I employ computational methods and causal inference strategies to answer questions in financial economics and behavioral finance. My recent work focuses on construction of novel datasets using AI/NLP to predict market returns.
Working with Prof. Alexander Torgovitsky on replicating empirical tables/figures by translating partial identification strategies into Python/R code. Designing Monte Carlo simulations to evaluate finite-sample bias and variance of new estimators.
Constructed a large-scale dataset by crawling hundreds of thousands of corporate disclosure records. Estimated the causal impact of environmental regulations on firm behavior using quasi-experimental designs.