Hi, I’m Thomas Martins 🇧🇷 / Martinez 🇪🇸, a quantitative risk analyst, economist and statistician with a strong background in time series forecasting and financial econometrics.
I build full-stack, production-grade tools for risk analytics and supervisory reporting, combining end-to-end data pipelines, probabilistic programming and economic models to deliver reproducible and interpretable outputs for regulatory metrics and risk management.
My portfolio includes three projects that demonstrate my ability to build data pipelines, deploy interactive dashboards, and integrate quantitative methods in a modern risk infrastructure:
An end-to-end platform for Basel III liquidity, capital, and IRRBB metrics, including DuckDB warehouse design, dbt transformations and tests, Dagster orchestration and Streamlit dashboard deployment. Live App | GitHub | Blog
A research project that links Bayesian macroeconomic modeling and scalable probabilistic programming in Python with Basel III IRRBB scenarios and NII/EVE impacts. Jupyter | GitHub | Blog
A quantitative framework for interest-rate risk hedging combining no-arbitrage term-structure models (Diebold–Li / DNS and AFNS) and stochastic simulation of yield-curve dynamics for NII hedging using optimal control and reinforcement learning. Jupyter | Pluto.jl | Live Widget
A model for non-maturing deposit rates combining state-space time series modeling for the yield-curve and Bayesian hierarchical modeling for sector heterogeneity and volume. Jupyter | GitHub | Blog
Alongside my professional activities, my research interests include:
I’m passionate about using Bayesian methods and structural modeling to answer complex economic questions at the intersection of statistics, finance and macroeconomics.
Curious about my academic work?
Visit my Research page for ongoing projects and ideas.
You can also explore some of my Blog posts
I have an open-access digital book:
Bayesian Methods in Asset Pricing
Feel free to reach out by email:
thomascsmartins (at) gmail.com
Thanks for visiting!
A bank’s net interest income is a sequential decision problem: choose a hedge every month as the yield curve moves. I model the curve with an arbitrage-free ...
I rebuilt my Basel ALM risk pipeline on a more modern, production-grade stack. It also includes a few novel models with the old ones, such as Hull-White 1...
Banks live and die by their cheapest source of funding: customer deposits in current and savings accounts. Unlike a fixed-term bond, these non-maturing depos...
Interest rate risk in the banking book (IRRBB) is one of the fundamental components of Basel III regulations. Supervisors require banks to evaluate the impac...