Welcome
I am Michael Casetta, a UT Austin Finance major with a Statistics & Data Science minor and pursuing a Certificate in Advanced Mathematics, focused on quantitative investing and research. I enjoy building institutional-style models in Python—from DCC-GARCH risk engines to factor studies like Fama-French—and document them clearly for reproducibility. My goal is to integrate rigorous math, clean code, and practical portfolio design to deliver research that scales from notebooks to production. The goal of my research is to consistently learn and improve to produce better and higher quality results.
Beyond classes, I work on multi-model strategies that blend forecasting, risk, and optimization. I am actively developing a GitHub portfolio, preparing for advanced finance study, and targeting research roles where I can contribute immediately on day one.
Course Schedule (Mon–Thu)
| Day | Time | Course | Title | Location |
|---|---|---|---|---|
| MW | 11:00 AM – 12:30 PM | STA 372T | Optimization | UTC 3.110 |
| MW | 12:30 PM – 2:00 PM | FIN 367 | Investment Management | GSB 2.120 |
| MW | 2:00 PM – 3:30 PM | MIS 301 | Intro to Information Systems | UTC 1.132 |
| MW | 3:30 PM – 5:00 PM | FIN 374C | Advanced Investment Analysis | UTC 4.328 |
Websites I Like
QuantStart
quantstart.com — Tutorials and articles on quantitative finance and algorithmic trading.
Investopedia
investopedia.com — Definitions and primers for finance, markets, and accounting.
CFA Institute
cfainstitute.org — Standards, research, and curriculum references.
Embedded Videos
Four videos on core finance concepts that I have either researched or am currently making projects about (Markowitz, CAPM/Fama-French, risk and return, and one broader investing explainer).
Copyright notes: All embedded videos remain the property of their respective creators on YouTube. This page only embeds them via the official player and does not host or redistribute the content.
About Me
I am passionate about building research-grade tools that bridge theory and practice. Recent work includes a Monte Carlo DCC-GARCH engine with CVaR/VaR reporting, factor regressions with OLS/Lasso/Elastic Net and K-Fold validation (In Progress), and a DCC GARCH Value at Risk model. I enjoy turning math and code into clear, decision-useful insights for portfolio construction.