I'm doing my master thesis which consists on performing thousands of simple linear regressions around earnings announcements. So, I have several earnings announcements (the date of each earning announcement is the day 0) which I have to regress from day0-300 to day0-46, on the market index.
I have 3 datasets, the Market dataset (returns on S&P), the CRSP dataset (returns on stocks) and the Earnings dataset.
To run each regression, I start with an observation from the Earnings datset from which I get an earning announcement date which is linked to a specific company. And then, I perform the regression based on the estimation range mentioned before (using the time-series from Market dataset and CRSP dataset). The Earnings dataset and the CRSP dataset should be linked by PERMNO.
The objective is to add to every observation in the Earnings dataset an intercept and a slope.
To start, can you tell me how can I perform multilple simple linear regressions and extract just the intercept and the slope for each of them?
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