eventstudy

My quant portfolio leverages quantitative finance and data-driven insights to optimize investment strategies. Using advanced models, statistical analysis, and machine learning, I develop systematic trading strategies to capitalize on market inefficiencies and generate alpha.

Event Study package is an open-source R project created to facilitate the computation of financial event study analysis.

Financial Event Study made easy

Event-driven analysis of OPEC announcements on oil market returns using Python

Daily research pipeline scoring small-cap biotech trial catalysts against options-implied moves, trades base rates and mispricing, not predicted direction. Python, PostgreSQL.

Study of divorce-related Google queries in the United States in connection with COVID-19 pandemic and cosequent sanitary measures. Nowcasting model of state crude divorce rates thanks to Google Trends Indicators.

Difference-in-differences event study on IMF PortWatch satellite AIS data. Databricks lakehouse (PySpark, Delta, Lakeflow) + statsmodels + Tableau. Measures a 43.4% Red Sea traffic decline against 14 control chokepoints, with pre-registered windows and a placebo-validated estimator.