Causal Effect of Fed Credit Facilities on Bond Spreads
Novel identification strategy using ratings heterogeneity + causal ML for counterfactual estimation.
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Rayhan Momin
Macro and rates researcher at PNC CIO. Focused on macro-finance, causal inference, econometrics, and ML tooling.
I hold a PhD in Finance and an MBA from the University of Chicago Booth School of Business. Previously, I worked as a research assistant at the Federal Reserve Board of Governors and as an analyst at JPMorgan. I earned my BA in Economics-Mathematics from Columbia University.
Featured Writing
Heterogeneous Treatment Effects via Deep Neural Networks
Semi-parametric DiD estimator with deep neural networks for dynamic treatment effects and policy counterfactuals.
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Laubach-Williams r* in Python
Python implementation of the natural rate of interest model used for monetary policy analysis.
View projects →Causal ML Auto-Inference
Automated inference toolkit for causal machine learning estimators with valid confidence intervals.
View projects →Focus Areas
- Causal Machine Learning
- Applied Econometrics
- Asset Pricing
- Macro-Finance & Monetary Policy