Summary
José Neto is a Senior Quantitative Analyst and PhD candidate in Finance at Kellogg with nine years of experience applying empirical asset pricing, financial econometrics, and machine learning to real-world markets. Based in São Paulo, he blends academic research at Northwestern with industry work at XP Inc., bringing rigorous econometric modeling and high-frequency market analysis to institutional practice. His background includes building databases and forecasting models for Brazil’s COVID-19 response and lending/interest-rate dynamics, reflecting strong data engineering and policy-relevant modeling skills. Comfortable moving between theory and production, he has collaborated with central market institutions like B3 and FEBRABAN, investigating trader behavior and disaggregated financial flows. Notably, he pairs advanced machine-learning tools with deep domain expertise in asset pricing to extract actionable signals from noisy, high-frequency data.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Arts - BA Economics, Bachelor of Arts - BA Economics at Ibmec
Kellogg School of Management
Master of Science - MS Economics, Master of Science - MS Economics at FGV EESP
Portuguese, Spanish, English