Evaluating Model Predictions Using RMSE

Easy Time-series Analysis Model Evaluation

In a recent study of the monthly returns of a particular stock over a five-year period, an analyst calculated the following metrics: the mean return was 1.5% per month, while the variance of the returns was 0.04. To evaluate the performance of a predictive model that attempts to forecast these returns, the analyst uses the Root Mean Squared Error (RMSE) metric, which is essential for assessing the accuracy of the model's predictions.

Given RMSE values for two different predictive models, Model A with an RMSE of 0.025 and Model B with an RMSE of 0.03, which of the following statements about the evaluation of these models is accurate?

Model A provides more accurate predictions than Model B since it has a lower RMSE.

RMSE values can be interpreted directly in terms of stock return percentages.

Both models are equally effective in prediction as RMSE alone does not determine model performance.

Hint

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