Reading and Writing Papers
: One-liner summaries of core papers in finance academia
: Short tips on writing, list of good examples in empirical and theoretical economics
: Specific tips on how to critically assess an economics research paper, useful for discussions & referee reports
What I Learned in Grad School
: General takeaways on coursework and the core exam
: Thoughts on coursework and the curriculum paper
: Tips on TA, reading groups, and project management
: Self-Evaluation checklist for more productive research
What I Did in Grad School
My Setup for Productive Research
: Presentation to Incoming Booth PhD Students on Workflow, Apps and Technology, Getting New Ideas
Booth ML in Finance Reading Group
: Reading group on ML applications in finance that I co-created and organized
: Regular survey exploring PhD students' views on vital policy issues and timely topics
Code and Data
: Compilation of plausibly exogenous variation used in empirical economics work (updated daily through this listserv)
Variables Construction in Finance
: Compilation of norms on constructing often-used variables in finance research
: Collection of publicly available high-frequency data
Conference Discussions
1. Estimating a Model of Decentralized Trade with Asymmetric Information [Slides]
• By Tristan Hennig / Bank of England, Modelling with Big Data & Machine Learning (Nov 2020)
2. Internal Models, Make Believe Prices, and Bond Market Cornering [Slides]
• By Ishita Sen and Varun Sharma / EFA (Apr 2021)