Python.

  • The Structure of Economic News

    Data and summaries for the 180 topics estimated for Business News and Business Cycles.

    Recession Attention

  • DiSTL

    A collection of efficient Gibbs sampling implementations for latent Dirichlet allocation in Python.

  • glVAR

    A fast method for group lasso vector autoregression in Python.

  • labbot

    A set of Python decorators useful for iterative development of research code.

  • IPCA

    A Python implementation of instrumented principal components analysis (with Matthias Buchner).

  • statsmodels

    I contributed the distributed estimation procedure of Lee et al. (2015) for penalized estimators.

  • changepointsHD

    An R implementation of a simulated annealing algorithm for change-point detection.