•Built program solely for Event Study, which checks and analyze the significance of different events’ influence on stock return
•Extracted data from SQL Server, computed statistical summary, visualized data through Matplotlib
•Modeled cumulative abnormal return (CAR) of classified stocks over benchmark within a 3 months’ time window through Numpy, Pandas, Datetime packages implemented in Python using OOP design
•Developed program that auto-generated daily stock investment filter based on events (news, announcements etc.)
•Detected positive and negative influence events out of 17 events, provided outline for reference and future updates