One of the required assumptions for multiple linear regression is that residuals are normally distributed, correct?
After running my regression, my normal probability plot is showing the typical 'heavy tail' S shape.
Does this inability to satisfy the assumption deem my whole model useless? Is there anyway I can get normal residuals?
My dependent variable is VaR, and my independent variables are Average Return, Log of Market value, dummy variable 1 and dummy variable 2.
Edit: I've tried transforming the independent variable (VaR)(Square root, Log, reciprocal), but it doesn't seem to make sufficient difference