I’m very new to Stata and statistical testing in general, but I have grown very fond of it.

I’m currently trying to analyze calendar anomalies on stock data, I have approximately 3700 observations of daily returns of which I have created dummy variables for each month of the year.

I initially made a simple linear regression containing all dummies, but later decided to go for a regression with Newey West standard errors to avoid autocorrelation and heteroscedasticity. I have so far applied lag(254) to represent the number of open stock market days per year, and hence one cycle of testing. Furthermore, I decided to remove the constant to avoid the any variables being omitted.

Command: newey stock_return dummy_jan dummy_feb dummy_mars dummy_apr dummy_maj dummy_juni dummy_juli dummy_aug dummy_sept dummy_oct dummy_nov dummy_dec, lag(254) noconstant

What are your thoughts on this reasoning and processes? Thereafter I have tried to conduct a Breusch-Godfrey and Breusch-Pagan to evaluate the presence of autocorrelation and heteroscedasticity after the Newey regression, but seemingly this does not work. Any recommendations are kindly accepted.

If I have placed this post in the wrong spot, please forgive me as this is my first post on the forum.