Data Science Tutorial: The Event Study -- A powerful causal inference model

In this tutorial, we'll dive into performing an event study using Python, perfect for data scientists, financial analysts, and anyone interested in causal inference methods. Learn how to download financial data with yfinance, calculate daily returns, and create dummy variables to capture specific event dates. We'll walk through setting up and running regression models with statsmodels, testing hypotheses about event impacts, and interpreting both daily and cumulative returns.
Whether you're exploring causal inference in finance or enhancing your data science toolkit, this step-by-step guide will help you understand how to design and implement robust event studies. We'll cover everything from data preparation and regression analysis to hypothesis testing with dummy variables, making it easy to apply these techniques in your own research or investment strategy.
Join us as we break down complex statistical methods into practical, actionable insights. Don't forget to like, subscribe, and hit the notification bell for more tutorials on advanced data analytics and causal inference methods in Python!
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