Event Study Google Sheets Template
Run professional event studies directly in your spreadsheet. No coding required.
The template supports 3 return models -- Market Model, Mean Adjusted, and Market Adjusted -- and handles up to 500 events per analysis. As emphasized by MacKinlay (1997), the Market Model remains the most widely used expected return model in event study research, explaining approximately 20-30% of the variance in daily stock returns for a typical firm. This spreadsheet-based approach makes rigorous event study methodology accessible to researchers without programming experience.
How It Works
Three Steps to Results
Go from raw data to publication-ready event study results in minutes.
Enter Your Data
Add event dates, firm tickers, and configure your event window in the template.
Fetch Market Data
The template automatically fetches stock prices and market index data.
View Results
Get abnormal returns, cumulative returns, and test statistics instantly.
Models
Included Return Models
Three well-established approaches to estimating expected returns.
Market Model
Estimates expected returns using the CAPM relationship between stock and market.
Mean Adjusted Model
Uses the average historical return as the expected return benchmark.
Market Adjusted Model
Uses the market return directly as the expected return.
Features
Everything You Need
A complete toolkit for spreadsheet-based event study analysis.
- Automatic stock price data fetching
- Market Model, Mean Adjusted, Market Adjusted
- Cumulative Abnormal Returns (CAR)
- T-test and Sign test statistics
- Downloadable CSV results
- Works in Google Sheets and Excel
FAQ
Frequently Asked Questions
How much does it cost?
The template is available for purchase on Gumroad with no recurring fees or limitations.
Do I need programming skills?
No, everything works in the spreadsheet interface.
What data sources does it use?
Stock prices are fetched automatically from Google Finance.
Can I use it for academic research?
Yes, but for advanced analyses (panel DiD, synthetic control, etc.), we recommend the R package.
Need More Power?
The R package offers 15 return models, 12 test statistics, panel DiD estimators, synthetic control, and much more.