In order to perform a price forecast, I built four linear models:1-3 have one independent variable, 4 has two independent variables. n = 28 in all cases

1. ad. R² = 0.91, AIC = -27, BIC = -25

2. ad. R² = 0.95, AIC = -37, BIC = -34

3. ad. R² = 0.97, AIC = -70, BIC = -68

4. ad. R² = 0.95, AIC = -35, BIC = -32

Which statements can be derived from these results?

As I understood the issue so far, the lower AIC/BIC score the better. However, both information criteria penalize the usage of more independent variables as the risk of overfitting increases.

Therefore, I would drive that model 3 is the best model as adjusted R² is high as well as AIC and BIC are the lowest of all four models. Further I would prefer 4 over 2 as ad. R² is the same and 4 as lower AIC/BIC scores even though it has two independent variables in comparison to one in 2. Model 1 would be the worst performing model.

Is it possible to make these statements?

Thank you very much for your clearification.

Best,

Anton