Evaluation of Time-Series Models Using MSE and Adjusted R-squared

Very Hard Time-series Analysis Model Evaluation

Consider a time-series analysis where an analyst is evaluating two models: Model A and Model B. Model A has a mean squared error (MSE) of 10, while Model B has an MSE of 15. The analyst also computes the adjusted R-squared values for both models, finding that Model A has an adjusted R-squared of 0.85, whereas Model B has an adjusted R-squared of 0.80. The analyst aims to determine which model performs better overall.

Which of the following statements correctly characterizes the evaluation of these two time-series models, based on their MSE and adjusted R-squared?

Model A is superior to Model B since it has a lower MSE and a higher adjusted R-squared.

Model B cannot be evaluated against Model A because the adjusted R-squared is the only valid metric.

Both models are equally effective as the differences in their MSE and adjusted R-squared are negligible.

Hint

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