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Research & Interests

Here's what I've been building: research that spans continents, models that wrestle with uncertainty, and analyses that bridge theory and application. Every project taught me something I didn't know I needed to learn.

OPEC News

How do oil production decisions ripple through renewable energy markets? This study examines the causal relationship between OPEC quota announcements and clean energy stock volatility. I designed the technical infrastructure: building R pipelines for event study analysis, implementing Fama-French regression models, and developing time-series methods to quantify market sensitivity. By combining supervised learning with exploratory techniques, we're uncovering structural patterns in how traditional energy policy shapes the financial behavior of sustainable alternatives. Our findings are under review for publication in the Global Finance Journal.

My Senior Thesis: Bayesian Statistics

My thesis investigates financial risk dynamics in Sub-Saharan African economies using Bayesian inference methods. I'm developing R implementations of Hamiltonian Monte Carlo, Bayesian VARs, and Bayesian neural networks to model posterior distributions of risk parameters. This research compares Bayesian approaches with classical machine learning techniques to evaluate predictive performance in contexts where data is limited and uncertainty is high. The work addresses a critical gap: applying sophisticated statistical methods to regions often overlooked in quantitative finance literature, with implications for policy and investment decision-making.

Richter Scholar Program

Corporate environmental risk isn't just about reputation—it's measurable in balance sheets. I analyzed 10-K disclosures from S&P 500 companies to quantify how biodiversity-related risks correlate with financial leverage. Building fixed-effects regression models in R, I identified key drivers of environmental exposure and developed frameworks for sustainability-informed financial assessment. This research required navigating messy, unstructured corporate disclosures and transforming qualitative risk language into quantitative metrics. The work culminated in a presentation at Lake Forest College's Brain, Mind & Behavior Symposium to an audience of 200+ faculty, students, and alumni.

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